Take this network from 3rd to 1st on Paradigm's Prediction Market challenge (https://www.paradigm.xyz/puzzles/prediction-market-challenge), in rounds that build on each other instead of one wave of separate attempts.

A Python class quotes passive limit orders on one simulated binary market, scored by mean edge over 200 simulations. Simulator and rules: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e. Run it single-process without --sandbox: --workers is refused on some machines and --sandbox fails on Python 3.12.

Standing on 2026-11-05: 3rd of 186 at 104.84 (retail 128.63, arbitrage -23.79). First 109.59 (130.77, -21.18), second 109.43 (127.73, -18.31). The gap is mostly arbitrage loss.

Start from wave 3's best, combine-cash, +2.08 paired holdout gain (standard error 0.41) over the base: https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741 . Independent alternative, simplify: https://api.imd.fun/artifacts/5aa77c807417d8eb4743635be24fb9590f57e3e636dfb11050dd283e0a14ad6d . The base: https://api.imd.fun/artifacts/5ec4e47200eb5e16cec281f133e5e7fbfd73b3157fcf5f2c60d013ffa9300b76 . Wave 3's report, every result and what it learned: https://github.com/Identity-md/research/blob/main/jobs/c4cb1c7f-a37c-466a-9a72-14427ce0b354/files/artifacts/goal/writeup/report.md

How to run the rounds:

Keep a scoreboard in your notes: the current best's code hash, and each candidate's paired difference against it.
Every item measures against the current best on the same seeds, paired, with a standard error, and its tuning seeds never overlap its holdout. One 200-run mean has a standard error near 12, so only paired differences over thousands of seeds rank candidates.
Keep seeds 900000 to 903999 untouched for finalists, run only by your measure items. Promote a new best only when its paired gain there exceeds twice its standard error.
Split each round: about 40% combine and deepen what the scoreboard says works, 30% fresh mechanisms, 15% take away, 15% measure and replicate. Fresh items read none of the files above and look for one mechanism the best lacks. Wave 3 measured knowing the next step's probability as worth +24 and retail parameters +1: probability and jump estimation, and less arbitrage loss, are the levers.
No two items in a round try the same idea; name each item's idea in its brief.
Each item returns JSON: approach, tried, next, code, code_sha256, its tuning score, and its paired difference with standard error.
Stop after two rounds in a row with no promotion, or at the last episode.

Write-up: the best strategy's full code, ready to submit, its evidence on the finalist seeds, and a ranked table of every promotion.

The answer

Prediction Market challenge: from 3rd to 1st, the final strategy and its evidence

1. The strategy to submit

The best file is T, the code field of https://api.imd.fun/artifacts/79af781a0f1882f2a291e045f803714b52128f9938480d54fb43360417b381ac.


code_sha256 (UTF-8 bytes of the file)	`9fba1eb5659d5b0ac9b7273a968a520ef9a95551c697be22020993005af70192`
size	43,168 bytes, 896 lines
Paradigm standing (requester's note, 2026-11-07 02:05Z)	1st at 110.87 (2nd 110.69, 3rd 109.59); the objective started from 3rd at 104.84
paired gain over wave 3's combine-cash on seeds 900000..903999	+3.502 (standard error 0.336), n = 4000, 0 failures, run on this machine during the write-up (section 3.1)
paired gain over MA, its direct base	+1.227 (se 0.354) on T's own holdout 170000..170999, n = 1000; +0.66 on Paradigm's runs; a partial check here on 744 finalist seeds gave +0.185 (se 0.265), so this link is the least established (section 3.2)
check values (unmodified simulator b244530e, seeds 310000..310003, total_edge)	17.899934, 24.258579, 2.433424, 259.215142
runtime	about 1.35 s a simulation serial here, equal to its base MA (1.37 s); it passed Paradigm's sandbox, which stops a submission at about 270 s for 200 runs

The file is submittable as is. Section 2 is the file in full; section 3 is its evidence on the finalist seeds; section 4 is the ranked promotion table; section 5 is what the next run should try.

What T is. T is goal 7be68b75's x-plus-b: the per-spread merge MA (149883fe…, itself a sibling goal's merge of four spread-specific blocks) with four changes that this goal found or measured, carried by hand and gated per competitor spread through one table on line 34:

ON = dict(cancel=(2, 3, 4), cut=(1, 4), postjump=(1,), premium=(), deadband=(3,))

cancel (spreads 2, 3, 4): this goal's retreat cancel (RC). When the rival's bid falls exactly one tick or its ask rises exactly one tick, cancel every own order on that side and place nothing there for one callback, clearing that side's probe and exposure bookkeeping. The one change that passed this goal's finalist gate (section 4).
cut (spreads 1, 4): belief weight multiplied by 0.016 on the stale side after a one-tick rival retreat. The descendant of this goal's retreat-crossing family (runner-up in section 4).
postjump (spread 1): the spread-1 jump-withhold wrapper plus its qb_z = 4 bank condition.
premium (off everywhere): the spread-4 ask risk premium change; measured negative and left off.
deadband (spread 3): keep_lo replaced by 1 in add_b and add_a.

A run has one competitor spread, read from the rival's first quotes as self.s (ask minus bid equals 2s minus 1), so each entry acts on its spreads only and the entries compose.

No code repository. The goal ran research batches only; no code batch was spawned and goal.json names no trunk. Every candidate lives as the code field of a result artifact at https://api.imd.fun/artifacts/<result SHA-256>.

2. Full code of T

Save the block below as a .py file. Its UTF-8 SHA-256 must be 9fba1eb5659d5b0ac9b7273a968a520ef9a95551c697be22020993005af70192 (the file ends with a newline after the last line).

"""Crossing-cover base with isolated, untuned per-spread overrides stacked: each acts only in runs of its own competitor spread."""
import math
from orderbook_pm_challenge.strategy import BaseStrategy
from orderbook_pm_challenge.types import CancelOrder, PlaceOrder, Side

P = dict(lam_r=0.25, m=5.0, sig_n=1.2, lam_j=0.0019, sig_j=0.35, sig=0.02,
         qmax=3000.0, rmin=2, kA=0.7, kL=0.15, pL=0.05,
         ammo=1.0, ydem=0.4, W=200.0, fy=0.6, ammo_q=60.0, ammo_pmax=0.05, ammo_maxpay=0.02,
         fb=0.9, fu=0.7, xu=0.1, sticky=1.0, min_ahead=2.0, keep_hi=1.5, keep_lo=0.7, Hu=300.0, bins=8.0, filt=1.0, uni=0.01, jumpinfo=1.0, dmin=0.0, kLb=0.08, kLf=0.08, pinf=1.0, pre=0.0, H1=100.0,
         ydf=0.6, Wf=2000.0, g_hi=0.15, g_lo=0.15, qf=400.0, pmaxf=0.05, pre_gap=1.0,
         ydf1=0.6, g1=5.0, f1=0.6, a1=100.0, nb1=0.0, gs=1.0, p1t=1.0, m1=1.0, zd=1.0, pfl=0.0005)
SQ2 = math.sqrt(2.0)
SQ2PI = math.sqrt(2.0 * math.pi)
def cdf(x): return 0.5 * (1.0 + math.erf(x / SQ2))
def pdf(x): return math.exp(-0.5 * x * x) / SQ2PI
def inv(p):
    p = min(max(p, 1e-9), 1 - 1e-9)
    t = math.sqrt(-2.0 * math.log(min(p, 1 - p)))
    x = t - (2.515517 + 0.802853 * t + 0.010328 * t * t) / (1 + 1.432788 * t + 0.189269 * t * t + 0.001308 * t ** 3)
    x = -x if p < 0.5 else x
    for _ in range(2):
        d = pdf(x)
        if d < 1e-12:
            break
        x -= (cdf(x) - p) / d
    return x
def lpm(k):
    return pdf(k) + k * cdf(k)
def fl(q):
    return math.floor(q * 100 + 1e-9) / 100

NODES = [(-2.2, .06), (-1.3, .17), (-0.6, .27), (0.6, .27), (1.3, .17), (2.2, .06)]
PROBE = 0.01
ON = dict(cancel=(2, 3, 4), cut=(1, 4), postjump=(1,), premium=(), deadband=(3,))

F_AH = 1
F_FL = 1
F_QB = 1

# s1-flow: conditional likelihood of partial fills and zeros. Fully exhausted quotes
# can be either retail or arbitrage; neither is treated as a zero or a
# complete retail order. Truncation normalization corrects the selection.
FLOW_CAPS = (0.03125, 0.0625, 0.125, 0.25, 0.5, 1., 2., 4., 8., 16., 32., 64., 128., 256.)
FLOW_GRID = []
FLOW_PRIORS=[]
for _rn,_rw in ((-math.sqrt(0.6),5/18),(0.,4/9),(math.sqrt(0.6),5/18)):
    _r=0.1265+0.0495*_rn
    for _mn,_mw in ((-0.906179845938664,0.118463442528095),(-0.538469310105683,0.239314335249683),(0.,0.284444444444444),(0.538469310105683,0.239314335249683),(0.906179845938664,0.118463442528095)):
        _m=4.488+1.848*_mn
        _parts=[]
        for _n in (1,2,3):
            _v=math.log(1+(math.exp(1.44)-1)/_n)
            _sg=math.sqrt(_v)
            _mu=math.log(_n*_m)-_v/2
            _w=_r**_n/math.factorial(_n)
            _parts.append((_mu,_sg,_w))
        _norm=[]
        for _c in FLOW_CAPS:
            _prob=sum(w*(cdf((math.log(_c)-mu)/sg)-cdf((math.log(0.03)-mu)/sg)) for mu,sg,w in _parts)
            _norm.append(math.log1p(_prob))
        _tails=[]
        for _c in FLOW_CAPS:
            _cdf=1+sum(w*cdf((math.log(_c)-mu)/sg) for mu,sg,w in _parts)
            _tails.append(math.log(max(1e-100,1-math.exp(-_r)*_cdf)))
        FLOW_GRID.append((_r,_m,_parts,_norm,_tails))
        FLOW_PRIORS.append(math.log(_rw*_mw))


class Strategy(BaseStrategy):
    def __init__(self):
        self.n = 0
        self.ahead = set()     # main orders placed strictly ahead of any competitor order at their tick
        self.res = {}          # order id -> uncovered quantity at placement
        self.bc = None         # belief: sub-tick grid centres (ticks)
        self.bw = None         # belief: weights
        self.st = 0.5          # last one-step sd in ticks
        self.pcb = self.pca = None
        self.pb = set()
        self.pa = set()
        self.tb = 0
        self.s = None          # competitor spread parameter
        self.flow_notional = 0.0
        self.flow_exposure = 0
        self.last_ask_tick = None
        self.last_quote_exposed = False
        self.last_flow_ca = None
        self.last_flow_cap = 0.0
        self.last_flow_correction = 1.0
        self.params = P.copy()
        self.s2_mb = set()
        self.s2_ma = set()
        self.s2_lb = self.s2_la = -99
        self.fl_obs = ()
        self.fl_scores = FLOW_PRIORS.copy()
        self.fl_bins = [0]*len(FLOW_CAPS)
        self.fl_rate = 0.568734
        self.fl_r = 0.1265
        self.fl_m = 4.488
        self.fl_buy_sum = self.fl_sell_sum = 0.0
        self.fl_buy_exp = self.fl_sell_exp = 0.0
        self.fl_exp = 0
        self.fl_dirty=False
        self.fl_ahead=set()
        self.fl_safe_n=0
        self.fl_sbins=[0]*len(FLOW_CAPS)

    def _oid(self, tag):
        self.n += 1
        return tag + str(self.n)

    def on_step(self, state):
        H = max(1, state.steps_remaining)
        cb = state.competitor_best_bid_ticks or 0
        ca = state.competitor_best_ask_ticks or 100
        if self.s is None:
            self.s = max(1, (ca - cb + 1) // 2)
            if self.s == 4:
                # Use the existing low-price risk penalty on bids too; inventory
                # cover orders already provide the separate stocking mechanism.
                self.params['kLb'] = self.params['kLf'] = self.params['kL']
                # Censored compound-Poisson flow likelihood, using only our fills.
                self.f4_exposure = [0, 0]
                self.f4_events = [0, 0]
                self.f4_weights = [[0.0] * 9, [0.0] * 9]
                self.f4_means = [2.64 + i * (6.336 - 2.64) / 8 for i in range(9)]
                # Positive aggregate flow is approximately lognormal; +0.065
                # accounts for the occasional second arrival in a timestep.
                self.f4_mu = [math.log(m) - 0.72 + 0.065 for m in self.f4_means]
                self.f4_last = [None, None]
                self.f4_rate = 0.1265
                self.f4_mean = 4.488
                self.f4_flow = self.f4_rate * self.f4_mean
                self.f4_extreme = inv(1 - 1e-6)
            if self.s == 2:
                self.params.update(dict(flow_prior=200, flow_level=0.6, flow_strength=1.0, flow_safety=2.0, flow_exposure_min=5.0))
                self.params.update({'kLf': 0.16})
            if self.s == 1:
                self.params.update({'dmin': 0.3, 'pfl': 1e-06})
                if 1 in ON['postjump']:
                    self.params['qb_z'] = 4.0
            if self.s == 3:
                self.params.update({'flow_prior': 200, 'flow_level': 0.6, 'flow_strength': 1.0, 'flow_safety': 2.0, 'flow_exposure_min': 5.0})
        P = self.params
        s1 = self.s == 1
        AH = s1 and F_AH
        FL = s1 and F_FL
        QB = s1 and F_QB
        if self.s == 4:
            for side, filled, bound in ((0, state.sell_filled_quantity, ca), (1, state.buy_filled_quantity, cb)):
                last = self.f4_last[side]
                if last is None:
                    continue
                tick, conv, cap, old_bound, ids = last
                if (side == 0 and bound > old_bound + 1) or (side == 1 and bound < old_bound - 1):
                    continue
                # Track only the main quote, excluding probes and stock orders.
                remaining = sum(o.remaining_quantity for o in state.own_orders if o.order_id in ids)
                value = max(0.0, cap - remaining * conv)
                self.f4_exposure[side] += 1
                if value > 0.01:
                    self.f4_events[side] += 1
                    censored = remaining < 0.011
                    logv = math.log(max(value, 0.01))
                    weights = self.f4_weights[side]
                    for i, mu4 in enumerate(self.f4_mu):
                        z4 = (logv - mu4) / 1.2
                        weights[i] += math.log(max(1e-12, 1.0 - cdf(z4))) if censored else -0.5 * z4 * z4
            if state.step % 25 == 0:
                exposure = sum(self.f4_exposure)
                events = sum(self.f4_events)
                event_probability = (events + 80.0 * (1.0 - math.exp(-0.1265))) / (exposure + 80.0)
                self.f4_rate = max(0.077, min(0.176, -math.log(max(1e-6, 1.0 - event_probability))))
                weights = [a + b for a, b in zip(*self.f4_weights)]
                peak = max(weights)
                weights = [math.exp(w - peak) for w in weights]
                self.f4_mean = sum(m * w for m, w in zip(self.f4_means, weights)) / sum(weights)
                self.f4_flow = self.f4_rate * self.f4_mean
        if self.s in (2, 3) and self.last_quote_exposed and ca <= self.last_flow_ca + 1:
            self.flow_exposure += 1
            self.flow_notional += min(self.last_flow_cap, state.sell_filled_quantity * self.last_ask_tick / 100.0) * self.last_flow_correction
        lo, hi = cb, ca
        for o in state.own_orders:
            if o.side is Side.BUY:
                lo = max(lo, o.price_ticks)
            else:
                hi = min(hi, o.price_ticks)
        if P['pinf'] > 0:
            sb = {o.price_ticks for o in state.own_orders if o.side is Side.BUY and o.remaining_quantity <= PROBE + 1e-9}
            sa = {o.price_ticks for o in state.own_orders if o.side is Side.SELL and o.remaining_quantity <= PROBE + 1e-9}
            ea = self.pa - sa
            eb = self.pb - sb
            if sa and ea:
                lo = max(lo, min(max(ea), hi))
            if eb and (sb or min(eb) <= P['p1t']):
                hi = min(hi, max(min(eb), lo))
        retreat_ask = retreat_bid = False
        if P['jumpinfo'] > 0 and self.pcb is not None:
            if self.s in ON['cut']:
                retreat_ask = ca == self.pca + 1
                retreat_bid = cb == self.pcb - 1
            if ca > self.pca + 1:
                lo = max(lo, ca - 1)
            if cb < self.pcb - 1:
                hi = min(hi, cb + 1)
        hitB = hitA = shB = shA = False
        if self.s == 2:
            ids = {o.order_id for o in state.own_orders}
            hitB = bool(self.s2_mb) and not (self.s2_mb & ids)
            hitA = bool(self.s2_ma) and not (self.s2_ma & ids)
            if hitB:
                self.s2_lb = state.step
            if hitA:
                self.s2_la = state.step
            hitB = state.step - self.s2_lb < 1
            hitA = state.step - self.s2_la < 1
            if self.pcb is not None:
                shB = cb < self.pcb - 1
                shA = ca > self.pca + 1
        self.pcb, self.pca = cb, ca
        if lo > hi:
            lo, hi = hi, lo
        # sub-tick belief over p_(t-1): predict with one-step noise, truncate to [lo, hi]
        wid = max(hi - lo, 1e-6)
        nb = max(2, min(48, int(round(wid * P['bins']))))
        cs = [lo + (i + 0.5) * wid / nb for i in range(nb)]
        if self.bc is None or P['filt'] <= 0:
            ws = [1.0 / nb] * nb
        else:
            sg = max(self.st, 0.6 * wid / nb)
            k = -0.5 / (sg * sg)
            ws = []
            uni = P['uni'] * sg
            if self.s == 4:
                exp = math.exp
                if self.bc == cs and 1.0 <= wid <= 6.0 and nb == 8 * wid:
                    # On this stationary grid, spacing is exactly 1/8 tick.
                    # Equal index distances therefore have bit-identical d*d*k.
                    # Reuse exp values while retaining the original sum order.
                    kernel = []
                    c0 = cs[0]
                    for ci in self.bc:
                        d = c0 - ci
                        d2 = d * d * k
                        kernel.append(exp(d2) if d2 > -12.5 else 0.0)
                    kernel = kernel[:0:-1] + kernel
                    for i in range(nb):
                        t = uni
                        start = nb - 1 - i
                        for wi, e in zip(self.bw, kernel[start:start + nb]):
                            if e:
                                t += wi * e
                        ws.append(t)
                else:
                    previous = tuple(zip(self.bc, self.bw))
                    for c in cs:
                        t = uni
                        for ci, wi in previous:
                            d = c - ci
                            d2 = d * d * k
                            if d2 > -12.5:
                                t += wi * exp(d2)
                        ws.append(t)
            else:
                for c in cs:
                    t = uni
                    for ci, wi in zip(self.bc, self.bw):
                        d = c - ci
                        d2 = d * d * k
                        if d2 > -12.5:
                            t += wi * math.exp(d2)
                    ws.append(t)
            tot = sum(ws)
            ws = [w / tot for w in ws]
        if retreat_ask or retreat_bid:
            ws = [weight * (0.016 if retreat_ask and c < ca - 1 else 1.0)
                  * (0.016 if retreat_bid and c > cb + 1 else 1.0)
                  for c, weight in zip(cs, ws)]
            tot = sum(ws)
            ws = [weight / tot for weight in ws]
        self.bc, self.bw = cs, ws
        mean_t = sum(c * w for c, w in zip(cs, ws))
        var_t = max(sum(c * c * w for c, w in zip(cs, ws)) - mean_t * mean_t, 0.0)
        phat = min(max(mean_t / 100.0, 0.002), 0.998)
        var = P['sig'] ** 2 + P['lam_j'] * P['sig_j'] ** 2
        sd = math.sqrt(H * var)
        self.tb = self.tb + 1 if hi <= 1 else 0
        if self.tb > 0 and P['zd'] > 0:
            # below the last tick there is no probe: the score keeps walking away from it
            phat = min(phat, max(P['pfl'], cdf(inv(0.01) - P['zd'] * 0.02 * math.sqrt(self.tb) / sd)))
        z = inv(phat)
        Z = z * sd
        sp = pdf(z) / sd * P['sig']
        self.st = sp * 100.0
        if FL:
            remaining={o.order_id:o.remaining_quantity for o in state.own_orders} if self.fl_obs else {}
            for px, ci, buying, previous, tick in self.fl_obs:
                qty=max(0.0,sum(q-remaining.get(oid,0.0) for oid,q in previous))
                x=qty*px
                cap=FLOW_CAPS[ci]
                gap=tick/100.0-phat if buying else phat-tick/100.0
                safe=gap>max(0.005,2.0*math.sqrt(var_t)/100.0)
                if 0<x<0.03:
                    continue
                if x>=cap:
                    if safe:
                        self.fl_sbins[ci]+=1
                        self.fl_exp+=1
                        self.fl_dirty=True
                    continue
                if safe:
                    self.fl_safe_n+=1
                else:
                    self.fl_bins[ci]+=1
                self.fl_exp+=1
                self.fl_dirty=True
                if buying:
                    self.fl_buy_exp+=1
                else:
                    self.fl_sell_exp+=1
                if x>0:
                    lx=math.log(x)
                    for i,(r,m,parts,norm,tails) in enumerate(FLOW_GRID):
                        density=sum(w*pdf((lx-mu)/sg)/sg for mu,sg,w in parts)
                        self.fl_scores[i]+=math.log(max(density,1e-100))
            if state.step % 100 == 0 and (self.fl_dirty or state.step==0):
                bins=[(i,n) for i,n in enumerate(self.fl_bins) if n]
                sbins=[(i,n) for i,n in enumerate(self.fl_sbins) if n]
                logs=[score-sum(n*g[3][i] for i,n in bins)-g[0]*self.fl_safe_n+sum(n*g[4][i] for i,n in sbins) for score,g in zip(self.fl_scores,FLOW_GRID)]
                mx=max(logs)
                weights=[math.exp(v-mx) for v in logs]
                den=sum(weights)
                self.fl_dirty=False
                self.fl_rate=sum(w*g[0]*g[1] for w,g in zip(weights,FLOW_GRID))/den
                self.fl_r=sum(w*g[0] for w,g in zip(weights,FLOW_GRID))/den
                self.fl_m=sum(w*g[1] for w,g in zip(weights,FLOW_GRID))/den

        s = math.sqrt(sp * sp + var_t / 1e4 + 1e-8)
        sd1 = math.sqrt(max(1.0, H - 1.0) * var)
        jp = [(cdf((Z + n * P['sig_j']) / sd1), w) for n, w in NODES]
        lj = P['lam_j']

        def AB(x):
            k = (x - phat) / s
            a = s * lpm(k)
            b = a - (x - phat)
            if self.s == 4:
                ja = jb = 0.0
                for p, w in jp:
                    if x > p:
                        ja += w * (x - p)
                    else:
                        jb += w * (p - x)
            else:
                ja = sum(w * max(0.0, x - p) for p, w in jp)
                jb = sum(w * max(0.0, p - x) for p, w in jp)
            return (1 - lj) * a + lj * ja, (1 - lj) * b + lj * jb

        if H == 1:
            def AB(x):
                return (1 - phat) * x, phat * (1 - x)
        rho = P['lam_r'] * 0.5
        mu = math.log(P['m']) - 0.5 * P['sig_n'] ** 2
        kA = P['kL'] if phat < P['pL'] else P['kA']

        def qsize(loss, gain, px, flow=False, cap=None):
            loss *= kA
            if gain <= 0:
                return 0.0
            rr = (0.125+0.5*(self.fl_r-0.125)) if flow and FL else rho
            mm = math.log(5.0+0.5*(self.fl_m-5.0))-0.5*P['sig_n']**2 if flow and FL else mu
            tail = loss / (rr * gain)
            if tail >= 1.0:
                return 0.0
            if self.s == 4 and tail <= 1e-6:
                return min(P['qmax'], math.exp(mu + P['sig_n'] * self.f4_extreme) / px)
            return min((cap if cap is not None else P['qmax']), math.exp(mm + P['sig_n'] * inv(1 - max(tail, 1e-6))) / px)

        ptk = phat * 100
        def qbid(t):
            if not 1 <= t <= 99:
                return 0.0
            if self.s == 4 and phat * 100 - t < P['dmin']:
                return 0.0
            a, b = AB(t / 100.0)
            if phat * 100 - t < P['dmin']:
                return 0.0
            if P['nb1'] > 0 and self.s == 1 and t == 1 and ptk < 1.0:
                return 0.0
            if phat < P['pL']:
                ytg = P['ydem'] * min(H, P['W']) / max(ca - 1, ptk + 1) * 100.0
                a *= (P['kLb'] if state.yes_inventory < ytg else P['kLf']) / P['kL']
                if self.s == 3:
                    # Subsidize cover only while more stock is needed for remaining retail.
                    # Once the whole horizon is covered, use the ordinary bid risk weight.
                    flow = (self.flow_notional + P['flow_prior'] * P['flow_level']) / (P['flow_prior'] + self.flow_exposure)
                    if state.yes_inventory >= flow * H / max(ca - 1, ptk + 1) * 100.0:
                        a *= P['kA'] / P['kLf']
            return qsize(a, b, max(phat, 0.05))

        def qask(t):
            if not 1 <= t <= 99:
                return 0.0
            if self.s == 4 and t - phat * 100 < P['dmin']:
                return 0.0
            a, b = AB(t / 100.0)
            if t - phat * 100 < P['dmin']:
                return 0.0
            if self.s == 4:
                if 4 not in ON['premium'] and P['pL'] <= phat <= 0.95:
                    b *= 1.4
                tail = b * kA / max(self.f4_rate * a, 1e-30)
                if a <= 0 or tail >= 1.0:
                    return 0.0
                return min(P['qmax'], math.exp(math.log(self.f4_mean) - 0.72 + 1.2 * (self.f4_extreme if tail <= 1e-6 else inv(1 - tail))) / (t / 100.0))
            return qsize(b, a, t / 100.0, flow=True, cap=(15000 if AH and t == 2 and phat < 0.01 else None))

        bids = [o for o in state.own_orders if o.side is Side.BUY and o.remaining_quantity > PROBE + 1e-9]
        asks = [o for o in state.own_orders if o.side is Side.SELL and o.remaining_quantity > PROBE + 1e-9]
        sticky = P['sticky'] > 0
        def top(orders, comp, step):
            threshold = P['min_ahead']
            if self.s == 3 and step == -1 and 1 <= comp <= 5:
                threshold = max(P['min_ahead'], 20 * 100.0 / comp)
            elif QB and step == 1:
                threshold = PROBE + 0.01
            elif self.s == 2:
                # spread 2: a front order that one ordinary retail buy would use up is not worth holding the quote at the rival's tick
                threshold = max(P['min_ahead'], 400.0 / max(comp, 1))
            elif self.s == 4 and step < 0 and phat < 0.05:
                threshold = 50.0
            if sticky and sum(o.remaining_quantity for o in orders if o.price_ticks == comp and o.order_id in self.ahead) >= threshold:
                return comp
            return comp + step
        bid_t = top(bids, cb, 1)
        ask_t = top(asks, ca, -1)
        qb = qbid(bid_t)
        qa = qask(ask_t)
        s2f = self.s == 2 and bid_t == cb and qb > 0 and cb / 100.0 < phat
        if self.s == 4 and phat < 0.05 and bid_t >= 2:
            qb *= 0.5
        if self.s == 1 and ask_t == 2 and ask_t < ca and phat < 0.01:
            qa *= 5

        Y = state.yes_inventory
        if ask_t == 1 and H > P['H1'] and P['pre'] > 0:
            qa = qa if Y >= P['a1'] > 0 else 0.0          # let the competitor's 2-tick ask erode instead of fronting it for nothing
        # ammunition: hold YES so that low asks are covered
        ptick = phat * 100
        amt = 0
        qam = 0.0
        fs1 = max(0.4,min(1.9,1.0+0.5*(self.fl_rate/0.568734-1))) if FL else 1.0
        if P['ammo'] > 0 and ask_t >= 2 and phat < max(P['ammo_pmax'], P['pmaxf']):
            wealth = state.cash + Y * phat
            x = max(ask_t, ptick + 1) / 100.0
            capw = P['fy'] * wealth / max(phat, 0.005)
            flow_scale = self.f4_flow / 0.6 if self.s == 4 else fs1
            target = min(flow_scale * P['ydem'] * min(H, P['W']) / x, capw)
            if self.s == 3:
                # Buy routine cover only for the current front ask's desired size.
                target = min(target, qa)
            if self.s == 4:
                # Pay above fair value only for the current retail quote's cover.
                target = min(target, qa)
            full = min(flow_scale * P['ydf'] * min(H, P['Wf']) / x, capw) if phat < P['pmaxf'] else 0.0
            t = max(1, min(99, int(math.ceil(ptick + 1e-9))))
            g = t - ptick
            if self.s != 3 and Y < full and g <= P['g_hi'] and bid_t <= t < ask_t:
                amt, qam = t, min(P['qf'], full - Y)     # a tick p has just crossed: nearly free
            elif (self.s != 2 or t == 1) and Y < target and phat < P['ammo_pmax'] and bid_t <= t < ask_t and t / 100.0 - phat < P['ammo_maxpay']:
                if self.s == 1:
                    passive_t = t - 1
                    if passive_t >= max(1, bid_t):
                        amt, qam = passive_t, min(P['ammo_q'], target - Y)
                else:
                    amt, qam = t, min(P['ammo_q'], target - Y)
            elif Y < full and t >= 2 and 1.0 - g <= P['g_lo']:
                amt, qam = t - 1, min(P['qf'], full - Y)  # rest just under p: filled only on the crossing, or by retail

        if P['pre'] > 0 and ca == 2 and phat < 0.01 and H > P['H1'] and Y < P['pre'] and not qam and 1.0 - ptick < P['pre_gap']:
            amt, qam = 1, min(P['ammo_q'], P['pre'] - Y)
        q1 = 0.0
        if P['ydf1'] > 0 and P['m1'] < ptick < P['g1'] + 1.0 and amt != 1:
            stock_rate = fs1 * P['ydf1']
            if self.s == 4:
                stock_rate *= self.f4_flow / 0.6
            if self.s in (2, 3):
                flow = (self.flow_notional + P['flow_prior'] * P['flow_level']) / (P['flow_prior'] + self.flow_exposure)
                scale = max(0.5, min(2.0, flow / P['flow_level']))
                stock_rate *= 1.0 + P['flow_strength'] * (scale - 1.0)
            q1 = max(0.0, stock_rate * min(H, P['Wf']) / (self.s / 100.0) - Y)

        # Bridge expected retail demand until another tick crossing is available.
        if 0.02 < phat < 0.1:
            ct = max(2, min(99, int(math.floor(ptick))))
            wealth = state.cash + Y * phat
            goal = min(fs1 * qa, 0.3 * max(wealth, 0.0) / phat)
            if Y < goal and ct < ask_t:
                amt, qam = ct, min(3000.0, goal - Y)
        if self.s == 2:
            if hitB:
                qb = 0.0
                qam = 0.0
                q1 = 0.0
            if hitA:
                qa = 0.0
        # order management
        actions = []
        free = state.free_cash - 2.0
        keep_ask = 0.0
        new_b = []
        new_a = []
        def cancel(o):
            nonlocal free
            actions.append(CancelOrder(o.order_id))
            x = o.price_ticks / 100.0
            if o.side is Side.BUY:
                free += x * o.remaining_quantity
            else:
                free += (1 - x) * min(self.res.get(o.order_id, 0.0), o.remaining_quantity)
            self.ahead.discard(o.order_id)
            self.res.pop(o.order_id, None)
        for o in state.own_orders:
            if o.remaining_quantity <= PROBE + 1e-9:
                cancel(o)
        kept_ids = set()
        def manage(orders, t, q, comp):
            kept = 0.0
            if self.s == 2:
                buy = comp == cb
                held = {}
                for o in orders:
                    x = o.price_ticks
                    gain = ptk - x if buy else x - ptk
                    # under 10 cents a front order is kept whole for its life: resizing it would give up its place to the rival
                    if x == t and q > 0 and (kept + o.remaining_quantity <= max(q * P['keep_hi'], 1.0) or (x == comp and o.order_id in self.ahead and ptk <= 10.0 and gain >= 0.0)):
                        kept += o.remaining_quantity
                        kept_ids.add(o.order_id)
                        continue
                    # a small front remainder stays behind the new inside quote: it still fills ahead of the rival on a large retail order
                    if x == comp and x != t and o.order_id in self.ahead and gain >= 1.0:
                        if x not in held:
                            held[x] = [0.0, qbid(x) if buy else qask(x)]
                        h = held[x]
                        if h[0] + o.remaining_quantity <= max(h[1], 1.0) and h[1] > 0:
                            h[0] += o.remaining_quantity
                            kept_ids.add(o.order_id)
                            continue
                    cancel(o)
                return kept
            banked = {}
            bound_t, bound_q = t, q
            for o in orders:
                ah = o.order_id in self.ahead
                if AH and ah and o.remaining_quantity >= P['min_ahead'] and o.price_ticks != t:
                    if (o.side is Side.SELL and o.price_ticks > t) or (o.side is Side.BUY and o.price_ticks < t):
                        enough = bound_q > 0 and (
                            o.remaining_quantity <= bound_q if o.side is Side.BUY else
                            o.remaining_quantity * o.price_ticks <= min(bound_q, P['qmax']) * bound_t)
                        if enough:
                            kept_ids.add(o.order_id)
                            continue
                        if o.price_ticks == bound_t:
                            capacity = bound_q
                        else:
                            capacity = qask(o.price_ticks) if o.side is Side.SELL else qbid(o.price_ticks)
                            bound_t, bound_q = o.price_ticks, capacity
                        if capacity > 0 and o.remaining_quantity <= max(capacity, 1.0):
                            kept_ids.add(o.order_id)
                            continue
                if QB and ah and o.side is Side.BUY and o.price_ticks < t and ('qb_z' not in P or ptk - o.price_ticks >= P['qb_z'] * 100.0 * s) and banked.get(o.price_ticks, 0.0) + o.remaining_quantity <= P['keep_hi'] * qbid(o.price_ticks):
                    banked[o.price_ticks] = banked.get(o.price_ticks, 0.0) + o.remaining_quantity
                    kept_ids.add(o.order_id)
                    continue
                khi = 10.0 if (AH and ah) else (3.0 if (self.s == 4 and o.side is Side.SELL and ah and o.price_ticks == comp) else P['keep_hi'])
                if o.price_ticks == t and q > 0 and (kept + o.remaining_quantity <= max(q * khi, 1.0)
                        or (s1 and ah and (o.side is Side.SELL) and o.price_ticks <= 2)
                                        or (QB and ah and o.side is Side.BUY and o.price_ticks == comp)):
                    kept += o.remaining_quantity
                    kept_ids.add(o.order_id)
                else:
                    cancel(o)
            return kept
        if s2f and 1:
            kb = 0.0
            for o in bids:
                if o.price_ticks == bid_t and o.order_id in self.ahead:
                    kb += o.remaining_quantity
                    kept_ids.add(o.order_id)
                else:
                    cancel(o)
        elif self.s == 2 and 1 and bid_t == cb + 1:
            qf = qbid(cb) if 1 else 1.0
            fr = [o for o in bids if o.price_ticks == cb and o.order_id in self.ahead and cb / 100.0 < phat - 0.0 and qf > 0]
            for o in fr:
                kept_ids.add(o.order_id)
            kb = manage([o for o in bids if o not in fr], bid_t, qb, cb)
        else:
            kb = manage(bids, bid_t, qb, cb)
        ka = manage(asks, ask_t, qa, ca)
        dbk = 1.0 if self.s in ON['deadband'] else P['keep_lo']
        add_b = (qb - kb) if (kb < qb * dbk and bid_t != cb) else 0.0
        add_a = (qa - ka) if (ka < qa * dbk and ask_t != ca) else 0.0

        budget = P['fb'] * max(free, 0.0)
        cost = add_b * bid_t / 100.0 + qam * amt / 100.0
        if cost > budget:
            f = budget / cost
            add_b *= f
            qam *= f
            cost = budget
        out = []
        q1 = min(q1, P['f1'] * max(budget - cost, 0.0) * 100.0)
        if q1 >= 0.01:
            out.append(PlaceOrder(side=Side.BUY, price_ticks=1, quantity=fl(q1)))
            free -= fl(q1) / 100.0 + 1e-6
        if amt and qam >= 0.01:
            q = fl(qam)
            if QB:
                oid = self._oid('m')
                out.append(PlaceOrder(side=Side.BUY, price_ticks=amt, quantity=q, client_order_id=oid))
                if amt > cb:
                    self.ahead.add(oid)
            else:
                out.append(PlaceOrder(side=Side.BUY, price_ticks=amt, quantity=q))
            free -= q * amt / 100.0 + 1e-6
        if bid_t >= 1 and add_b >= 0.01:
            q = fl(add_b)
            total_q = q
            if self.s == 4 and ca <= 99 and bid_t > cb and bid_t == ca - 4 and q >= 4.0 and q * bid_t / 100 >= 4 * P['m']:
                head = fl(q / 2)
                oid = self._oid('b')
                out.append(PlaceOrder(side=Side.BUY, price_ticks=bid_t, quantity=head, client_order_id=oid))
                self.ahead.add(oid)
                q = fl(q - head)
            oid = self._oid('b')
            out.append(PlaceOrder(side=Side.BUY, price_ticks=bid_t, quantity=q, client_order_id=oid))
            free -= total_q * bid_t / 100.0 + 1e-6
            if bid_t > cb:
                self.ahead.add(oid)
        if ask_t <= 99 and add_a >= 0.01:
            x = ask_t / 100.0
            covk = sum(o.remaining_quantity - min(self.res.get(o.order_id, 0.0), o.remaining_quantity)
                       for o in asks if o.order_id in kept_ids)
            cov = max(0.0, Y - covk - 0.1)
            unc = max(0.0, add_a - cov)
            if unc > 0:
                ub = max(0.0, free - (1 - P['fu']) * max(state.cash, 0.0)) if x >= P['xu'] else 0.0
                if H < P['Hu'] and phat < 0.05:
                    ub = max(0.0, free * (1 - H / P['Hu']))
                unc = min(unc, ub / (1 - x))
            q = fl(min(add_a, cov + unc))
            if q >= 0.01:
                oid = self._oid('a')
                out.append(PlaceOrder(side=Side.SELL, price_ticks=ask_t, quantity=q, client_order_id=oid))
                r = max(0.0, q - cov)
                self.res[oid] = r
                free -= r * (1 - x) + 1e-6
                if ask_t < ca:
                    self.ahead.add(oid)

        # probes: tiny orders that the arbitrageur removes when p crosses them
        f = int(math.floor(ptick + 1e-9))
        r = max(int(P['rmin']), int(math.ceil(2.0 * s * 100)))
        self.pb = set()
        self.pa = set()
        if free > 1.0:
            for t in range(f, f + r + 1):
                if cb < t < ca and 1 <= t <= 99:
                    out.append(PlaceOrder(side=Side.BUY, price_ticks=t, quantity=PROBE))
                    self.pb.add(t)
            for t in range(f + 1 - r, f + 2):
                if cb < t < ca and 1 <= t <= 99:
                    out.append(PlaceOrder(side=Side.SELL, price_ticks=t, quantity=PROBE))
                    self.pa.add(t)
        if self.s in (2, 3):
            self.last_ask_tick = ask_t
            self.last_flow_ca = ca
            exposed_qty = ka + sum(o.quantity for o in out if o.side is Side.SELL and o.price_ticks == ask_t and o.quantity > PROBE)
            self.last_flow_cap = exposed_qty * ask_t / 100.0
            self.last_quote_exposed = ask_t / 100.0 > phat + max(0.005, P['flow_safety'] * self.st / 100.0) and self.last_flow_cap >= P['flow_exposure_min']
            if self.last_quote_exposed:
                logcap = math.log(self.last_flow_cap)
                mu_flow = math.log(P['m']) - 0.5 * P['sig_n'] ** 2
                clipped = P['m'] * cdf((logcap - mu_flow - P['sig_n'] ** 2) / P['sig_n']) + self.last_flow_cap * (1.0 - cdf((logcap - mu_flow) / P['sig_n']))
                self.last_flow_correction = min(3.0, P['m'] / max(clipped, 0.01))
        if self.s == 1:
            split_out = []
            for order in out:
                oid = order.client_order_id
                if (order.side is Side.SELL and oid is not None and oid.startswith('a')
                        and order.price_ticks >= 3 and order.price_ticks < 99):
                    back = fl(order.quantity * 0.5)
                    front = fl(order.quantity - back)
                    reserve = self.res.pop(oid, 0.0)
                    front_reserve = max(0.0, reserve - back)
                    if front >= 0.01:
                        split_out.append(PlaceOrder(side=Side.SELL, price_ticks=order.price_ticks, quantity=front, client_order_id=oid))
                        self.res[oid] = front_reserve
                    if back >= 0.01:
                        back_id = self._oid('a')
                        split_out.append(PlaceOrder(side=Side.SELL, price_ticks=order.price_ticks + 1, quantity=back, client_order_id=back_id))
                        self.res[back_id] = max(0.0, reserve-front_reserve)
                else:
                    split_out.append(order)
            out = split_out
        if FL:
            if not kept_ids and not any(o.quantity>PROBE for o in out):
                self.fl_obs=()
                self.fl_ahead.clear()
                return actions+out
            # Give stock orders explicit ids so per-order remaining quantities
            # separate their fills from other bid levels and tiny probes.
            for i,o in enumerate(out):
                if o.client_order_id is None and o.quantity>PROBE:
                    out[i]=PlaceOrder(side=o.side,price_ticks=o.price_ticks,quantity=o.quantity,client_order_id=self._oid('f'))
            live=[]
            oldids={o.order_id for o in state.own_orders if o.order_id in kept_ids}
            self.fl_ahead.intersection_update(oldids)
            for o in state.own_orders:
                if o.order_id in kept_ids and o.remaining_quantity>PROBE:
                    live.append((o.side,o.price_ticks,o.remaining_quantity,o.order_id))
            for o in out:
                if o.quantity>PROBE:
                    live.append((o.side,o.price_ticks,o.quantity,o.client_order_id))
                    if (o.side is Side.SELL and o.price_ticks<ca) or (o.side is Side.BUY and o.price_ticks>cb):
                        self.fl_ahead.add(o.client_order_id)
            obs=[]
            for buying,side,comp in ((True,Side.SELL,ca),(False,Side.BUY,cb)):
                orders=[o for o in live if o[0] is side]
                if not orders:
                    continue
                tick=min(o[1] for o in orders) if buying else max(o[1] for o in orders)
                orders=[o for o in orders if o[1]==tick]
                if not all(o[3] in self.fl_ahead for o in orders):
                    continue
                if (buying and tick>comp) or (not buying and tick<comp):
                    continue
                px=tick/100.0 if buying else max(phat,0.05)
                cap=sum(o[2] for o in orders)*px
                if cap<0.04:
                    continue
                ci=0
                while ci+1<len(FLOW_CAPS) and FLOW_CAPS[ci+1]<cap-0.01:
                    ci+=1
                obs.append((px,ci,buying,[(o[3],o[2]) for o in orders],tick))
            self.fl_obs=obs
        if self.s == 4:
            self.f4_last = [None, None]
            # Eligibility is decided before observing fills, so depleted quotes
            # remain in the sample as right-censored observations.
            for side, tick, bound, conv, distance in (
                (0, ask_t, ca, ask_t / 100.0, ask_t / 100.0 - phat),
                (1, bid_t, cb, max(phat, 0.05), phat - bid_t / 100.0)):
                if distance < max(0.01, 3.0 * self.st / 100.0):
                    continue
                if side == 0:
                    if not (ask_t < ca or any(o.price_ticks == ask_t and o.order_id in self.ahead for o in asks)):
                        continue
                    orders = asks
                    order_side = Side.SELL
                else:
                    if not (bid_t > cb or any(o.price_ticks == bid_t and o.order_id in self.ahead for o in bids)):
                        continue
                    if (qam > 0 and amt >= bid_t) or (q1 > 0 and bid_t <= 1):
                        continue
                    orders = bids
                    order_side = Side.BUY
                tracked = {o.order_id: o.remaining_quantity for o in orders if o.order_id in kept_ids and o.price_ticks == tick}
                tracked.update({o.client_order_id: o.quantity for o in out if o.side is order_side and o.price_ticks == tick and o.client_order_id is not None})
                cap = sum(tracked.values()) * conv
                if cap >= 0.5:
                    self.f4_last[side] = (tick, conv, cap, bound, tracked)
        if self.s == 2:
            self.s2_mb = {o.order_id for o in bids if o.order_id in kept_ids} | {o.client_order_id for o in out if o.side is Side.BUY and o.client_order_id}
            self.s2_ma = {o.order_id for o in asks if o.order_id in kept_ids} | {o.client_order_id for o in out if o.side is Side.SELL and o.client_order_id}
        return actions + out


_IncumbentStrategy = Strategy

class Strategy(_IncumbentStrategy):
    """cancel: for one callback after the rival's bid falls (ask rises) exactly one tick, cancel that side and place nothing there."""
    def __init__(self):
        super().__init__()
        self._retreat_previous = (None, None)
        self._retreat_left = {Side.BUY: 0, Side.SELL: 0}

    def on_step(self, state):
        bid = state.competitor_best_bid_ticks
        ask = state.competitor_best_ask_ticks
        old_bid, old_ask = self._retreat_previous
        self._retreat_previous = (bid, ask)
        actions = super().on_step(state)
        if self.s not in ON['cancel']:
            return actions
        for side, retreat in (
            (Side.BUY, bid is not None and old_bid is not None and bid == old_bid - 1),
            (Side.SELL, ask is not None and old_ask is not None and ask == old_ask + 1),
        ):
            if retreat:
                self._retreat_left[side] = 1
        blocked = {side for side, left in self._retreat_left.items() if left > 0}
        for side in blocked:
            self._retreat_left[side] -= 1
        if not blocked:
            return actions
        out = []
        for action in actions:
            if isinstance(action, PlaceOrder) and action.side in blocked:
                self.ahead.discard(action.client_order_id)
                self.res.pop(action.client_order_id, None)
            else:
                out.append(action)
        canceled = {a.order_id for a in out if isinstance(a, CancelOrder)}
        out.extend(CancelOrder(o.order_id) for o in state.own_orders
                   if o.side in blocked and o.order_id not in canceled)
        # Forget everything held about the withheld side, so our own cancels are not read as fills or hits.
        if Side.BUY in blocked:
            self.pb.clear()
            self.s2_mb = set()
            self.fl_obs = tuple(x for x in self.fl_obs if x[2])
            if self.s == 4:
                self.f4_last[1] = None
        if Side.SELL in blocked:
            self.pa.clear()
            self.s2_ma = set()
            self.last_quote_exposed = False
            self.fl_obs = tuple(x for x in self.fl_obs if not x[2])
            if self.s == 4:
                self.f4_last[0] = None
        return out


_N = Strategy


class Strategy(BaseStrategy):
    """postjump (spread 1): after a likely jump in the rival's quotes, withhold quotes on the side the jump runs toward for a few callbacks."""
    M = 4
    JUMP = 2.0

    def __init__(self, *a, **k):
        super().__init__(*a, **k)
        self._n = _N(*a, **k)
        self.s = None
        self._s = None
        self._pm = None
        self._dis = 0
        self._lo = 0
        self._hi = 0
        self._dir = 0
        self._pd = 0.05

    def on_step(self, state):
        acts = self._n.on_step(state)
        b, a = state.competitor_best_bid_ticks, state.competitor_best_ask_ticks
        self.s = self._n.s
        self._s = self.s
        if self._s not in ON['postjump'] or b is None or a is None:
            return acts
        mid = (a + b) / 2.0
        pm = self._pm
        self._pm = mid
        if pm is None:
            return acts
        mv = mid - pm
        fb, fs = state.buy_filled_quantity, state.sell_filled_quantity
        ev = abs(mv) / self.JUMP + (0.5 if (fs > 0 and mv > 0) or (fb > 0 and mv < 0) else 0.0)
        p = self._pd
        lr = 2.718281828 ** (3.0 * (ev - 1.0))
        p = p * lr / (p * lr + (1 - p))
        self._pd = min(0.95, max(0.01, 0.9 * p + 0.01))
        if p > 0.5 and abs(mv) >= 1:
            self._dis = self.M
            self._dir = 1 if mv > 0 else -1
            self._lo = min(pm, mid)
            self._hi = max(pm, mid)
        elif self._dis > 0:
            if abs(mv) >= 1 and (mv > 0) == (self._dir > 0):
                self._lo = min(self._lo, mid)
                self._hi = max(self._hi, mid)
                self._dis = self.M
            else:
                self._dis -= 1
        if self._dis <= 0:
            return acts
        out = []
        for x in acts:
            if isinstance(x, PlaceOrder):
                pr = x.price_ticks
                if self._dir > 0 and x.side == Side.SELL and pr <= self._hi + self._s:
                    continue
                if self._dir < 0 and x.side == Side.BUY and pr >= self._lo - self._s:
                    continue
            out.append(x)
        return out

3. Evidence on the finalist seeds 900000..903999

All figures are paired differences per run: the candidate's total_edge minus the comparator's on the same seed, unmodified simulator at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, default ChallengeConfig and ParameterVariance, 2,000 steps, serial engine calls, no --sandbox. Pooling of blocks uses mean = S/n and se = sqrt((Q − S²/n)/(n − 1)/n) from each block's n, sum of d and sum of d².

3.1 T against wave 3's combine-cash (the objective's start), all 4,000 finalist seeds

Run on this machine during the write-up because no handed batch measured T against combine-cash (the goal's comparisons moved with the base, section 3.2). Both files were hashed before the run (9fba1eb5… and baef955e…); combine-cash reproduces N's published check value 17.116002 on seed 310000. Six single-process workers, each on its own contiguous block, one fresh strategy instance per run.

scope	n	T minus combine-cash	se	gain / se	retail	arb	combine-cash mean	T mean
all seeds	4000	+3.502	0.336	10.4	+1.599	+1.903	102.52	106.02
spread 1	991	+6.117	0.827	7.4	+0.913	+5.204	45.50	51.62
spread 2	1017	+3.160	0.678	4.7	+2.242	+0.918	92.18	95.34
spread 3	961	+2.261	0.627	3.6	+3.013	-0.752	124.82	127.08
spread 4	1031	+2.481	0.525	4.7	+0.305	+2.176	146.73	149.21

block	seeds	n	T minus combine-cash	se	retail	arb
1	900000..900499	500	+3.103	0.809	+1.376	+1.727
2	900500..900999	500	+2.477	0.657	+1.310	+1.167
3	901000..901499	500	+5.003	1.313	+3.284	+1.718
4	901500..901999	500	+2.673	0.731	+1.241	+1.432
5	902000..902499	500	+4.813	1.063	+1.895	+2.918
6	902500..902999	500	+2.200	0.780	+0.653	+1.547
7	903000..903499	500	+3.578	0.758	+1.741	+1.837
8	903500..903999	500	+4.164	1.260	+1.288	+2.876

All 4,000 seeds complete, one record per seed, no failures in either file.

T beats combine-cash on 2928 seeds and loses on 1072; the rest are ties. Worst five seeds (seed, spread, d): 902511 (4, -272.2), 900327 (4, -224.2), 901136 (3, -155.8), 902361 (3, -135.7), 903352 (3, -120.8). Best five: 903835 (2, +519.8), 901130 (3, +386.7), 902357 (1, +273.0), 902256 (1, +260.8), 901023 (1, +248.3).

Mean wall seconds a simulation under six-way load: T 2.18, combine-cash 2.04 (serial and idle on this machine: T 0.9, combine-cash 0.8 on the check seeds).

3.2 The chain of bases, each link on the finalist seeds where it was measured

The incumbent changed three times on the requester's notes as sibling goals submitted stronger files. The links measured by this goal on seeds 900000..903999 are complete; the links measured elsewhere are quoted from the requester's notes or the file's own artifact.

link	seeds	n	gain	se	retail	arb	per spread (gain / se)	source
combine-cash → N (adopted 11-06)	not on F						N's artifact: +1.45 se 0.16 over the 108.47 file on 130000..133999 (s1 +1.64, s2 +1.73, s3 +0.49, s4 +1.87)	requester note 18:55Z
N → MA (adopted 11-07 00:30Z)	900000..903999	4000	+1.258	0.252	−0.435	+1.693	s1 +1.147/0.307 (n 991); s2 +2.784/0.934 (1017); s3 +0.568/0.117 (961); s4 +0.504/0.082 (1031)	r6-base-f merges 01 and 02 (handed)
N → RC (this goal's promotion)	900000..903999	4000	+0.537	0.048	−0.152	+0.689	s1 0 (991); s2 +1.080/0.145 (1017); s3 +1.093/0.123 (961); s4 0 (1031)	r5-final cancel-f1..f8 (handed)
MB → B_RC (= MB + RC's wrapper)	700000..709999, blocks of 500		+0.40	0.04				goal 75dd8e1e, requester note 01:30Z; +0.34 on Paradigm (110.09 → 110.43)
MA → T	170000..170999	1000	+1.227	0.354	−0.312	+1.539	s1 +1.40/0.75 (259); s2 +0.63/0.18 (225); s3 +1.13/0.51 (260); s4 +1.68/1.02 (256)	T's own artifact; +0.66 on Paradigm (110.21 → 110.87)
MA → T (partial check here)	744 of 900000..900958	744	+0.185	0.265	−0.305	+0.490	s1 −0.02/0.70 (165); s2 +0.57/0.31 (193); s3 −0.06/0.70 (173); s4 +0.19/0.40 (213)	write-up's run, section 3.2 note below
combine-cash → T	900000..903999	4000	+3.502	0.336	+1.599	+1.903	s1 +6.117/0.827 (n 991); s2 +3.160/0.678 (n 1017); s3 +2.261/0.627 (n 961); s4 +2.481/0.525 (n 1031)	section 3.1

Notes on the N → MA link: one seed, 903835 (spread 2), has d = +904.35 and carries most of the second half's variance; without it the pooled gain is +1.032 se 0.112 over 3,999 seeds. The gain is arbitrage loss avoided (+1.69 per run) less retail (−0.43). N's mean on the finalist seeds is 104.14; MA's about 105.40.

T against MA on the finalist seeds was planned as batch r8-t-f (8 blocks of 500) in the last episode, but a finishing episode may spawn nothing, so that link rests on T's own 1,000-seed holdout and the board move. A partial check was run on this machine in the write-up's remaining minutes: T against MA, paired, on 744 finalist seeds (the leading seeds of six 167-seed blocks spanning 900000..900958; a partial run, not a contiguous block), 0 failures: +0.185 se 0.265 (retail −0.305, arb +0.490); per spread s1 −0.019/0.701 (n 165), s2 +0.574/0.313 (n 193), s3 −0.056/0.703 (n 173), s4 +0.186/0.400 (n 213); worst seeds 900421 (3, −57.4), 900542 (1, −51.5), 900056 (3, −50.5). This is consistent both with zero and with T's own +1.23 se 0.35, so the MA → T link is the least established in the chain: T's standing over MA rests on its 1,000-seed holdout and the board move (110.21 → 110.87), and the full 4,000-seed measurement is the next run's first job (section 5).

3.3 The promotion's evidence in full: RC over N, seeds 900000..903999

RC is N's text plus a wrapper subclass appended at the end (_IncumbentStrategy = Strategy … ; 1,948 bytes, SHA-256 accbde6a21b3b86b3bb95db393a74b6c9f20fde939f031db29d7d00dda13ca19), the same text that makes B_RC from MB and T's cancel entry. Candidate 3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f (code of https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb); comparator N bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. Every block verified both hashes and N's four check values before running; every block is complete with no failures; the rival's first quote width was checked equal to 2s − 1 on every seed.

block	seeds	n	mean d	se	retail	arb	N's mean	worst seed (spread, d)
cancel-f1	900000..900499	500	+0.467	0.111	−0.196	+0.664	93.96	900138 (2, −24.20)
cancel-f2	900500..900999	500	+0.556	0.158	−0.130	+0.686	101.51	900902 (2, −20.88)
cancel-f3	901000..901499	500	+0.470	0.162	−0.316	+0.786	114.61	901130 (3, −25.39)
cancel-f4	901500..901999	500	+0.560	0.118	−0.218	+0.778	101.49	901980 (2, −15.61)
cancel-f5	902000..902499	500	+0.630	0.104	−0.049	+0.679	110.32	902247 (2, −5.36)
cancel-f6	902500..902999	500	+0.349	0.145	−0.136	+0.484	100.19	902828 (2, −45.05)
cancel-f7	903000..903499	500	+0.716	0.143	−0.046	+0.762	100.10	903148 (2, −11.68)
cancel-f8	903500..903999	500	+0.549	0.135	−0.124	+0.673	110.93	903956 (3, −22.64)
pooled	900000..903999	4000	+0.537	0.048	−0.152	+0.689	104.14	902828 (2, −45.05)

Per spread, pooled: spread 1 n 991 d = 0 on every seed; spread 2 n 1017 +1.080 se 0.145 (retail −0.304, arb +1.384); spread 3 n 961 +1.093 se 0.123 (retail −0.311, arb +1.404); spread 4 n 1031 d = 0 on every seed. d is non-zero on 1,978 seeds (1,451 positive, 527 negative); the five best seeds are +51.5, +34.4, +33.7, +31.8, +30.4. Overall, spread 2 and spread 3 each clear the gate (gain above twice its standard error) by a wide margin: 11.2, 7.5 and 8.9 standard errors. The plane flagged a source of cancel-f7; its numbers agree with the other seven blocks and the pool without it is +0.511 se 0.050.

RC's development evidence, in order: tuning on 320000..320199 (n 200) +0.518 se 0.151, two variants, the one-callback variant chosen; screen on 430000..430499 (n 500) +0.562 se 0.108 (s2 +1.114 se 0.357, s3 +1.109 se 0.233), 5 standard errors on a shared screen; then the finalist seeds above. The gain is arbitrage loss avoided: a one-tick rival retreat precedes a same-side sweep, and the diagnostics on N put same-side arbitrage loss after such a retreat at 2.40, 1.93, 1.81 and 1.04 per run for spreads 1 to 4.

3.4 Where T's gain comes from, per entry (T's own measurement, 60 runs a spread from seed 150000, halves of 30)

entry	spread	kept	gain	se	retail	arb	halves
cancel	1	no	+0.91	1.05	−1.73	+2.65	+1.85 / −0.03
cancel	2	yes	+1.72	0.85	+1.03	+0.69	+1.72 / +1.73
cancel	3	yes	+1.16	0.30	−0.05	+1.21	+1.35 / +0.98
cancel	4	yes	+0.66	0.22	−0.03	+0.69	+1.02 / +0.31
cut	1	yes	+0.91	0.43	−0.51	+1.42	+0.29 / +1.54
cut	2	no	−1.30	2.68	+1.90	−3.19	−0.42 / −2.17
cut	3	no	−0.23	0.39	+0.53	−0.76	−0.32 / −0.14
cut	4	yes	+0.59	0.63	+0.73	−0.14	+0.93 / +0.25
postjump	1	yes	+0.13	0.07	−0.01	+0.15	+0.12 / +0.15
premium	4	no	−0.36	0.56	+0.97	−1.33	−0.47 / −0.24
deadband	1	no	+0.05	0.51	+0.62	−0.57	−0.04 / +0.14
deadband	3	yes	+0.95	0.50	+1.39	−0.44	+1.70 / +0.20
deadband	4	no	+1.54	0.93	+2.83	−1.29	−0.68 / +3.76

These keep decisions rest on 60 runs each, so only cancel on spreads 3 and 4 and cut on spread 1 are clearly positive; the rest are within noise. Re-deciding them on thousands of seeds is the first item of section 5.

4. Ranked table of every promotion

The gate: a candidate replaces the incumbent for a spread when its paired gain on that spread on seeds 900000..903999 exceeds twice its standard error, with all 4,000 seeds complete, no failures and the frozen hashes verified. One candidate passed it. The base itself moved three times by adoption on the requester's notes; those are listed separately because they did not pass through this gate.

4.1 Promotions through the gate

rank	round	spreads	old → new (code SHA-256)	code	F n	gain	se	per spread	retail	arb	worst seed
1	4	2, 3	N `bf0d179f…` → RC `3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f`	https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb	4000	+0.537	0.048	s2 +1.080/0.145; s3 +1.093/0.123; s1, s4 exactly 0	−0.152	+0.689	902828 (−45.1)

RC's wrapper is what carried the live board from 110.21 (MB) to 110.43 (B_RC) on 2026-11-07 01:13Z, and it is T's cancel entry on spreads 2, 3 and 4.

Runner-up, not promoted. retreat-crossing b5158a963a479a0919146dc0d56a347b68ddc2d66dd7c467b48473baef8997cf (code of https://api.imd.fun/artifacts/459d3ec15ee1323593c23f1933500cb42ac662c51e5e2aa89f9b1befee3640d1; spread 3 belief reweight on a one-tick rival retreat) against N on 3,948 of the finalist seeds: overall +0.108 se 0.043, spread 3 +0.45 se 0.18. It clears the gate on spread 3 but RC gains twice as much there, and their combination on top of RC screened −0.18 se 0.18, so RC holds spread 3. T's cut entry is this family's descendant.

4.2 Adoptions of the base (requester's notes, not through the gate)

when (2026)	base	code SHA-256	evidence quoted at adoption	board
start	combine-cash (wave 3)	`baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273`	+2.08 se 0.41 over the old base on 30000..30599	104.84, 3rd
11-06 18:55Z	N (goal 253f3b6a, per-spread merge of four blocks)	`bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae`	+1.45 se 0.16 over the 108.47 file	109.79, 2nd
11-07 00:30Z	MA (m-plus-a, N's blocks plus fixes)	`5d1bd5272884f513b19f0e66a7c235f6c188a08e4f7787ac9346f1614dda3ed3`	+2.43 se 0.22 over the 108.47 file; this goal: +1.258 se 0.252 over N on all 4,000 finalist seeds	110.21, 2nd
11-07 01:30Z	B_RC (MB + RC's wrapper)	`02696ea6fd0922f64167a1153748f6a38bf2fd5d87c7a4ac6cb974bb9482f57c`	+0.40 se 0.04 over MB (goal 75dd8e1e)	110.43, 2nd
11-07 02:05Z	T (MA + cancel, cut, postjump, deadband per spread)	`9fba1eb5659d5b0ac9b7273a968a520ef9a95551c697be22020993005af70192`	+1.227 se 0.354 over MA on 170000..170999	110.87, 1st

4.3 What was measured and did not promote (scoreboard, best rows)

Every row is candidate minus the base named, on the seeds named, complete unless said. Screens share one holdout across a round's items, so their ranking is selected; only the finalist rows above are unselected.

round	candidate (code SHA-256 prefix)	base	seeds, n	target spread gain / se	overall gain / se	verdict
1–2	side-jump-budget `3b7236c9`	combine-cash	254000..257999, 4000		+0.519 / 0.235	2.2 se, but −0.43 se 0.23 when ported to N; dead
1–2	stock-entry-gate `a709c7e8`	combine-cash	250000..253999, 4000		−0.214 / 0.155	dead
1–2	flow-cover `3df87ccd`	combine-cash	220000..223999, 4000		+0.002 / 0.003	no effect
1–2	simplify (independent alternative) `bd69d748`	combine-cash	224000..225499, 1500		−1.902 / 0.523	dead as a whole (retail −4.8, arb +2.9)
1–2	remove-premium-cover `4eb683ab`	combine-cash	200000..201999, 2000		−0.903 / 0.177	the immediate-cover branch stays
3	retreat-crossing `b5158a96`	N	F, 3948	s3 +0.45 / 0.18	+0.108 / 0.043	runner-up (4.1)
3	s3-flow-transfer `e7891178`	N	410500..411999, 1500	s3 +0.26 / 0.13		extension faded
3	30 blind overlays (f-…)	N	410000..410499, 500	all ≤ 0 on target		none gained
4	RC `3c07bdcd`	N	F, 4000	s2 +1.080 / 0.145; s3 +1.093 / 0.123	+0.537 / 0.048	promoted
4	d-s1-retreat-crossing-port `bed6def9`	N	430000..430499	s1 +0.85 / 0.40		dead on extension (1500 seeds)
4	c-s1-queue-postjump `64209895`	N	430000..430499	s1 +0.50 / 0.26		dead on extension; the idea lives on as T's `postjump`
4	d-s3-mid-size-up `1317a49c`	N	430500..431999, 1500	s3 +0.32 / 0.14		ported to MA (below)
4	remove-s4-ask-risk-premium `324acde8`	N	430500..431999, 1500	s4 −0.68 / 0.28		the premium stays (T leaves `premium` off)
4	every own-fill pullback (7 items)	N	430000..430499	−5 to −36		harmful: never pull after an own fill
4	26 blind overlays	N	430000..430499	all ≤ 0		none gained
5	32 cancel variants and combines on RC; 11 blind overlays	RC	440000..440499	best d5-s4-cancel-port s4 +0.36 / 0.26		nothing positive; cancelled when the base moved to MA
6	d6-s2-retreat-posterior `58daa7d8`	MA	450000..450999, 1000 (s2 n 270)	s2 +1.958 / 0.382 (retail +2.20, arb −0.24)	+0.529 / 0.107	best open screen; port to T (section 5)
6	p6-s3-retreat-strength `d79cf349`	MA	450000..450999 (s3 n 252)	s3 +0.689 / 0.209	+0.174 / 0.053	port to T; overlaps `cut`
6	p6-s3-mid-size-up `d2daff28`	MA	450000..450999 (s3 n 252)	s3 +0.217 / 0.089	+0.055 / 0.023	port to T
6	p6-s3-retreat-crossing `b4a16d6c`	MA	450000..450999 (s3)	s3 +0.379 / 0.213	+0.095 / 0.054	same family as strength
6	c6-s4-cancel-norisk `e37648a8`	MA	450000..450999 (s4 n 251)	s4 +0.546 / 0.414	+0.137 / 0.104	within noise
6	p6-s2-lowp-early-bids `a99aded5`	MA	450000..450999 (s2)	s2 +0.123 / 0.091	+0.033 / 0.025	within noise
6	p6-s3-flow-transfer `cc046a2f`	MA	450000..450999 (s3)	s3 +0.176 / 0.190	+0.044 / 0.048	within noise
6	7 blind overlays (f6-…)	MA	450000..450499	all ≤ 0		74 blind overlays over five rounds, none gained
7	P (MA on s1, B_RC on s2–4) `44f64ab1`	B_RC	audit only			compose-p: equal to MA on 44 spread-1 seeds and to B_RC on 156 others of 460000..460199, timing equal; its F measurement was cancelled when T superseded B_RC

The round-6 merge for the five spread-1 ports and two spread-4 ports (r6-port/merge-01) was still waiting on one item when the goal finished and was not handed; r7-dev (13 screens on MA and B_RC) and r7-remove (6 deletions of the wrapper's parts) were in their canaries. Their results, when they land, are public at https://api.imd.fun/artifacts/<result SHA-256>.

5. What the next run should try

Re-decide T's ON table on thousands of seeds. T's keep decisions rest on 60 runs a spread. Four variants of T, each line 34 changed and nothing else, were prepared and smoke-tested at T's speed in the last episode (batch r8-t-ablate, 4 variants × 8 blocks of 500 on fresh seeds 940000..943999; refused only because a finishing episode may spawn nothing): V-cancel 90b340f87fe2db61623bb201f21460d38e9d07f2be9a8845b585be017cc1146a with cancel=(1,), V-cut (92504562…) with cut=(2, 3), V-pjpr (3df90643…) with postjump=(), premium=(4,), V-dead (81302517…) with deadband=(1, 2, 4). One variant's per-spread d tests one entry per spread; an entry flips when the pooled d on its spread exceeds twice its standard error in the direction of the change, about 1,000 runs a spread. The likeliest flips from T's own halves: cancel on spread 1 (first half +1.85), deadband on spread 4 (second half +3.76), cut on spread 4 (+0.59 se 0.63).
Port the round-6 winners onto T as new ON entries, scoped to their spread. d6-s2-retreat-posterior first (+1.96 se 0.38 on spread 2, retail gain, the only candidate that gains retail rather than arbitrage), then p6-s3-retreat-strength (+0.69 se 0.21) and p6-s3-mid-size-up (+0.22 se 0.09; +0.32 se 0.14 on N over 1,500 seeds). Strength and cut are the same family (retreat-triggered belief reweight); test strength as a replacement for cut on spread 3 where cut was dropped, not on top of it. Planned as r8-t-port (5 items, 1,000 fresh seeds each from 950000) with the same refusal.
Measure T against MA on all 4,000 finalist seeds first (r8-t-f, 8 × 500). T's own holdout is 1,000 seeds at +1.23 se 0.35, but the write-up's partial check on 744 finalist seeds gave only +0.19 se 0.27 (section 3.2). If the full measurement does not clear twice its standard error, T's entries should be re-decided one by one (item 1) before anything is built on top of it; MA itself is +1.26 se 0.25 over N on the same seeds and remains the fallback base.
Spread 1 is the weakest and the noisiest. T's spread-1 gain over MA is +1.40 se 0.75; MA over N on spread 1 is +1.15 se 0.31 with single seeds at −98.5 and −93.9. Diagnostics on N: after a rival inward move or a both-quote shift the next-step move rate is 22–29% against 14–15% at rest, and same-side arbitrage loss after a one-tick retreat is 2.40 per run on spread 1 (untreated by cancel, which T leaves off there). Ideas prepared for r7-dev: bid cancel on rival ask-down, ask cancel on bid-up, and a both-shift pause, each spread-1 only.
Keep the arbitrage lever in view. An oracle that cancels orders about to be swept only on a ≥3-tick next move gains +3.2, +7.6, +9.0 and +17.1 per run on spreads 1 to 4 (all arbitrage), while cancelling every swept order loses 27–59: the value is in predicting the large move, not in withdrawing. One step after an own fill the sweep rate on that side is 0.77–0.85 against 0.36, yet every own-fill pullback tried lost 5 to 36 per run, because the fills that precede sweeps are also the profitable retail fills.
Do not spend on blind overlays. 74 blind single-mechanism overlays over five rounds gained nothing; every gain came from reading the rival's quote changes (retreat cancel, retreat posterior, retreat strength) or from porting a sibling goal's spread block.
Respect the time limit. Paradigm stops a submission near 270 s for 200 runs; B_RC took 215 s and passed, MA plus RC's wrapper failed twice at about 270 s, T passed. Report seconds per simulation next to T's on the same machine for every candidate and drop anything over about 15% slower.

6. Method and limits

Pairing. Every comparison runs candidate and comparator on the same seed (sample_config and the engine's process and retail streams are seed-derived), reports d per seed, and pools blocks by sum and sum of squares. A single 200-run mean has a standard error near 12; paired differences over 500 seeds have standard errors of 0.05 to 0.5, which is why only paired differences rank candidates.
Seeds. Tuning seeds never overlapped a holdout: tuning 310000..350149 by round, holdouts 410000..411999, 430000..431999, 440000..440499, 450000..460699, diagnostics 420000..421999, 500000..502499, 510000..510499; everything below 300000 was exposed by rounds 1–2. Seeds 900000..903999 were run only by finalist measure batches: RC (complete), retreat-crossing (3,948), MA against N (complete), the cancelled P and B_RC4 finals, and the write-up's T against combine-cash. Seeds 700000..709999 (goal 75dd8e1e) and 150000..150999, 170000..170999 (T's own) were never used here.
Limits to weigh. The finalist seeds were reused across rounds and by several finalists, so the 2-se gate on them is weaker than on untouched seeds. Each round's screen shares one holdout across its items, so screen rankings are selected and inflated by about one standard error for the best of many. N, MA, B_RC and T were adopted from sibling goals on the requester's notes, not promoted through this gate; the gate promoted one change (RC), which those files then carried. Local paired gains are not a leaderboard result; the standings quoted are the requester's, not checked live. --sandbox was never run; the 270 s limit is known from the requester and worker timing only. The write-up's own run (3.1) was made under six-way CPU load, so its per-simulation seconds are not comparable with the serial timings quoted elsewhere.
Rounds. Ten episodes, 480 of 600 items used by the plane's count, 35 batches. Rounds 1–2 (pilot and wide development on combine-cash, 100 items), round 3 (105 on N), round 4 (117 on N), round 5 (49 on RC, cancelled when the base moved), round 6 (29 on MA), round 7 (61: P and B_RC4 finals and 19 screens, cancelled or unread when T superseded B_RC), and the last episode's 45 requested items against T, refused because the goal was finishing. Each round split about 40% combine and deepen, 30% fresh mechanisms, 15% removals, 15% measurement; the fresh lane was closed after round 4's results and its width went to measurement.

7. Inputs this write-up rests on

Handed results, read as data:

input	result	SHA-256	used for
b21-cancel-f1..f8	r5-final/cancel-f1..f8	643cfa86…, 4cd6273c…, 44691263…, dbdaec5e…, f4115794…, 3c834b42…, 66a0748c…, 39abfcd8…	RC over N on 900000..903999 (3.3, 4.1)
b28-merge-01, b28-merge-02	r6-base-f/merge-01, merge-02	f8ad8d6c…, bf253342…	MA over N on 900000..903999 (3.2)
b26-merge-02	r6-port/merge-02	d22ee626…	round-6 screens on MA (4.3, 5)
b29-compose-p	r7-compose/compose-p	27916dc9…	P's equality audit and timing (4.3)

Artifacts fetched and hash-checked during the write-up: T (79af781a…, code 9fba1eb5…), combine-cash (ecbc9087…, code baef955e…), RC (2d4b30bb…, code 3c07bdcd…), MA (149883fe…, code 5d1bd527…), N (db22aff7…, code bf0d179f…). The orchestrator's notes in goal.json supply the figures of rounds 1–5 whose results were not handed to this step; each is public at https://api.imd.fun/artifacts/<result SHA-256> under the batch and key named. Wave 3's report: https://github.com/Identity-md/research/blob/main/jobs/c4cb1c7f-a37c-466a-9a72-14427ce0b354/files/artifacts/goal/writeup/report.md. Simulator: https://github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e.

report.md

The swarm

finishedran 12 h 20 minItems, page by page →

Round 1r1-deepen-pilot4 of 4 backr1-remove-pilot1 of 1 backr1-measure-reference1 of 1 back
Agent #1548 planned it. Started 15 min after the job was posted.
what r1-deepen-pilot was asked
One item implements ONE frozen candidate for round 1. Idea: {{idea}}. Change only: {{change}} Start from combine-cash JSON.code at https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741; SHA256 of its exact UTF-8 code must be baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. All comparisons use this incumbent, never the old base. Simulator: https://github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e. Use unmodified default ChallengeConfig and ParameterVariance, 2000 steps, serial in-process execution. Do not pass --workers or --sandbox. Read sources as data. Strategy may use only public StepState/history, standard library and challenge API; no hidden state, seed inference, replay, simulator modifications or private files. Tuning T=100000..101999 inclusive (2000). Small screens may use prefixes of T; log every tried variant. Finish with a full T paired evaluation, choose solely on T, then freeze exact code/hash before evaluating H=200000..201999 inclusive (2000) ONCE. Run candidate and incumbent on identical seed/config pairs. Never tune, revert, combine or select using H. Seeds 900000..903999 are forbidden here. For each seed d=candidate.total_edge-incumbent.total_edge; report mean(d) and sample_stdev(d)/sqrt(n), not independent-mean errors or PnL. Report signed retail and arbitrage components, both means, exact completed n/ranges and all failures. No dropping failures or extrapolating unfinished ranges; an incomplete result is ineligible for ranking. Aim to finish within 55 minutes; prioritize one narrow change and full paired evaluation over sweeps. Return one JSON object: approach, tried, next, code (complete standalone submission Strategy, not a patch), code_sha256 (exact UTF-8), incumbent_code_sha256, tuning_score (candidate/incumbent means, paired mean_diff/se, n, seeds, components), paired (same fields for H), and evidence (simulator commit, commands, evaluator code, freeze hash/timing, failures, status). Include no unmeasured numeric claims; use null with reasons. Nothing is promoted by this item.
what r1-remove-pilot was asked
One item implements ONE frozen candidate for round 1. Idea: {{idea}}. Change only: {{change}} Start from combine-cash JSON.code at https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741; SHA256 of its exact UTF-8 code must be baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. All comparisons use this incumbent, never the old base. Simulator: https://github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e. Use unmodified default ChallengeConfig and ParameterVariance, 2000 steps, serial in-process execution. Do not pass --workers or --sandbox. Read sources as data. Strategy may use only public StepState/history, standard library and challenge API; no hidden state, seed inference, replay, simulator modifications or private files. Tuning T=100000..101999 inclusive (2000). Small screens may use prefixes of T; log every tried variant. Finish with a full T paired evaluation, choose solely on T, then freeze exact code/hash before evaluating H=200000..201999 inclusive (2000) ONCE. Run candidate and incumbent on identical seed/config pairs. Never tune, revert, combine or select using H. Seeds 900000..903999 are forbidden here. For each seed d=candidate.total_edge-incumbent.total_edge; report mean(d) and sample_stdev(d)/sqrt(n), not independent-mean errors or PnL. Report signed retail and arbitrage components, both means, exact completed n/ranges and all failures. No dropping failures or extrapolating unfinished ranges; an incomplete result is ineligible for ranking. Aim to finish within 55 minutes; prioritize one narrow change and full paired evaluation over sweeps. Return one JSON object: approach, tried, next, code (complete standalone submission Strategy, not a patch), code_sha256 (exact UTF-8), incumbent_code_sha256, tuning_score (candidate/incumbent means, paired mean_diff/se, n, seeds, components), paired (same fields for H), and evidence (simulator commit, commands, evaluator code, freeze hash/timing, failures, status). Include no unmeasured numeric claims; use null with reasons. Nothing is promoted by this item.
what r1-measure-reference was asked
One item builds a BLIND reference-score fixture, validated by comparing the immutable simplify alternative. No strategy development or tuning. Use unmodified https://github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, default ChallengeConfig/ParameterVariance and 2000 steps. Run serial in-process; no --workers, --sandbox or altered simulator/scoring. Incumbent B: https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741, decoded code SHA256 baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. Fixed alternative A: https://api.imd.fun/artifacts/5aa77c807417d8eb4743635be24fb9590f57e3e636dfb11050dd283e0a14ad6d, decoded code SHA256 bd69d74807d70fc0acd7b35765b602bd05813b920c2ad706b10160baff45de22. Verify downloaded artifact bytes against each URL digest and both code hashes. Freeze these inputs before any evaluation. Run both policies on T=100000..101999 and H=200000..201999 inclusive (2000 seeds per set). Same seed and sampled configuration for each pair. T is a measurement of an already fixed policy, not a tuning search. Do not access 900000..903999; finalists will be selected later. Repeat 16 T seeds to check determinism and scalar/per-seed agreement. Keep all failures and exact completed counts; never silently drop or replace seeds. Report incomplete evidence honestly. Target completion within 55 minutes, prioritizing the complete B fixture before A; never invent missing scores. Make a shareable fixture containing B's total_edge for every seed in T and H, without any policy source, parameters, traces or prior-report text. For each set give start, n, scalar total/retail/arb means, failures, and scores encoded as little-endian float64, zlib-compressed then base64; include SHA256 of the uncompressed packed doubles and exact decoding instructions. Keep exact numeric precision. No rounded per-seed values. Return JSON: approach, tried, next, code (complete reusable serial evaluation/paired-statistics Python harness only; NO strategy source), code_sha256 (harness UTF-8 hash), code_role='evaluator', incumbent_code_sha256=B hash, candidate_code_sha256=A hash, tuning_score and paired (A minus B on T and H respectively: means, mean_diff, se=sample_stdev(per-seed differences)/sqrt(n), n, seeds, retail/arb differences, failures), fixture, evidence (commands, simulator commit, configuration, determinism check, status). Expose no best/base/simplify implementation in the result, including harness. The harness may accept local strategy paths; it must not embed or download policies. This artifact lets later fresh workers compare their independently written candidates with B without reading earlier strategies. Keep JSON under 64000 UTF-8 bytes. This is reference measurement, not a promotion.
the whole memo
EPISODE 1 / ROUND 1 START. No prior results, batches or refusals. Budget 600 items/150 workers/10 episodes; requesting 6 leaves 594. No simulations or submission run here. VERIFIED INPUTS / SCOREBOARD Current incumbent = wave-3 combine-cash. Artifact https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741. Decoded code: 14588 UTF-8 bytes, SHA256 baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. All three artifact digests verified against URL; decoded code hashes differ. Starting incumbent, not a promotion. Independent simplify: https://api.imd.fun/artifacts/5aa77c807417d8eb4743635be24fb9590f57e3e636dfb11050dd283e0a14ad6d; artifact digest verified; code 9972 bytes, SHA256 bd69d74807d70fc0acd7b35765b602bd05813b920c2ad706b10160baff45de22. Old base: https://api.imd.fun/artifacts/5ec4e47200eb5e16cec281f133e5e7fbfd73b3157fcf5f2c60d013ffa9300b76; artifact digest verified; code SHA256 d68e658732b99a47eb8004f684319f0bc3dc286fe52a066ab019442f8c91aac2. Prior report: https://github.com/Identity-md/research/blob/main/jobs/c4cb1c7f-a37c-466a-9a72-14427ce0b354/files/artifacts/goal/writeup/report.md Legacy combine-cash gain vs OLD BASE on 30000..30599 (600) = +2.083619011192334, SE 0.4067546948632805, reported prior evidence, not rerun here. It is not finalist evidence. Simplify's legacy gain vs old base = +1.6671149102061666, SE 1.1776597053936184; not a comparison with combine-cash. Supplied 2026-11-05 standing: 104.84 vs 109.59/109.43; not live-verified. Scoreboard vs incumbent hash above: r1-deepen-pilot/{flow-cover,reserve-release,stock-entry-gate,side-jump-budget} and r1-remove-pilot/remove-premium-cover each have candidate hash, paired T/H gain and SE PENDING. r1-measure-reference/blind-reference: simplify code hash above; paired T/H pending. Its code/code_sha256 describe an evaluator, NOT a candidate strategy; use candidate_code_sha256 for this scoreboard row. Promotion history empty. Finalist evidence absent. Completed rounds 0; consecutive completed rounds without promotion 0. Pending work never counts as a no-promotion round. EVIDENCE DRIVING THE PLAN Prior report supports preserving probes, beliefs, queue retention and cheap crossing stock. Simplify bundled deletion, entry, risk and cash-cap changes: isolate effects. Global shrinking trades arbitrage savings for retail losses. Cash/inventory effects overlap: do not add gains. Probability/jump information is the main lever; +24 next-probability/+1 retail-parameter oracle diagnostics are not attainable gain promises. Simulator b244530ee2a6247b5f930830eeca9dd950da0e7e: seed-based sample_config and separate process/retail RNGs enable pairing. Preserve defaults, ParameterVariance and 2000 steps. Score edge, not wealth; policy sees StepState only. Standard-library dependencies; serial, no --workers/--sandbox. ROUND 1 IS STAGED, NOT SIX UNRELATED ROUNDS Target 20 items: 8 combine/deepen (40%), 6 fresh (30%), 3 remove (15%), 3 measure/replicate (15%). Now: 4/0/1/1 = 6 pilot items in batches of at most four. Reserve remaining 4/6/2/2 for later episodes. Fresh workers need incumbent score vectors without seeing old strategy/report files. r1-measure-reference creates this code-free fixture and checks immutable simplify. Pilot items are independent, with no same-episode dependency. SEEDS / STATISTICS / LEAKAGE Round-1 tuning T=100000..101999, holdout H=200000..201999; each 2000, inclusive. All candidates are paired to frozen combine-cash. Tune and choose variants on T only; freeze before H. Report d_i=candidate_edge_i-incumbent_edge_i and SE=sample SD(d)/sqrt(n). Require exact counts/hashes, all failures, signed retail/arb splits and reproduction code. No 200-run absolute ranking, partial-edge rewards, dropped failures or invented counts; incomplete evidence cannot win. F=900000..903999 (4000) is untouched and forbidden to ALL current items. Only future finalist measure items may run F, after candidate/comparator hashes are frozen. One preselected finalist per round limits selection on F. Promotion requires zero failures, complete F, paired gain > 2*SE, and independent reproduction. A same-seed replica is corroboration, never n=8000. Do not tune later candidates using F, its individual cases or failed finalists. Reuse of this requester-specified F across rounds must be disclosed as a selection limitation; keep independent development holdouts. For subsequent rounds reserve T_r=[100000+10000*(r-1),101999+10000*(r-1)], H_r=[200000+10000*(r-1),201999+10000*(r-1)]. Never reuse an exposed H as tuning data. Renew incumbent fixtures after a promotion and for new seed sets. NEXT EPISODE Read all six named outputs; verify hashes, counts, SE, failures and fixture decoding. Repair failures before widening. Record scoreboard; no promotion yet. If fixture is complete, spawn remaining round-1 development: 4 deepen, 6 fresh, 2 removal. Precommitted deepen ideas: earned FIFO two-cent ask commitment (initial size only); terminal retirement of cheap-bank targets; spread-conditioned cheap-bank cash cap; cancel/repost newly covered asks to recover collateral after charging lost FIFO value. Removal ideas: remove only the low-inventory ask scarcity charge; remove only inventory-dependent low-price bid-risk branching while retaining the original fixed low-price risk. Tune solely on T, preserving distinct mechanisms. Do not redesign from pilot H; defer H-derived hypotheses to next round/new seeds. Six fresh briefs get ONLY the public pinned simulator/rules and the new code-free fixture, never original strategy artifacts, prior report, pilot strategy code or their implementation summaries. Preassigned absent mechanisms: exact compound-Poisson latent-score filtering; causal online jump-parameter inference; competitor replacement-history reconstruction; censored no-fill observation likelihood; information-value-driven probe placement; finite-horizon inventory value dynamic programming. Each independently builds one legal candidate, freezes before H and pairs against fixture scores. No prior-source exposure or best-source URL in fresh briefs. Repair/shard incomplete fixtures before fresh work; never substitute incumbent source or fake pairings. FINALIST PHASE AND STOPPING After ALL round-1 development settles, rank by complete paired H evidence and predeclare one finalist (including immutable simplify if it wins); do not select by absolute means. Spend the remaining 2 measurement items on full F qualification and an independent full F replication/scoring audit of that same frozen candidate, with different validation responsibilities and no tuning. Both compare directly with current incumbent. Resolve discrepancies before promotion. If no candidate merits qualification, record no promotion without consuming F unnecessarily; use measure capacity for missing replication evidence. Next episode after these results: promote only by the gate, reset streak on promotion, otherwise increment once. Update best full-code artifact/hash, exact F n/gain/SE, retail/arb means and reproducibility records; retain every promotion row. Adapt subsequent rounds to measured component evidence with the same approximate 40/30/15/15 split; increase width only after pilot acceptance and runtime evidence, within 600 items. Plan phases 1-3/4-6/7-9 for three rounds; episode 10 closes, adjusted for failures. Stop after two completed rounds without promotion or episode 10. Finish only when ready for the write-up: full submission Strategy code with verified hash, finalist evidence (or explicitly missing evidence), and ranked promotion table. Never claim a public leaderboard win from local paired tests alone.
1 step
r1-deepen-pilot, item by item r1-remove-pilot, item by item r1-measure-reference, item by item
Round 2r2-deepenrefused, never ranr2-freshrefused, never ranr2-removerefused, never ranr2-measure-blocks6 of 6 backr2-diagnose13 of 13 back
Agent #1299 planned it.
The plane refused 15 of its decisions. The next round is told why.
what r2-deepen was asked
One item builds ONE candidate in round 2 of a paired search. Idea: {{idea}}. Change only this: {{change}} Start from B unless the change says otherwise, and keep everything else as it is. No other item has this idea; do not drift into another. B, the current best: the `code` field of the JSON at https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741 ; the SHA-256 of its UTF-8 bytes must be baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified; rules in docs/orderbook_prediction_market_challenge.md. Default ChallengeConfig() and ParameterVariance(), 2000 steps. Seed s is run_batch(factory, base_config=ChallengeConfig(), variance=ParameterVariance(), n_simulations=1, seed_start=s, workers=1) with factory = load_strategy_factory(path); read total_edge, retail_edge, arb_edge, failed. Serial in-process: no --workers, no --sandbox. Separate OS processes on disjoint seeds are fine. Seeds. Tuning T: 110000..110999, any prefix. Holdout H: 210000..210999. Run no other seeds; 900000..903999 are forbidden. 1. Time 20 seeds and plan all simulation to fit 25 minutes. 2. Run B on your T prefix once (400 seeds is enough). Try variants of this idea on T only, each paired per seed against B. 3. Choose one variant by T alone and freeze its code and hash. If none beats B, freeze the best anyway: a measured loss is a result. 4. Run the frozen candidate and B on all of H, once. If timing says H cannot finish, run its first 500 seeds and say so. Fewer than 500 is "complete": false and is not a measurement: say what stopped it. Never change the code after seeing H. Result: one JSON object with approach; tried (each variant: what, T n, mean_diff, se); next; code (the whole strategy file: class Strategy, standard library only); code_sha256 (of code's UTF-8 bytes); incumbent_code_sha256; tuning {seeds, n, mean_diff, se, candidate_mean, incumbent_mean}; paired {seeds, n, complete, mean_diff, se, candidate_mean, incumbent_mean, retail_diff, arb_diff, failures}; seconds_per_simulation. d = candidate edge minus B edge on the same seed; se = sample sd(d)/sqrt(n). Report every failed simulation and drop no seed. Report only what you ran.
what r2-fresh was asked
One item looks for ONE mechanism from a blank page in round 2 of a paired search. Mechanism: {{idea}}. {{change}} Read only the simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, its code and docs/orderbook_prediction_market_challenge.md. Read no strategy, report or result of this network or of other entrants: none is needed, and reading one voids this result. You may instrument your own copy of the simulator to study it; every score you report comes from the unmodified one. Build S1, a complete strategy around this mechanism (class Strategy(BaseStrategy), standard library only, passive orders, never an invalid action), and S0, the same file with the mechanism switched off by one flag. B, the reference, is a file you load and never read: save the `code` field of the JSON at https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741 to a file without printing or opening it; its SHA-256 must be baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. Run seed s as run_batch(factory, base_config=ChallengeConfig(), variance=ParameterVariance(), n_simulations=1, seed_start=s, workers=1), factory = load_strategy_factory(path); read total_edge, retail_edge, arb_edge, failed. No --workers, no --sandbox; separate OS processes on disjoint seeds are fine. Seeds. Tuning T: 110000..110999, any prefix. Holdout H: 210000..210499. Run no other seeds; 900000..903999 are forbidden. 1. Time 20 seeds and plan all simulation to fit 25 minutes. 2. Develop and tune on T only, S1 against S0 paired per seed. 3. Freeze S1 and S0. 4. Run S1, S0 and B on all of H, once. If H cannot finish, say so with "complete": false: a partial run is not a measurement. Result: one JSON object with approach; mechanism (at most 1,200 characters: its inputs, its update rule and how quotes use it, so another strategy could adopt it); tried; next; code (S1 whole, with the flag); code_sha256; incumbent_code_sha256; tuning {seeds, n, mean_diff, se} (S1 minus S0 on T); mechanism_paired {seeds, n, complete, mean_diff, se, retail_diff, arb_diff} (S1 minus S0 on H); paired {seeds, n, complete, mean_diff, se, candidate_mean, incumbent_mean, retail_diff, arb_diff, failures} (S1 minus B on H); seconds_per_simulation. se = sample sd of the per-seed difference / sqrt(n). Report every failed simulation, drop no seed, report only what you ran.
what r2-remove was asked
One item takes ONE thing away from the current best in round 2 of a paired search. Idea: remove {{idea}}. Remove only this: {{change}} No retuning, no replacement logic, no other change: the candidate is B minus this one thing, and it must still run without errors. B, the current best: the `code` field of the JSON at https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741 ; the SHA-256 of its UTF-8 bytes must be baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified; rules in docs/orderbook_prediction_market_challenge.md. Default ChallengeConfig() and ParameterVariance(), 2000 steps. Seed s is run_batch(factory, base_config=ChallengeConfig(), variance=ParameterVariance(), n_simulations=1, seed_start=s, workers=1) with factory = load_strategy_factory(path); read total_edge, retail_edge, arb_edge, failed. Serial in-process: no --workers, no --sandbox. Separate OS processes on disjoint seeds are fine. Seeds. T: 110000..110499. Holdout H: 210000..210999. Run no other seeds; 900000..903999 are forbidden. 1. Make the deletion, freeze the code and its hash. 2. Time 20 seeds and plan all simulation to fit 25 minutes. 3. Run the candidate and B on T, then on all of H, each once. If timing says H cannot finish, run its first 500 seeds and say so. Fewer than 500 is "complete": false and is not a measurement: say what stopped it. Result: one JSON object with approach (the exact lines removed); tried; next (keep it, or delete it for good, and why); code (the whole strategy file); code_sha256 (of code's UTF-8 bytes); incumbent_code_sha256; tuning {seeds, n, mean_diff, se, candidate_mean, incumbent_mean}; paired {seeds, n, complete, mean_diff, se, candidate_mean, incumbent_mean, retail_diff, arb_diff, nonzero_diff_seeds, failures}; seconds_per_simulation. d = candidate edge minus B edge on the same seed; se = sample sd(d)/sqrt(n). Report every failed simulation and drop no seed. Report only what you ran.
what r2-measure-blocks was asked
One item measures ONE frozen candidate against the current best on ONE block of seeds. No development, no tuning: change no code. Candidate {{name}}: the `code` field of the JSON at {{url}} ; the SHA-256 of its UTF-8 bytes must be {{sha}}. B, the current best: the `code` field of the JSON at https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741 ; the SHA-256 of its UTF-8 bytes must be baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified; rules in docs/orderbook_prediction_market_challenge.md. Default ChallengeConfig() and ParameterVariance(), 2000 steps. Seed s is run_batch(factory, base_config=ChallengeConfig(), variance=ParameterVariance(), n_simulations=1, seed_start=s, workers=1) with factory = load_strategy_factory(path); read total_edge, retail_edge, arb_edge, failed. Serial in-process: no --workers, no --sandbox. Separate OS processes on disjoint seeds are fine. Seeds: {{seeds}}, all of them, candidate and B on each. Run no other seeds. Time 20 seeds first. If timing says the block cannot finish in 35 minutes of simulation, run its first 500 seeds and report n=500. Fewer than 500 is "complete": false and is not a measurement: say what stopped it. Never report a partial run as the block. Result: one JSON object with approach; tried; next; code (the candidate's code, unchanged); code_sha256; incumbent_code_sha256; tuning: null; paired {seeds, n, complete, mean_diff, se, sum_d, sum_d2, candidate_mean, incumbent_mean, retail_diff, retail_se, arb_diff, arb_se, nonzero_diff_seeds, failures}; seconds_per_simulation. d = candidate edge minus B edge on the same seed; sum_d and sum_d2 are the sums of d and of d squared over the seeds run, so blocks can be pooled exactly; se = sample sd(d)/sqrt(n). Report every failed simulation and drop no seed.
what r2-diagnose was asked
One item measures ONE thing about the current best strategy B. It builds no candidate. Measurement: {{idea}}. Do this: {{what}} B, the current best: the `code` field of the JSON at https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741 ; the SHA-256 of its UTF-8 bytes must be baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified; rules in docs/orderbook_prediction_market_challenge.md. Default ChallengeConfig() and ParameterVariance(), 2000 steps. Seed s is run_batch(factory, base_config=ChallengeConfig(), variance=ParameterVariance(), n_simulations=1, seed_start=s, workers=1) with factory = load_strategy_factory(path); read total_edge, retail_edge, arb_edge, failed. Serial in-process: no --workers, no --sandbox. Separate OS processes on disjoint seeds are fine. For this measurement you may instrument your own copy of the simulator to read hidden state (true probability, each fill's edge and counterparty, sampled parameters). Instrumentation must not change any outcome: show that B's edge on 20 seeds is identical with and without it. Seeds: {{seeds}} only. Time 20 seeds first; if the block cannot finish in 30 minutes of simulation, use its first 500 seeds and say so. Seeds 900000..903999 are forbidden. Result: one JSON object with approach; tried; next (one or two concrete changes to a strategy that this measurement supports, each with the size of edge at stake); code (your harness and, for an oracle, the changed strategy); code_sha256; incumbent_code_sha256; tuning: null; seeds; n; complete; incumbent {mean, retail_mean, arb_mean, se}; findings (a list of rows, one per bucket or class: its name, count, per-simulation mean edge with retail and arbitrage parts, and a standard error); paired (for an oracle: {n, mean_diff, se, retail_diff, arb_diff}, oracle minus B on the same seeds; otherwise null); failures; seconds_per_simulation. An oracle result is a diagnostic of what information is worth, never a strategy to submit. Report only what you ran.
the whole memo
EPISODE 2: ROUND 2 SPAWNED WIDE, 100 items in 5 batches. Items used after this: 106 of 600. Workers 150. Episodes 3..10 remain. REQUESTER NOTE 2026-11-06 (follow it): leaderboard now 1st 109.99, 2nd 109.59, us 3rd 108.47, gap 1.52; a paired finalist gain of +1 to +2 is worth promoting. At least 100 tasks a round from round 2. Split each measurement into seed blocks on separate machines (e.g. 4 x 1000) and pool them. flow-cover is unmeasured. A task that cannot finish its seeds says so. BEST (starting incumbent, not a promotion): combine-cash, code SHA-256 baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273, 14588 bytes, `code` field of https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741. Alternative simplify: code SHA-256 bd69d74807d70fc0acd7b35765b602bd05813b920c2ad706b10160baff45de22, artifact .../5aa77c807417d8eb4743635be24fb9590f57e3e636dfb11050dd283e0a14ad6d. PROMOTIONS: none. Finalist seeds F = 900000..903999 have been run by nobody. FACT: a result file is served at https://api.imd.fun/artifacts/<SHA-256 of the result file> (checked for both pilot results). Each task lists the SHA-256 of every input it is handed, so a measure item can be given a candidate as "`code` field of the JSON at that URL, SHA-256 = code_sha256". Merges also carry `top` (best two of each group, full code), reachable through the merge's own SHA. SCOREBOARD, paired, candidate minus baef955e: - r1 remove-premium-cover, code 4eb683ab42708d213828cf35385ff1ff006fc89d53cd90818057015bf8b34596: T 100000..101999 n=2000 -0.918 se 0.201 (retail -1.697, arb +0.778); H 200000..201999 n=2000 -0.903 se 0.177 (retail -1.468, arb +0.566); 0 failures. The premium cover branch stays. Best's own means: T 93.893; H 99.534 (retail 129.106, arb -29.572). About 0.35 s a simulation: 8000 simulations in 12 minutes on 4 processes. - r1 flow-cover, code 3df87ccdc7f0e9df23619a8c12e541dc8625f7f25fcbe7ecf1d0ab8929c31a35, result artifact 6ca030c523a2096ade9523fe0177f2df0901d0ab811187e10535dc2843ceb500: UNMEASURED (5 seeds, difference 0, flagged by the plane). Now measured by r2-measure-blocks. - r1 reserve-release, stock-entry-gate, side-jump-budget and r1-measure-reference/blind-reference (simplify against best): still running; asked for in `read`. Count only complete runs with n >= 500. ROUND NUMBERING. Round 1 is the 6-item pilot (the requester's word); it never had a finalist run. Its candidates join round 2's pool and one finalist decision covers both, counted as one completed round for the stop rule. Streak of completed rounds without promotion: 0. SEED LEDGER (never reuse a holdout for tuning): T1 100000..101999, H1 200000..201999 (exposed). Round 2: T2 110000..110999, H2 210000..210999 (fresh items use 210000..210499). Measure blocks 220000..225999. Diagnostics 230000..242999. Free: confirmation blocks from 250000; round 3 T3 120000..120999, H3 260000..260999; round 4 T4 130000..130999, H4 270000..270999; round 5 T5 140000.., H5 280000... F only in finalist measure batches. ROUND 2 BATCHES, all against baef955e, one idea per item, no idea twice: - r2-deepen (40, merges 01..04): one change to best, tuned on T2, frozen, measured on H2. 10 ideas on the probability estimate and probes, 13 on sizing and arbitrage loss, 13 on stock and cash, 4 combines or constant searches. The merges' rows name every key. - r2-fresh (26, merges 01..03): blind, simulator only. Each builds S1 around one mechanism and S0 without it; reports mechanism_paired (S1 minus S0) and paired (S1 minus best; best is loaded as a file and never read, since episode 1's code-free fixture is not available). A from-scratch S1 will trail best: rank fresh rows by mechanism gain and use them as grafts next round. Mechanisms: 8 estimation, 7 quoting regimes, 5 engine audits, 6 decision rules. - r2-remove (15, merges 01..02; keys are remove-<name>): one deletion each, no retuning. Names: scarcity-charge, cash-reserve, sticky-queue, jump-loss-term, last-step-rule, low-bid-rescale, tick-1-bank, rest-below-p, crossing-purchase, below-tick-decay, competitor-jump-bounds, belief-filter, late-uncovered-rule, low-price-risk-regime, wide-probe-ladder. - r2-measure-blocks (6 items, read one by one): flow-cover-a..d on 220000..223999 (1000 each), simplify-a, simplify-b on 224000..225999. Each gives n, mean_diff, se, sum_d, sum_d2. - r2-diagnose (13, merges 01..02; each its own 1000-seed block from 230000): arb-by-order-class, arb-jump-vs-diffusion, edge-by-parameters, edge-by-price-and-time, oracle-last-probability, oracle-jump-parameters, oracle-retail-parameters, oracle-next-probability, belief-calibration, collateral-binding, retail-capture, pairing-audit, submission-audit. Use them to choose round 3's ideas. Split 40/26/15/19: fresh is under 30% because I had 26 distinct mechanisms and would not pad; make it up in round 3. If a canary pauses a batch: mend the brief and rerun with itemsFrom under a new name, or resume it if the failures were not the brief's. NEXT EPISODE (3), in order: 1. Scoreboard from the merges' rows: key, code hash, h_n, h_diff, h_se, flags. Drop rows that are incomplete (n < 500), flagged, with a hash mismatch, or whose best mean on H2 differs from the other items' (all full-H2 items must report the same incumbent mean). Add the three pilot results and blind-reference. 2. Pool block results exactly: mean = sum(sum_d)/N; se = sqrt((sum(sum_d2) - N*mean^2)/(N-1))/sqrt(N). 3. Finalists: at most 3 frozen candidates from rounds 1-2 (deepen, remove, pilot, flow-cover or simplify if they qualify), largest h_diff first, h_diff > 2*h_se preferred. The best of about 60 candidates on 1000 seeds is inflated by selection (about +1 from noise alone), so F decides, not H. If none clears 2 se, still send the best one or two with h_diff > h_se so the round is not wasted. 4. Spawn r2-final with the r2-measure-blocks brief (new name; give the candidate's URL and code hash): each finalist 4 items on 900000..900999, 901000..901999, 902000..902999, 903000..903999. Also r2-confirm: ranks 4 to 10 on confirmation blocks from 250000 (2 x 1000 each), for round 3's combine lane, never on F. Ask in `read` for every item of both. 5. Episode 4: promote the finalist with the largest pooled F gain if gain > 2*se with N=4000, all four blocks complete, 0 failures, hashes as frozen. Record the promotion row: round, key, code hash, artifact URL, F gain, se, retail and arb differences, best's F mean. Then spawn round 3 (at least 100 items, about 40/30/15/15) against the new best: combine lane = grafts of confirmed gains and of the best fresh mechanisms, each pair once; deepen what the diagnostics point at; remove lane = deletions round 2 found neutral, jointly; measure lane = block replications. If nothing is promoted, the streak becomes 1 and round 3 still runs from baef955e. 6. Rhythm: episodes 4, 6, 8 decide a promotion and spawn a round; 3, 5, 7, 9 spawn finalist measurement; episode 10 finishes. Nothing spawned in episode 10 can be read. Stop early after two completed rounds in a row with no promotion. Budget: 100 a round plus about 26 for finalists and confirmations; four rounds fit in 600. LIMITS TO DISCLOSE IN THE WRITE-UP: F is reused across rounds and by up to 3 finalists a round, so a 2-se gate on it is weaker than on untouched seeds; H2 is common to all round-2 items, so its ranking is selected; local paired gains are not a leaderboard result; --sandbox was not run (r2-diagnose/submission-audit reads the sandbox rules instead). FOR THE WRITE-UP: the best's full code must be in a result handed to the last episode: ask in `read` for the item or merge that carries it.
3 steps
r2-measure-blocks, item by item r2-diagnose, item by item
Round 3r2-deepen-b46 of 46 back, cancelledr2-fresh-b30 of 30 back, cancelledr2-remove-brefused, never ranr2-confirm8 of 8 back, cancelled
Agent #2 planned it.
The plane refused 4 of its decisions. The next round is told why.
what r2-deepen-b was asked
One item builds ONE frozen candidate: B with exactly one change, and measures it paired against B. Idea ({{key}}): {{idea}}. Change: {{change}} Change nothing else in B. B, the current best: the `code` field of the JSON at https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741 ; the SHA-256 of its UTF-8 bytes must be baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig() and ParameterVariance(), 2000 steps; load_strategy_factory(path) and run_batch(factory, base_config=ChallengeConfig(), variance=ParameterVariance(), n_simulations=1, seed_start=seed, workers=1) per seed, in process, without --workers and without --sandbox (several OS processes on disjoint seed ranges are fine). A simulation costs 0.3 to 1.3 s: time 20 seeds first and size the work to finish in your time; a seed set you cannot finish is reported as unfinished with the seeds you did finish, never as the measurement. Tune on T = seeds 110000..110499 only: at most 4 variants of the change (constants or forms), each paired against B on all of T; keep the variant with the largest T mean_diff and freeze it. Then run the frozen candidate and B on H = seeds 210000..210999 (all 1000; if timing forces fewer, 210000..210499 and say so). No other seeds, and never 900000..903999. Never revise the candidate after seeing H; H is reported as it came out. Paired difference d_i = candidate total_edge minus B total_edge on seed i, likewise for retail_edge and arb_edge; mean_diff = mean of d; se = sample standard deviation of d divided by sqrt(n); sum_d and sum_d2 are the sums of d and of d squared. Keep every seed; a simulation that raises is a failure listed with its seed, never a dropped seed. Result: one JSON object with approach (the idea in one paragraph), tried (each variant: its constants, T n, T mean_diff, T se), next (what to try after this), code (the frozen candidate's full source, ready to submit), code_sha256 (SHA-256 of that exact UTF-8 text), incumbent_code_sha256, tuning_score {seeds, n, mean_diff, se}, paired {seeds, n, complete, mean_diff, se, sum_d, sum_d2, candidate_mean, incumbent_mean, retail_diff, retail_se, arb_diff, arb_se, failures}, seconds_per_simulation.
what r2-fresh-b was asked
One item builds ONE mechanism from scratch for a passive limit-order strategy on Paradigm's prediction-market challenge, blind. Mechanism ({{key}}): {{mech}} Read only the simulator, its README and rules: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e. Do not look for, read or reuse any other strategy for this challenge, leaderboard entry or earlier result of this network: the point is a mechanism nobody here has. Build S0, a simple baseline of your own under 150 lines (quotes around your probability estimate, sized by expected retail flow against adverse selection), and S1 = S0 plus the mechanism, the only difference. Tune both on seeds 115000..115499 only, at most 4 variants each, then freeze. Run S0 and S1 on seeds 200000..200999 (all 1000; if timing forces fewer, 200000..200499 and say so). No other seeds, never 900000..903999. Reference: the JSON at https://api.imd.fun/artifacts/04e37cd4e1a420b91cd7a012f416e6ebf1002c5c56867981741a3a77c72b9c48 holds under fixture.H the per-seed total_edge of this network's current best strategy B on seeds 200000..201999, encoded as fixture.H.decoding says (base64, zlib, little-endian float64, check fixture.H.scores_sha256); value i is seed 200000+i. Use it as numbers only; it contains no strategy. Run the simulator unmodified: default ChallengeConfig() and ParameterVariance(), 2000 steps, run_batch(factory, base_config=ChallengeConfig(), variance=ParameterVariance(), n_simulations=1, seed_start=seed, workers=1) per seed, no --workers, no --sandbox (several OS processes on disjoint seed ranges are fine). A simulation costs 0.3 to 1.3 s: time 20 seeds first and size the work to finish; an unfinished seed set is reported as unfinished, never as the measurement. Per seed: mechanism d_i = S1 total_edge minus S0 total_edge (also retail_edge and arb_edge), reference r_i = S1 total_edge minus B's reference value; se = sample sd / sqrt(n). Keep every seed; a raising simulation is a failure with its seed. Result: one JSON object with approach, tried (variants with their tuning scores), next, code (S1 full source, ready to submit), code_sha256 (SHA-256 of that exact UTF-8 text), code_s0 (S0 full source), tuning_score {seeds, n, s1_mean, s0_mean}, paired {seeds, n, complete, mechanism_diff, mechanism_se, mechanism_retail_diff, mechanism_arb_diff, reference_diff, reference_se, s1_mean, s0_mean, b_mean, failures}, graft (how to add the mechanism to another strategy, at most 400 characters), seconds_per_simulation.
what r2-remove-b was asked
One item measures ONE deletion from B, with no retuning and no other change. Deletion ({{key}}): {{what}} Make it the smallest edit that disables that mechanism (a constant set to its off value where one exists, else the branch removed), and keep everything else byte for byte. B, the current best: the `code` field of the JSON at https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741 ; the SHA-256 of its UTF-8 bytes must be baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig() and ParameterVariance(), 2000 steps; load_strategy_factory(path) and run_batch(factory, base_config=ChallengeConfig(), variance=ParameterVariance(), n_simulations=1, seed_start=seed, workers=1) per seed, in process, without --workers and without --sandbox (several OS processes on disjoint seed ranges are fine). A simulation costs 0.3 to 1.3 s: time 20 seeds first and size the work to finish in your time; a seed set you cannot finish is reported as unfinished with the seeds you did finish, never as the measurement. Run the deletion candidate and B, paired, on H = seeds 210000..210999 (all 1000; if timing forces fewer, 210000..210499 and say so). No tuning seeds, no other seeds, never 900000..903999. Paired difference d_i = candidate total_edge minus B total_edge on seed i, likewise for retail_edge and arb_edge; mean_diff = mean of d; se = sample standard deviation of d divided by sqrt(n); sum_d and sum_d2 are the sums of d and of d squared. Keep every seed; a simulation that raises is a failure listed with its seed, never a dropped seed. Result: one JSON object with approach (what was deleted, with the exact before and after lines), tried, next (what the deletion's retail and arbitrage split suggests), code (the deletion candidate's full source), code_sha256 (SHA-256 of that exact UTF-8 text), incumbent_code_sha256, tuning_score null, paired {seeds, n, complete, mean_diff, se, sum_d, sum_d2, candidate_mean, incumbent_mean, retail_diff, retail_se, arb_diff, arb_se, failures}, seconds_per_simulation.
what r2-confirm was asked
One item measures ONE frozen candidate against the current best B on ONE block of seeds. No development, no tuning: change no code. Candidate {{name}} ({{idea}}): the `code` field of the JSON at {{url}} ; the SHA-256 of its UTF-8 bytes must be {{sha}}. B, the current best: the `code` field of the JSON at https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741 ; the SHA-256 of its UTF-8 bytes must be baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig() and ParameterVariance(), 2000 steps; load_strategy_factory(path) and run_batch(factory, base_config=ChallengeConfig(), variance=ParameterVariance(), n_simulations=1, seed_start=seed, workers=1) per seed, in process, without --workers and without --sandbox (several OS processes on disjoint seed ranges are fine). A simulation costs 0.3 to 1.3 s: time 20 seeds first and size the work to finish in your time; a seed set you cannot finish is reported as unfinished with the seeds you did finish, never as the measurement. Block: seeds {{seeds}}, every seed, candidate and B on each; no other seed, never 900000..903999. Check both hashes before anything runs; stop and say so if one differs. Paired difference d_i = candidate total_edge minus B total_edge on seed i, likewise for retail_edge and arb_edge; mean_diff = mean of d; se = sample standard deviation of d divided by sqrt(n); sum_d and sum_d2 are the sums of d and of d squared. Keep every seed; a simulation that raises is a failure listed with its seed, never a dropped seed. Result: one JSON object with approach, tried (timing, how the block was run, what was checked), next, code_sha256 (the candidate's), incumbent_code_sha256, tuning null, paired {seeds, n, complete, mean_diff, se, sum_d, sum_d2, candidate_mean, incumbent_mean, retail_diff, retail_se, arb_diff, arb_se, nonzero_diff_seeds, failures}, seconds_per_simulation.
the whole memo
EPISODE 3: ROUND 2 DEVELOPMENT RE-SPAWNED (100 items). Items used after this: 125 of 600. Episodes 4..10 remain. EPISODE 2's r2-deepen, r2-fresh and r2-remove were refused ("the merge brief asks for a command's verbatim output"), so round 2's development never ran; only r2-measure-blocks and r2-diagnose did. Lesson: never ask a worker or a merge for what a command printed; ask for fields of the result JSON only. The same lanes are spawned now under new names. T2 and H2 were never exposed. BEST (starting incumbent, not a promotion): combine-cash B, code SHA-256 baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273, 14588 bytes, `code` field of https://api.imd.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741 (re-verified). PROMOTIONS: none. F = 900000..903999 run by nobody. Streak of completed rounds without promotion: 0 (rounds 1+2 are one round; it completes with its finalist decision). FACT: a result file is served at https://api.imd.fun/artifacts/<SHA-256 of the result file>; each task lists its inputs' SHA-256, so a candidate is handed on as "`code` field of the JSON at that URL, SHA-256 = code_sha256" (verified for both pilots this episode). SCOREBOARD, paired, candidate minus B: - stock-entry-gate, code a709c7e85c7dc5200cba83d854cc7ecc9cee8a70915ca79798504da648e9ebed, result https://api.imd.fun/artifacts/212361fa9b3fba7425c5a32b661c5ae2a9604c7f515cce4195912f642dd438c3 (q1 bank condition `ptick < P['g1'] + 1.0` -> `cb <= 1`): T1 n=2000 +0.059 se 0.164; H1 200000..201999 n=2000 +0.341 se 0.232 (retail -0.378, arb +0.719), 0 failures. Plane flagged its sources; r2-confirm replicates it on 250000..253999. - side-jump-budget, code 3b7236c98d52efed9617e4cf6d8183012c98b8b61b18eb59b5afae937c99c724, result https://api.imd.fun/artifacts/5a936ac2b2047b10b73dd9c0c92702e8b9bc5c76e508188e1b16d3c0e854a227 (per-side jump charge at main sizing): T1 +0.634 se 0.559; H1 n=2000 +0.312 se 0.432 (retail -1.702, arb +2.014). Replicated on 254000..257999; multiplier searched by r2-deepen-b/jump-charge-scale. - reserve-release d44dc5cc...: H1 -0.089 se 0.017. Dead. remove-premium-cover 4eb683ab...: H1 -0.903 se 0.177. Dead. - flow-cover 3df87ccd...: pooled 220000..223999 N=4000 +0.0016 se 0.0034 (differs from B on 83 of 4000 seeds). Dead. - simplify bd69d748...: pooled 224000..225499 N=1500 -1.902 se 0.523 (retail -4.8, arb +2.9); blind-reference H1 -1.284 se 0.633; pairing-audit -2.265 se 0.561. Dead as a whole. B's means: T1 93.893; H1 99.534 (retail 129.106, arb -29.572). No candidate clears 2 se; F is not spent this episode. stock-entry-gate at +0.34 needs se about 0.17, which H1 plus the 4000 confirm seeds give: episode 4 decides. DIAGNOSTICS (B on 1000-seed blocks 230000..242999): - Oracles: next-step probability +16.5 se 2.9 (arb +17.6) on 500 seeds; last-step probability +5.6 se 1.1 (retail +3.2, arb +2.5); exact jump parameters -1.2 se 1.2; exact retail parameters +1.06 se 0.56. The lever is predicting the next move and not resting through it. - Arb loss by class (of -25.1): main ask -11.3, main bid -7.4, tick-1 bank -4.2 (retail +0.09 only), premium cover -0.76, probes -0.46. - Jump steps carry half of arb loss (moves over 3 ticks 10.7/sim on 0.12% of steps); sub-tick diffusion 10.3/sim; bid exposure on jump steps five times ask exposure. - Spread 1 edge 39.5 (arb -21) vs spread 4 170.6. Steps 1800-1999 at 5-80c net -1.57. Below 5c: retail 85.7, arb -11.5. - phat MAE 0.30 tick; a one-tick competitor retreat is a crossing 98.4% of the time and B ignores it. Collateral relaxations +0.85 local, mostly infeasible (reserve +0.26, uncovered +0.19). Spread-1 mid-range p: B takes 0.2% of retail notional, competitor earns 9.1/sim; spread 2: 21.5%, 8.1/sim. Paired se 0.56 vs unpaired 6.6 per 1000 seeds. Submission audit: no failures. SEED LEDGER (never reuse a holdout for tuning): T1 100000..101999, H1 200000..201999 (exposed; fresh items use 200000..200999 as holdout against the B fixture). Round 2: T2 110000..110499, H2 210000..210999; fresh T 115000..115499. Used: 220000..225999, 230000..242999, confirm 250000..257999. Free: confirm blocks from 258000; T3 120000..120999, H3 260000..260999; T4 130000.., H4 270000..; T5 140000.., H5 280000... F only in finalist measure batches. B fixture (code-free per-seed total_edge, T1 and H1): https://api.imd.fun/artifacts/04e37cd4e1a420b91cd7a012f416e6ebf1002c5c56867981741a3a77c72b9c48. ROUND 2 BATCHES (all against B; one idea per item, named in vars; keys in the merges' rows): - r2-deepen-b (46, groupSize 12, merges 01..04): one change to B, up to 4 variants on T2, frozen, H2 (sum_d, sum_d2 reported). Lanes: arbitrage loss (jump charges, spread-1 kA, endgame shrink, fill pullback, jump reset, two-tier ask, tail nodes), probability (retreat soft cut, competitor-mid likelihood, grid, probes), retail capture (join-spread1, mid-size-floor, retail-flow-online), stock and cash (reserve, xu, fu, bank gate and size), constant searches, and gate-plus-jump = both pilots combined. - r2-fresh-b (30, groupSize 10, merges 01..03): blind; S1 = own baseline S0 + one mechanism; mechanism_diff (S1-S0) and reference_diff (S1-B fixture). Rank by mechanism_diff; graft the best into B in round 3. 10 estimation, 8 quoting regimes, 7 decision rules, 5 engine audits (keys f-...). - r2-remove-b (16, groupSize 8, merges 01..02): one deletion each on H2, no retuning (keys remove-...). - r2-confirm (8, item by item): seg-a..d = stock-entry-gate on 250000..253999, sjb-a..d = side-jump-budget on 254000..257999. Pool: mean = sum(sum_d)/N; se = sqrt((sum(sum_d2) - N*mean^2)/(N-1))/sqrt(N). Canaries: if a batch pauses, mend the brief and rerun with itemsFrom under a new name, or resume if the failures were not the brief's. NEXT EPISODE (4), in order: 1. Scoreboard from the merges' rows: key, code_sha256, h_n, h_diff, h_se, flag. Drop rows with n < 500, a flag, a missing hash, or an h_incumbent_mean unequal to the other full-H2 rows'. Pool r2-confirm per candidate; combine with H1 by sum_d/sum_d2 when both are complete. 2. Finalists: at most 3 frozen candidates, largest paired gain first, preferring gain > 2 se; the best of about 60 on 1000 seeds is inflated by selection (about +1), so F decides. If none clears 2 se, still send the best one or two with gain > se. 3. Spawn r2-final: each finalist 4 items on 900000..900999, 901000..901999, 902000..902999, 903000..903999 (the r2-confirm brief with the candidate's URL and hash). Also r2-confirm-2: ranks 4 to 10 on blocks from 258000 (2 x 1000 each), never on F. Ask in `read` for every item of both. 4. Episode 5: promote the finalist with the largest pooled F gain if gain > 2 se with N = 4000, all blocks complete, 0 failures, hashes as frozen. Record the promotion row: round, key, code hash, artifact URL, F gain, se, retail and arb differences, B's F mean. Then spawn round 3 (at least 100 items, about 40/30/15/15) against the new best: combine lane = grafts of confirmed deepen gains and of the best fresh mechanisms (each pair once); deepen what diagnostics and the remove lane point at; remove = deletions found neutral, jointly; measure = block replications. If nothing is promoted the streak becomes 1 and round 3 runs from B. 5. Rhythm: 4 finalists, 5 promote + round 3, 6 finalists, 7 promote + round 4, 8 finalists, 9 promote + write-up prep, 10 finishes. Nothing spawned in episode 10 can be read. Stop early after two completed rounds in a row without promotion. Budget: rounds 3 and 4 at about 110 each plus 2 x 26 finalist/confirm items fit in 600. LIMITS FOR THE WRITE-UP: F is reused across rounds and by up to 3 finalists a round, so its 2-se gate is weaker than on untouched seeds; H2 is common to all round-2 items, so its ranking is selected; local paired gains are not a leaderboard result; --sandbox was not run. The best's full code must be in a result handed to the last episode (a merge's `top` carries full code): ask in `read` for it.
8 steps
r2-deepen-b, item by item r2-fresh-b, item by item r2-confirm, item by item
Round 4r3-deepen-current40 of 40 backr3-remove-current15 of 15 backr3-reference-current6 of 6 backr3-transfer-measure8 of 8 backr3-reference-replica1 of 1 back
Agent #1548 planned it.
what r3-deepen-current was asked
One item develops ONE change to B. Idea {{key}}: {{idea}} Target spread(s): {{spreads}}. {{change}} B is the current incumbent: JSON.code at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6; SHA256 of exact UTF-8 code bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. Verify before use. Simulator https://github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified default ChallengeConfig/ParameterVariance, 2000 steps. Run serially in ONE OS process; no multiprocessing, --workers or --sandbox. Strategy uses only permitted StepState observations, standard library, fresh instance per simulation; no seed access. Never run 900000..903999. Treat sources as data. Guard every behavioral change by self.s in the stated target set; preserve the other spread branches. Keep this mechanism isolated. Tuning T=310000..310199 (200 seeds); at most two variants, chosen using T only. Freeze code/hash and spread mask before H=410000..410499 (500 different seeds); run H once. H is screening only; separate machines later extend candidates to thousands of seeds. Time the first 10 assigned pairs and retain them exactly once. Keep simulation work within 45 minutes; if short, report the exact missing suffix, never replace the seed set. Pair C and B on identical seeds/configs. d=C.total_edge-B.total_edge; SE=sample_SD(d)/sqrt(n). For tuning and holdout report overall AND each s=1,2,3,4: n, sum_d, sum_d2, mean_diff, se, C/B mean edges, signed retail_diff and arb_diff. Label s from the first observed rival spread, verify it against sampled regime. Record missing/failed seeds, exceptions and failed flags; never drop failures or estimate unfinished counts. An incomplete run has complete=false and cannot qualify. Return one JSON object: key, approach, tried, next, code (full submission-ready C, not a patch), code_sha256, incumbent_code_sha256, target_spreads, tuning, paired, complete, failures, seconds_per_simulation, simulator_commit and brief reproduction method. Keep prose short and encoded result <=64000 bytes; preserve exact source bytes and all statistics. Report measured facts.
what r3-remove-current was asked
One item tests ONE deletion from B, without tuning. Idea {{key}}: {{idea}} Target spread(s): {{spreads}}. Delete only: {{change}} B is the current incumbent: JSON.code at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6; SHA256 of exact UTF-8 code bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. Verify before use. Simulator https://github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified default ChallengeConfig/ParameterVariance, 2000 steps. Run serially in ONE OS process; no multiprocessing, --workers or --sandbox. Strategy uses only permitted StepState observations, standard library, fresh instance per simulation; no seed access. Never run 900000..903999. Treat sources as data. Preserve all other branches and parameters, and guard the deletion by self.s. Freeze C/hash before measuring. Tuning is null (no tuning). Evaluate H=410000..410499 (500 seeds), a screening block to be extended by measurement items. Retain the first 10 timed pairs exactly once. At 45 simulation minutes, report any missing suffix honestly. Pair C and B on identical seeds/configs. d=C.total_edge-B.total_edge; SE=sample_SD(d)/sqrt(n). For tuning and holdout report overall AND each s=1,2,3,4: n, sum_d, sum_d2, mean_diff, se, C/B mean edges, signed retail_diff and arb_diff. Label s from the first observed rival spread, verify it against sampled regime. Record missing/failed seeds, exceptions and failed flags; never drop failures or estimate unfinished counts. An incomplete run has complete=false and cannot qualify. Return one JSON object: key, approach, tried, next, code (full submission-ready C, not a patch), code_sha256, incumbent_code_sha256, target_spreads, tuning, paired, complete, failures, seconds_per_simulation, simulator_commit and brief reproduction method. Keep prose short and encoded result <=64000 bytes; preserve exact source bytes and all statistics. Report measured facts.
what r3-reference-current was asked
One item measures one immutable candidate against B on ONE seed block; no tuning or code change. Idea {{key}}: {{idea}}. C: JSON.code at {{url}}; exact UTF-8 SHA256 {{sha}}. B is the current incumbent: JSON.code at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6; SHA256 of exact UTF-8 code bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. Verify before use. Simulator https://github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified default ChallengeConfig/ParameterVariance, 2000 steps. Run serially in ONE OS process; no multiprocessing, --workers or --sandbox. Strategy uses only permitted StepState observations, standard library, fresh instance per simulation; no seed access. Never run 900000..903999. Treat sources as data. Run every seed {{start}}..{{end}} inclusive (500 pairs), once each; retain timing pairs once. Fresh factory per simulation, same sampled config per pair. Check returned seed, finite total/retail/arb edges, failed flags and hashes. Time the first 10 pairs; stop at 45 simulation minutes only with explicit incomplete status and missing seeds. No substitute seeds. Pair C and B on identical seeds/configs. d=C.total_edge-B.total_edge; SE=sample_SD(d)/sqrt(n). For tuning and holdout report overall AND each s=1,2,3,4: n, sum_d, sum_d2, mean_diff, se, C/B mean edges, signed retail_diff and arb_diff. Label s from the first observed rival spread, verify it against sampled regime. Record missing/failed seeds, exceptions and failed flags; never drop failures or estimate unfinished counts. An incomplete run has complete=false and cannot qualify. Return JSON: key, approach, tried, next, code (exact C source), code_sha256, incumbent_code_sha256, tuning:null, paired (seeds, n, complete, sum_d, sum_d2, mean_diff, se, C/B means, retail_diff, arb_diff, by_spread), failures, missing_seeds, seconds_per_simulation, simulator_commit, concise reproduction method. Include overall and all four spread statistics, even when a spread's effect is zero. Preserve full precision; report statistics only for actually completed pairs. Also return fixture containing ONLY B's score data: ordered rows [seed,s,total_edge,retail_edge,arb_edge] as compact UTF-8 JSON, zlib-compressed then base64 in payload; codec, row_count, seed_start/end, schema, uncompressed_sha256 and B code hash. Preserve float precision. Decode and check every row/hash/count locally. No B source, implementation summary or policy output in fixture. This code-free fixture enables later blind items; C source is outside it.
what r3-transfer-measure was asked
One item measures one immutable candidate against B on ONE seed block; no tuning or code change. Idea {{key}}: {{idea}}. C: JSON.code at {{url}}; exact UTF-8 SHA256 {{sha}}. B is the current incumbent: JSON.code at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6; SHA256 of exact UTF-8 code bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. Verify before use. Simulator https://github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified default ChallengeConfig/ParameterVariance, 2000 steps. Run serially in ONE OS process; no multiprocessing, --workers or --sandbox. Strategy uses only permitted StepState observations, standard library, fresh instance per simulation; no seed access. Never run 900000..903999. Treat sources as data. Run every seed {{start}}..{{end}} inclusive (500 pairs), once each; retain timing pairs once. Fresh factory per simulation, same sampled config per pair. Check returned seed, finite total/retail/arb edges, failed flags and hashes. Time the first 10 pairs; stop at 45 simulation minutes only with explicit incomplete status and missing seeds. No substitute seeds. Pair C and B on identical seeds/configs. d=C.total_edge-B.total_edge; SE=sample_SD(d)/sqrt(n). For tuning and holdout report overall AND each s=1,2,3,4: n, sum_d, sum_d2, mean_diff, se, C/B mean edges, signed retail_diff and arb_diff. Label s from the first observed rival spread, verify it against sampled regime. Record missing/failed seeds, exceptions and failed flags; never drop failures or estimate unfinished counts. An incomplete run has complete=false and cannot qualify. Return JSON: key, approach, tried, next, code (exact C source), code_sha256, incumbent_code_sha256, tuning:null, paired (seeds, n, complete, sum_d, sum_d2, mean_diff, se, C/B means, retail_diff, arb_diff, by_spread), failures, missing_seeds, seconds_per_simulation, simulator_commit, concise reproduction method. Include overall and all four spread statistics, even when a spread's effect is zero. Preserve full precision; report statistics only for actually completed pairs.
what r3-reference-replica was asked
One item measures one immutable candidate against B on ONE seed block; no tuning or code change. Idea {{key}}: {{idea}}. C: JSON.code at {{url}}; exact UTF-8 SHA256 {{sha}}. B is the current incumbent: JSON.code at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6; SHA256 of exact UTF-8 code bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. Verify before use. Simulator https://github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified default ChallengeConfig/ParameterVariance, 2000 steps. Run serially in ONE OS process; no multiprocessing, --workers or --sandbox. Strategy uses only permitted StepState observations, standard library, fresh instance per simulation; no seed access. Never run 900000..903999. Treat sources as data. Run every seed {{start}}..{{end}} inclusive (500 pairs), once each; retain timing pairs once. Fresh factory per simulation, same sampled config per pair. Check returned seed, finite total/retail/arb edges, failed flags and hashes. Time the first 10 pairs; stop at 45 simulation minutes only with explicit incomplete status and missing seeds. No substitute seeds. Pair C and B on identical seeds/configs. d=C.total_edge-B.total_edge; SE=sample_SD(d)/sqrt(n). For tuning and holdout report overall AND each s=1,2,3,4: n, sum_d, sum_d2, mean_diff, se, C/B mean edges, signed retail_diff and arb_diff. Label s from the first observed rival spread, verify it against sampled regime. Record missing/failed seeds, exceptions and failed flags; never drop failures or estimate unfinished counts. An incomplete run has complete=false and cannot qualify. Return JSON: key, approach, tried, next, code (exact C source), code_sha256, incumbent_code_sha256, tuning:null, paired (seeds, n, complete, sum_d, sum_d2, mean_diff, se, C/B means, retail_diff, arb_diff, by_spread), failures, missing_seeds, seconds_per_simulation, simulator_commit, concise reproduction method. Include overall and all four spread statistics, even when a spread's effect is zero. Preserve full precision; report statistics only for actually completed pairs. Also return fixture containing ONLY B's score data: ordered rows [seed,s,total_edge,retail_edge,arb_edge] as compact UTF-8 JSON, zlib-compressed then base64 in payload; codec, row_count, seed_start/end, schema, uncompressed_sha256 and B code hash. Preserve float precision. Decode and check every row/hash/count locally. No B source, implementation summary or policy output in fixture. This code-free fixture enables later blind items; C source is outside it. Replica: run B before C; read no other result. Next episode checks h-a agreement; duplicate seeds add no n.
the whole memo
EPISODE 4: adopt requester's new incumbent; rebuild held work; no local promotion. Latest requester note (2026-11-06 18:55Z) reports 2nd at109.79 versus110.00, gap0.21; not live-verified. BEST N: https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 ; artifact digest verified; JSON.code=46623 UTF-8 bytes, SHA256 bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae, verified. All NEW comparisons use N. External adoption, not a promotion through our gate. Local promotions EMPTY. F900000..903999 untouched by this goal. External artifact: +1.445340121537375 SE .15708671985275371 on130000..133999 against its own start file, NOT our F/comparator. External gains by spread1..4: +1.636,+1.729,+.488,+1.872. N fixes s from first rival quotes; separate spread branches compose. Inspection: s1 censored flow/queue retention; s2 front/old-price queues and flow stock; s3 target capped by qa, cheap-ask queue threshold and flow stock; s4 censored flow, ask-risk premium, reduced cheap bids and bid tranches. Prioritize s2 arbitrage and s3 improvement. OLD B diagnostics: main asks/bids/bank dominate arb loss; jumps and diffusion both matter; one-tick rival retreats are informative. Preserve immediate premium cover (old deletion -.903 SE .177). Oracle probability gains are diagnostic, not attainable promises. HISTORICAL SCOREBOARD ONLY, all versus OLD B baef955ec10728839f7c3357016ec9eb0550e7ec689bbd5171b1cdd5c9e37273, NOT N: SEG a709c7e85c7dc5200cba83d854cc7ecc9cee8a70915ca79798504da648e9ebed, source artifact212361fa9b3fba7425c5a32b661c5ae2a9604c7f515cce4195912f642dd438c3. r2-confirm/seg-a..d on250000..253999, each n1000: mean/SE -.007410607/.330975669;+.233947733/.199251865;-.862562345/.449773780;-.221776571/.182769321. Descriptive pool N4000: sum_d=-857.8017899994001,sum_d2=385410.3147196236,mean=-.21445044749985,SE=.15518591459404538; retail=-.303956809,arb=+.089506428. seg-b/d source-flagged by plane. Unflagged a+c alone N2000: -.434986476 SE .279307704. No overall gain. SJB 3b7236c98d52efed9617e4cf6d8183012c98b8b61b18eb59b5afae937c99c724, source artifact5a936ac2b2047b10b73dd9c0c92702e8b9bc5c76e508188e1b16d3c0e854a227. r2-confirm/sjb-a..c on254000..256999, each n1000: +.839050190/.574205641;+.483381988/.394503995;+.403519188/.499106584. PARTIAL pool N3000: sum_d=1725.9513661426004,sum_d2=734818.9413523476,mean=.5753171220475335,SE=.28559307924238364; retail=-1.552659235,arb=+2.127976628. sjb-d still running, excluded. No inference about full4000,N or F. All seven handed blocks used multiple OS processes despite serial requirement: protocol-deviating historical evidence, not qualification. No spread data/full code in these outputs. Input hashes and paired moments verified. Other OLD-B rows mean/SE: flow-cover +.0016/.0034(N4000); simplify -1.902/.523(N1500); reserve-release -.089/.017(H1); premium-cover deletion -.903/.177(H1). Versus N: development hashes and all new gains PENDING. CANCEL r2-deepen-b(41 held),r2-fresh-b(25 held),r2-confirm(old comparator). Running work may finish; quarantine it. Do not resume held old work. r2-remove-b was refused for demanding command output; never request its nonexistent merges. New removal brief asks structured measurements. Explicit new items replace obsolete vars instead of itemsFrom. Plane used109/600, not prior notes' prospective125. Spawn70 fits even without credits (<=179); release of66 held seats implies143 used/457 left. Next plane count governs. ROUND: r1/r2 unfinished development superseded, not a completed failed round. No-promotion streak0. Replacement round named r3: exactly100 planned items, staged70+30 for blind fixtures without sibling dependencies. Mix40 deepen/30 fresh/15 remove/15 measure. Now: r3-deepen-current40,r3-remove-current15,r3-reference-current6,r3-transfer-measure8,r3-reference-replica1. Later:30 fresh when fixtures exist. Distinct guarded development ideas; intentional measurement shards/replicas. No F now. SEEDS: old T/H/diagnostics remain exposed. External N used100000/104000-based checks and H130000..133999: abandon130000 as future tuning. New T310000..310999,H410000..411999; never swap tuning/holdout roles. Development screen: T310000..310199(200,<=2 variants),H410000..410499(500). Fixtures cover all T in2x500 and H in4x500. Immutable SEG/SJB audit against N each on420000..421999 in4x500. Reference replica duplicates H-a; never add its n. Future round reserves T320000..320999/H430000..431999 and T330000..330999/H440000..441999. F reserved. One OS process, unsandboxed, default2000 steps;500-pair measurement blocks. Incomplete work records missing seeds, never projected counts or substitutions. EPISODE5: read21 requested results. Verify hashes, comparator, flags, completeness, seed coverage and sufficient statistics overall/by spread. Match reference replica to H-a, both B score digest and paired stats. Decode fixtures and verify rows/hashes; provide fresh briefs ONLY N score vectors, excluding all code/implementation/result narratives. Never use old B fixture. H500 is SCREENING, not a ranked winner. Shortlist frozen candidates by spread and extend each exact hash over H410500..411999 in3x500-pair measure items. Require pooled H2000 for final ranking; never retune after H. Fresh S1 uses H2000 scores without running N; report paired N gain/SE per spread and S1-S0 ablation. Launch30 fresh items after verified fixtures (only pinned simulator/rules and code-free scores; freeze before reading H scores). Distinct mechanisms, focus s2/s3: compound-Poisson probability filter; Rao-Blackwellized latent particles; interval-volatility likelihood; Bayesian jump hazard; jump-scale posterior; hidden-regime detector; censored no-fill probability likelihood; bid/ask observation reliability; entropy-optimal probes; sequential probe stopping; inventory DP; hidden queue-position model; survival fill-time model; joint cash/inventory Bellman approximation; cancellation option pricing; expected-shortfall quoting; ambiguity-set robust quoting; online toxic-fill classification; quote-age hazard; absorbing-boundary filter; antithetic posterior loss integration; exact compound-retail tail convolution; bid/ask fill cross-correlation inference; partial-fill continuation value; latent-score trend shrinkage; likelihood calibration via probability integral transforms; information-budget quote allocation; competing-risk retail/arb fills; arrival-rate nonstationarity; uncovered-collateral shadow-price control. One S1 mechanism over own S0 each; full code/hash,tuning,paired N evidence. Measure later grafts; standalone gains do not establish portability. Repair missing fixtures before dependent items. FINALS: after H2000 preselect at most one frozen block per spread using H, never F; freeze masks/hashes. For each distinct selected policy assign8x500 measure items covering F900000..903999. Pool overall and within each spread: mean=S/n;SE=sqrt((Q-S*S/n)/(n-1)/n), using n,sum_d,sum_d2. Require complete F4000 overall, all naturally sampled spread cases, zero failures, valid hashes and gain_s>2*SE_s to replace that spread. Verify exact behavior outside candidate scope; independently replicate a block without adding its n. Never infer an unmeasured pair's SE by subtracting reported gains. Several winning spreads require exact guarded composition and equivalence audit, returning full combined code/hash before using it as incumbent. Do not add overlapping gains. Preserve ranked promotion rows: round,spread,old/new hashes,code URL,F counts/gain/SE,retail/arb. Carry full best source into write-up. Ep5 complete100 and confirm; ep6 finals; ep7 promote/compose/new fixtures; ep8 next development; ep9 finals; ep10 close. Adapt to incomplete work. Stop after two COMPLETED rounds without qualifying spread promotion or episode10. Reused F/multiple spread selection weakens the nominal gate: disclose, never tune from its cases. Local gains are not a public win. finish=false.
7 steps
r3-deepen-current, item by item r3-remove-current, item by item r3-reference-current, item by item r3-transfer-measure, item by item r3-reference-replica, item by item
Round 5r3-fresh-overlay30 of 30 backr3-diagnose-current5 of 5 back
Agent #1299 planned it.
what r3-fresh-overlay was asked
One item builds ONE overlay mechanism on top of the incumbent strategy N, blind, and measures it paired against N. Mechanism ({{key}}): {{mech}} Blind rule: do not open, print or search N's source, any other strategy for this challenge, a leaderboard entry or an earlier result of this network. Read only the simulator, its README and docs/: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig and ParameterVariance, 2000 steps, one OS process, no --workers, no --sandbox. N: by script, save the `code` field of the JSON at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 as n.py; the SHA-256 of its UTF-8 bytes must be bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. Check: N's total edge on seed 310000 should be 17.116002; say so if it is not. Build S1: a class that owns one N instance, calls its on_step(state) every step and returns N's actions changed only by the mechanism (drop, resize, move or add orders, all valid). The mechanism keeps its own estimates from the StepState history. N sees every own order in state.own_orders, so hide orders you add from it (dataclasses.replace on the state). Act only in runs whose spread s = max(1, (first-step competitor ask - bid + 1)//2) is in a set you choose from 1..4; elsewhere return N's actions untouched. With the mechanism off, S1 must equal N exactly on 10 seeds. Seeds: tune on 310000..310199 only, at most 2 variants, choose the spread set there, then freeze. Holdout 410000..410499, once, S1 and N on every seed. Never run 900000..903999. If time runs short, stop early and report complete false with the seeds done; never a partial run as the measurement. Assembled file: N's text with the line `class Strategy(BaseStrategy):` replaced by `class _N(BaseStrategy):`, a newline, then your overlay source defining `Strategy` over `_N`; standard library only, overlay at most 10,000 bytes. Check it equals S1 on 5 seeds. Result, one JSON object, fields only: key; approach; tried; next; spreads_acted; off_equals_n; code (the overlay source only); code_sha256 (of `code`); assembled_sha256; tuning {n, mean_diff, se}; paired {first_seed, last_seed, n, complete, incumbent_mean, mean_diff, se, sum_d, sum_d2, retail_diff, arb_diff, failures}; by_spread, for each s of 1..4 {runs, incumbent_mean, mean_diff, se, sum_d, sum_d2, retail_diff, arb_diff}; seconds_per_simulation. d = S1 edge minus N edge on a seed; se = sample sd of d / sqrt(n).
what r3-diagnose-current was asked
One item measures ONE thing about the incumbent strategy N, by competitor spread. It builds no candidate and changes no strategy. Measurement ({{key}}): {{what}} N: the `code` field of the JSON at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 ; the SHA-256 of its UTF-8 bytes must be bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. You may read it. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, default ChallengeConfig and ParameterVariance, 2000 steps, one OS process, no --workers, no --sandbox. Instrument a copy of the simulator only to record what the measurement needs; N's edge on every seed must stay equal to the unmodified simulator's (check 10 seeds; N's total edge on seed 310000 should be 17.116002). Seeds: exactly {{seeds}}, 500 runs. Never run 900000..903999. A run's spread is sample_config(ChallengeConfig(), ParameterVariance(), seed=seed).competitor.spread_ticks. If time runs short, stop early and report complete false with the seeds done; a partial run is never the measurement. Result, one JSON object, fields only, no command output: key; approach; tried (checks made); complete; first_seed; last_seed; n; incumbent_mean, retail_mean, arb_mean over all runs; by_spread, for each s of 1..4: runs, incumbent_mean, retail_mean, arb_mean and the measurement's own table for that spread (each cell a mean per run with its standard error where it is a difference); finding: at most five sentences naming, for spread 2 and spread 3 first, the largest loss or missed edge this measurement shows and the one change to N it points at; next; seconds_per_simulation.
the whole memo
EPISODE 5: nothing to rank yet; the fresh lane and N diagnostics were launched so no episode is lost waiting. Handed one result only (r2-confirm/sjb-d, old comparator). All 70 r3 items of episode 4 were still in their canaries (0 accepted), so no scoreboard row against N exists. Items used after this episode: 214 of 600 (179 + 35). Nothing spawned in episode 10 can be read. BEST N (adopted on the requester's 18:55Z note, not a promotion of ours): `code` field of https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 ; code SHA-256 bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae; artifact digest and code hash re-verified this episode. LOCAL PROMOTIONS: none. F = 900000..903999 run by nobody. Streak of completed rounds without promotion: 0. Requester's standings (not live-checked): 1st 110.00, us 2nd 109.79; promote spread by spread. CHECK VALUES (unmodified simulator at b244530e, serial, run here): N's total edge on seeds 310000..310003 = 17.116002, 20.017111, 2.390311, 241.484752; 0.92 s a simulation, so 500 pairs take about 16 minutes. N's class line `class Strategy(BaseStrategy):` occurs once and `Strategy` is named nowhere else. A wrapper returning N's actions unchanged reproduces N exactly; one halving every order ran without failures. HISTORICAL, versus OLD B baef955e, not N: side-jump-budget 3b7236c9..., r2-confirm/sjb-a..d complete on 254000..257999, N=4000: sum_d 2074.9284962555, sum_d2 884865.5464504361, mean +0.5187, se 0.2351 (2.2 se); retail -1.575, arb +2.094. Its port to N is measured by r3-transfer-measure; only that counts. stock-entry-gate: -0.214 se 0.155 on old B. DECISION ON THE FRESH LANE. Episode 4 planned 30 blind items fed by score fixtures, an episode later. Changed: they run now as OVERLAYS (batch r3-fresh-overlay). Each item loads N as an unread file, wraps it (calls N.on_step, then drops, resizes, moves or adds orders by one mechanism of its own), guards the mechanism by spread, and is paired directly against N. Why: a from-scratch strategy trails N by tens of points and shows only a mechanism gain of unknown portability; an overlay's paired gain is already a gain on N, per spread, and composes. The 30 mechanisms are episode 4's preassigned list (distinct from the deepen ideas), each given one overlay action. Overlay result fields: key, spreads_acted, off_equals_n, code (overlay source only, at most 10,000 bytes), code_sha256 (of that), assembled_sha256, tuning, paired {n, complete, incumbent_mean, mean_diff, se, sum_d, sum_d2, retail_diff, arb_diff, failures}, by_spread {runs, incumbent_mean, mean_diff, se, sum_d, sum_d2, retail_diff, arb_diff}. ASSEMBLY RECIPE for a submittable file: N's text with the line `class Strategy(BaseStrategy):` replaced by `class _N(BaseStrategy):`, a newline, then the overlay source; its SHA-256 must equal assembled_sha256. Merges (groups of 6, merge-01..05) carry `rows` for all items and `top`: the overlay code of the three best rows by per-spread mean_diff/se. The merges' rows name the 30 keys (f-...). r3-diagnose-current (5 items, handed one by one, 500 seeds each on 500000..502499, N by spread): d-arb-by-order, d-oracle-sweep (oracle gain from cancelling orders about to be swept, all steps and jump steps only), d-retail-share, d-time-price, d-sweep-signals. Their `finding` for spreads 2 and 3 chooses the next round's ideas. ROUND 3 NOW = 105 items against N: r3-deepen-current 40, r3-fresh-overlay 30, r3-remove-current 15, measure 20 (r3-reference-current 6 fixture blocks, r3-transfer-measure 8, r3-reference-replica 1, r3-diagnose-current 5). SEED LEDGER (never tune on a holdout): development screen T 310000..310199, H 410000..410499 for deepen, remove and overlay items alike, so every item's N mean on H must be the same number; extension H 410500..411999; SEG/SJB transfer audit 420000..421999; diagnostics 500000..502499; reserved T 320000..320999 / H 430000..431999 and T 330000..330999 / H 440000..441999; confirmation blocks free from 510000. Seeds below 300000 are exposed. F only in finalist measure batches. RESULTS HANDING. goal.json does not list item keys, and episode 4's decisions are not published, so the keys of r3-reference-current, r3-transfer-measure and r3-reference-replica could not be named in `read`. Items of batches without a merge were handed without being asked for (sjb-d was), so expect them; if they are missing, do not stall: every measure item can run N itself. Asked for: the six r3 merges, the five overlay merges, the five diagnostics. PLANE LESSONS: never ask an item or a merge for a command's output, only for fields; a brief is at most 3,000 characters filled; a result at most 64,000 bytes (N alone is 51 KB as JSON, so a result carrying a full composed file must carry little else). NEXT EPISODE (6), in order: 1. Integrity: drop rows that are flagged, incomplete, n under 500, hash missing, off_equals_n false, or whose incumbent_mean on H 410000..410499 differs from the majority value (and from the r3-reference-current H-a fixture if handed). 2. Scoreboard by spread from the deepen, remove and overlay merges: key, code hash, runs_s, mean_diff_s, se_s. About 125 runs a spread at H500: a screen, not a ranking; the best of 85 rows is inflated by selection. 3. Shortlist per spread: up to 3 candidates with mean_diff_s above 1.5 se_s on the spread they target. Spawn r3-extend: each exact hash, 3 measure items on 410500..410999, 411000..411499, 411500..411999, S and N on every seed, returning overall and per-spread n, sum_d, sum_d2, retail and arb differences and the per-seed arrays (seed, spread, d to 6 decimals), so any two candidates can later be paired with each other. An overlay candidate is given as the merge's SHA URL, its key in `top`, and the assembly recipe; a deepen candidate as its merge's `top` code. 4. To save an episode: a candidate whose screen gain on its spread is above 3 se_s goes straight to F in the same episode (r3-final: 8 items of 500 seeds over 900000..903999, same fields), at most one per spread, frozen hash. 5. Also spawn round 4's development in episode 6 (at least 100 items, about 40/30/15/15, against N, each guarded by spread): combine lane = same-spread pairs of round 3's screen winners and overlay-on-deepen grafts; deepen what the diagnostics name for spreads 2 and 3; fresh = new overlay mechanisms not in the list above; remove = deletions the remove lane found neutral, jointly; measure = replications. Use T 320000..320199 and H 430000..430499. 6. Episode 7: pool H2000 per spread, preselect at most one frozen block per spread, F finals (8 x 500 each). Episode 8: promote spread by spread where the pooled F gain on that spread exceeds 2 se with all 4000 seeds complete and 0 failures; spawn one compose item (guarded composition of the promoted blocks, exact-equality audit against each source on its spread, full code and hash, little else) and round 4's finals. Episode 9: second promotions and the final composed file; ask in `read` for the result that carries the full code. Episode 10: finish. Because a run has one spread and blocks are guarded, the composed file's F gain is the sum of the promoted spreads' sum_d over 4000; no re-measurement is needed, only the equality audit. 7. Stop early after two completed rounds in a row without a promotion. Round 3 completes with its F decision. LIMITS FOR THE WRITE-UP: F is reused across rounds and across up to four per-spread finalists, so its 2-se gate is weaker than on untouched seeds; H 410000..410499 is common to all round-3 items, so its ranking is selected; N came from another goal and was adopted, not promoted through our gate; local paired gains are not a leaderboard result; --sandbox was not run. Promotion rows: round, spread, old and new hash, code URL, F runs, gain, se, retail and arb change.
6 steps
r3-fresh-overlay, item by item r3-diagnose-current, item by item
Round 6r3-extend27 of 27 backr3-final-rc8 of 8 backr4-deepen44 of 44 backr4-fresh26 of 26 backr4-remove12 of 12 back
Agent #2 planned it.
what r3-extend was asked
One item measures ONE frozen candidate against the incumbent N on ONE block of 500 seeds, paired by seed. No development, no tuning: change no code. Candidate {{key}} ({{idea}}): {{how}} N: the `code` field of the JSON at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 ; SHA-256 of its UTF-8 bytes bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. Verify every hash by script first; report a mismatch, never work around it. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e. Seeds {{start}}..{{end}} inclusive, no seed outside this block. For each seed: config = sample_config(ChallengeConfig(), ParameterVariance(), seed=seed); SimulationEngine(config, factory, seed=seed).run() once for N and once per candidate; serial, no --workers, no --sandbox, unmodified simulator, default ChallengeConfig and ParameterVariance, 2000 steps. Run in the background (nohup) writing one line per (seed, strategy) to a file and poll it, or in chunks of 50 seeds per command, so a tool timeout loses nothing; each (seed, strategy) exactly once. Check first: N's total edge on seeds 310000..310003 must be 17.116002, 20.017111, 2.390311, 241.484752; report yours as check_values. d = candidate minus N total edge per seed; overall and per competitor spread s=1..4: n, sum_d, sum_d2, mean_diff = sum_d/n, se = sample sd of d / sqrt(n), incumbent_mean, candidate_mean, retail_diff, arb_diff (per-seed means). Result: one JSON object with key, candidate_sha256, incumbent_sha256, seeds {start, end}, n, complete (true only when every seed of the block ran once for both), missing_seeds, failures (seed and error), check_values, python_version, seconds_per_simulation, overall {n, sum_d, sum_d2, mean_diff, se, incumbent_mean, candidate_mean, retail_diff, arb_diff}, by_spread {"1","2","3","4": the same fields}, per_seed: an array of [seed, s, d rounded to 6 decimals] for every seed run, notes (at most 600 characters). No code in the result. A block that cannot finish reports complete false and the seeds that ran, never a partial block as the measurement.
what r3-final-rc was asked
One item measures ONE frozen candidate against the incumbent N on ONE block of 500 seeds, paired by seed. No development, no tuning: change no code. Candidate {{key}} ({{idea}}): {{how}} N: the `code` field of the JSON at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 ; SHA-256 of its UTF-8 bytes bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. Verify every hash by script first; report a mismatch, never work around it. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e. Seeds {{start}}..{{end}} inclusive, no seed outside this block. For each seed: config = sample_config(ChallengeConfig(), ParameterVariance(), seed=seed); SimulationEngine(config, factory, seed=seed).run() once for N and once per candidate; serial, no --workers, no --sandbox, unmodified simulator, default ChallengeConfig and ParameterVariance, 2000 steps. Run in the background (nohup) writing one line per (seed, strategy) to a file and poll it, or in chunks of 50 seeds per command, so a tool timeout loses nothing; each (seed, strategy) exactly once. Check first: N's total edge on seeds 310000..310003 must be 17.116002, 20.017111, 2.390311, 241.484752; report yours as check_values. d = candidate minus N total edge per seed; overall and per competitor spread s=1..4: n, sum_d, sum_d2, mean_diff = sum_d/n, se = sample sd of d / sqrt(n), incumbent_mean, candidate_mean, retail_diff, arb_diff (per-seed means). Result: one JSON object with key, candidate_sha256, incumbent_sha256, seeds {start, end}, n, complete (true only when every seed of the block ran once for both), missing_seeds, failures (seed and error), check_values, python_version, seconds_per_simulation, overall {n, sum_d, sum_d2, mean_diff, se, incumbent_mean, candidate_mean, retail_diff, arb_diff}, by_spread {"1","2","3","4": the same fields}, per_seed: an array of [seed, s, d rounded to 6 decimals] for every seed run, notes (at most 600 characters). No code in the result. A block that cannot finish reports complete false and the seeds that ran, never a partial block as the measurement.
what r4-deepen was asked
One item develops ONE change to the incumbent N and screens it paired against N. Idea {{key}}: {{idea}}. Spread(s): {{spreads}}. {{change}} Nothing else changes. N reads the rival's spread into self.s (1 to 4) at the first step and a run has one spread: act only when self.s is a target spread, so off-target seeds give d exactly 0. N: the `code` field of the JSON at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 ; SHA-256 of its UTF-8 bytes bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae; verify by script; you may read N. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e. For each seed: config = sample_config(ChallengeConfig(), ParameterVariance(), seed=seed); SimulationEngine(config, factory, seed=seed).run() once for N and once per candidate; serial, no --workers, no --sandbox, unmodified simulator, default ChallengeConfig and ParameterVariance, 2000 steps. Run in the background (nohup) writing one line per (seed, strategy) to a file and poll it, or in chunks of 50 seeds per command, so a tool timeout loses nothing; each (seed, strategy) exactly once. Check first: N's total edge on seeds 310000..310003 must be 17.116002, 20.017111, 2.390311, 241.484752; report yours as check_values. Tuning: seeds 320000..320199 only, at most 3 variants, pick one on tuning and freeze it. Holdout: seeds 430000..430499, every seed, the frozen variant and N. Never any other seed, never 900000..903999. d = candidate minus N total edge per seed; overall and per competitor spread s=1..4: n, sum_d, sum_d2, mean_diff = sum_d/n, se = sample sd of d / sqrt(n), incumbent_mean, candidate_mean, retail_diff, arb_diff (per-seed means). Result: one JSON object with key, idea, approach (at most 600 characters), tried (per variant: name, code_sha256, tuning mean_diff, se), next (one sentence), code (the frozen candidate's full source), code_sha256, incumbent_code_sha256, target_spreads, tuning {seeds, selected, variants}, paired {seeds, n, complete, missing_seeds, overall, by_spread {"1".."4"}}, failures (seed and error), check_values, python_version, seconds_per_simulation. A screen on 500 seeds, never a promotion.
what r4-fresh was asked
One item builds ONE overlay mechanism on the incumbent N, blind, and screens it paired against N. Mechanism {{key}}: {{mech}} Blind rule: do not open, print, diff or search N's source, any other strategy for this challenge, a leaderboard entry or an earlier result here. Read only the simulator, its README and docs: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified. Get N by script: download the JSON at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 , write its `code` field to n_strategy.py; SHA-256 of the UTF-8 bytes must be bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae (checked by script). Overlay: load n_strategy.py with its line `class Strategy(BaseStrategy):` replaced by `class _N(BaseStrategy):`; define `class Strategy(_N)` whose on_step calls super().on_step(state), then drops, resizes, moves or adds orders by your mechanism only, from the StepState and N's actions. N sets self.s (1 to 4) from the rival's spread at the first step and a run has one spread: act only on spreads where the mechanism makes sense (spreads_acted); show off_equals_n: switched off, actions equal N's on seeds 310000..310009 every step. For each seed: config = sample_config(ChallengeConfig(), ParameterVariance(), seed=seed); SimulationEngine(config, factory, seed=seed).run() once for N and once per candidate; serial, no --workers, no --sandbox, unmodified simulator, default ChallengeConfig and ParameterVariance, 2000 steps. Run in the background (nohup) writing one line per (seed, strategy) to a file and poll it, or in chunks of 50 seeds per command, so a tool timeout loses nothing; each (seed, strategy) exactly once. Check first: N's total edge on seeds 310000..310003 must be 17.116002, 20.017111, 2.390311, 241.484752; report yours as check_values. Tuning: seeds 320000..320199, at most 3 variants, freeze one. Holdout: seeds 430000..430499, every seed, frozen variant and N; no other seed, never 900000..903999. d = candidate minus N total edge per seed; overall and per competitor spread s=1..4: n, sum_d, sum_d2, mean_diff = sum_d/n, se = sample sd of d / sqrt(n), incumbent_mean, candidate_mean, retail_diff, arb_diff (per-seed means). Result: one JSON object with key, mech, approach (at most 600 characters), tried, next, spreads_acted, off_equals_n, code (overlay source only, at most 10000 bytes), code_sha256 (of it), assembled_sha256 (SHA-256 of N's text with that class line replaced, a newline, then the overlay), tuning {seeds, selected, variants}, paired {seeds, n, complete, missing_seeds, overall, by_spread {"1".."4"}}, failures, check_values, python_version, seconds_per_simulation. A screen, never a promotion.
what r4-remove was asked
One item tests ONE deletion from the incumbent N, without tuning, screened paired against N. Deletion {{key}}: {{idea}}. Target spread(s): {{spreads}}. Delete only: {{change}} Find it in N's source by this description; if N has no such mechanism, or it cannot be removed without touching another, set not_applicable true, say why, and run no simulations. The deletion must act only on the target spreads (guard by self.s, which N sets from the rival's spread at the first step), so off-target d is exactly 0. N: the `code` field of the JSON at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 ; SHA-256 of its UTF-8 bytes bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae; verify by script before use; you may read N. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e. For each seed: config = sample_config(ChallengeConfig(), ParameterVariance(), seed=seed); SimulationEngine(config, factory, seed=seed).run() once for N and once per candidate; serial, no --workers, no --sandbox, unmodified simulator, default ChallengeConfig and ParameterVariance, 2000 steps. Run in the background (nohup) writing one line per (seed, strategy) to a file and poll it, or in chunks of 50 seeds per command, so a tool timeout loses nothing; each (seed, strategy) exactly once. Check first: N's total edge on seeds 310000..310003 must be 17.116002, 20.017111, 2.390311, 241.484752; report yours as check_values. No tuning. Holdout: seeds 430000..430499, every seed, the deletion and N; never any other seed, never 900000..903999. d = candidate minus N total edge per seed; overall and per competitor spread s=1..4: n, sum_d, sum_d2, mean_diff = sum_d/n, se = sample sd of d / sqrt(n), incumbent_mean, candidate_mean, retail_diff, arb_diff (per-seed means). Result: one JSON object with key, idea, what_was_deleted (the removed or replaced lines, at most 1500 characters), not_applicable, code (the full candidate source), code_sha256, incumbent_code_sha256, target_spreads, paired {seeds, n, complete, missing_seeds, overall, by_spread {"1".."4"}}, failures, check_values, python_version, seconds_per_simulation, next (one sentence). A screen, never a promotion.
the whole memo
EPISODE 6: round 3 screened (105 items, all accepted); retreat-crossing sent to F; round 3 extension and round 4 development spawned (117 items: 27 extend, 8 final, 44 deepen, 26 fresh, 12 remove). Items used after this: 331 of 600. Episodes 7..10 remain; nothing spawned in 10 can be read. BEST N (adopted, not promoted): `code` of https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 , SHA-256 bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. LOCAL PROMOTIONS: none. F 900000..903999 run by nobody until r3-final-rc. Streak of completed rounds without promotion: 0 (round 3 completes with its F decision). Check values (unmodified simulator, N): seeds 310000..310003 total edge 17.116002, 20.017111, 2.390311, 241.484752; every brief asks for them. N's mean on H 410000..410499 is 104.4137531881468 on most machines, 104.39217582931519 on a few (older Python); within-item pairing is unaffected. SCOREBOARD, round 3 screen (H 410000..410499, candidate minus N; s = target spread; n per spread 115/116/138/131; complete, 0 failures). Candidate = `code` of https://api.imd.fun/artifacts/<art>. - retreat-crossing b5158a963a479a0919146dc0d56a347b68ddc2d66dd7c467b48473baef8997cf, art 459d3ec15ee1323593c23f1933500cb42ac662c51e5e2aa89f9b1befee3640d1 (s3): all +0.241 se 0.076; s3 +0.873 se 0.267 (3.3 se); tuning +0.053 se 0.097. -> F now (r3-final-rc) and extension. - s3-flow-transfer e7891178a0bd04852e48b14e76715b2ef37e7962d3dabca74f656dcda61d71de, art 4c44fcf1b73f132078bd65018aa8fea6531d4cc7c0cfd4e5f0b874a69ff39299 (s3): s3 +0.463 se 0.253; all +0.128 se 0.070. - s3-queue-transfer 998f1ca92b67bcc7ef539ca5e0beacf1def7472593f344cd660b4f59c6720ebd, art 530133206b1ed0615a14ad24e1aae13e0ec2f03b45d89cbf4e0f9f1a0ee2efe3 (s3): s3 +0.550 se 0.367; all +0.152 se 0.102. - f-jump-scale overlay 19aa0a454387c70ec599aacc8376ad9f6f128da3e15f380eea67b85798c0ebf6, assembled 499530021c3f72e8da491724f289913282998f1a183036e4ca65bfa1d3ccd86f, in `top` of r3-fresh-overlay/merge-01 = https://api.imd.fun/artifacts/1117198c0b6d6379587ca7db508e00b01a182bbbd5d78f737b803a9102057a2b (s2,s3): s3 +0.566 se 0.336, s2 +0.241 se 0.219. - s2-flow-jump-mask 91ce2de42cda0eb65638767a546b272549638ee7cf7fb94ed45a9650e5959db7, art fbd2c0ef8a258d64f04248e339e5e400f6ded3cb13f287718f45540542689b76 (s2): s2 +0.351 se 0.221; all +0.081 se 0.052. - s2-side-risk b1edc389df0c35a2dc0d73096f6a5eed337ff4ef026000ef67621f34773fee8f, art 7d4477490a285f9c7f2eb0d2ac89b584550b5e094737e0fad1d7670280e76bf7 (s2): s2 +0.390 se 0.270; all +0.091 se 0.063. - side-jump-budget 8c249a7d2ea89675599b3605807a195ee3c960f7db34650935c1f158ab210f14, art a53f876973198c8c1f235f17d201084f6ba7a97c6ad758b0b1229192ff731420 (s2,s3): s2 +0.98 se 0.98, s3 +0.98 se 0.97; all +0.50 se 0.35; tuning -0.02 se 0.42. - s1-queue-safety 77ba268c93b354ba963bb211608a2b8d2ea9c8d7e667cc9ef1c8bc8dcb926289, art e4f60b549bcecf2d4d54e39084dcd646c7fcfb67c44dd516545caf3aa384dd1c (s1): s1 +0.174 se 0.100; all +0.040 se 0.023. - f-flow-scales overlay 32f15d36aa069f24f51d668f00a8078f4a81dc646ed13252cbff516e3b16f9b7, assembled 18419c9594a4e685223f3d2eed57f197ccf29f36c13c02f4078e5b9f8e33599f, in `top` of r3-fresh-overlay/merge-05 = https://api.imd.fun/artifacts/24831096ba62b5aa485b6449ed0c80af71dc487f3fb25faa1a73a8c5fe59dcc3 (s4): s4 +0.307 se 0.185; all +0.081 se 0.049. Below 1.5 se: stock-entry-gate port 682cdc9b all +0.30/0.40 (s4 -0.29); s4-uncertainty-tail s4 +0.13/0.10; s3-flow-shrinkage s3 +0.11/0.08; f-post-jump s1 +0.06/0.05. The other 60 rows are null (24 deepen/overlay/remove rows within noise) or harmful: remove-far-probes -10.2, remove-penny-bank -1.0, remove-below-tick-decay -0.13/0.06, remove-flow-quote -0.16/0.12, f-ambiguity -44, f-competing-risk -5.9, f-cancel-option -5.2, f-shortfall-cap -4.0, f-drift-skew -2.0, f-endgame-stop -1.3, f-pit-calibration -0.87/0.15, f-join-timing -0.49/0.08, f-fill-imbalance -0.30/0.09, s2-coverage-threshold -0.14/0.08. Void and rerun in r4-remove: remove-hysteresis (paired against combine-cash), remove-late-uncovered (222 seeds). combine-cash vs N: -0.4 to -2.0 per 500-seed block. DIAGNOSTICS of N (500-seed blocks 500000..502499): an oracle cancelling orders about to be swept only on a >=3-tick next move gains +3.2 s1, +7.6 s2, +9.0 s3, +17.1 s4 (all arbitrage); cancelling every swept order loses 27-59. One step after an own fill the sweep rate on that side is 0.77-0.85 vs 0.36 without (s2,s3), and such fills precede 64% of arb loss: the own-fill pullback family in r4-deepen is the main bet. Jump-step asks net -6.7 s2, -11.6 s3; bids with no rival bid net -5.0 s2, -3.1 s3; nonjump inside asks net +112 s2, +75 s3 (never shrink them). At 20-80c N takes 21-23% of retail notional on s2 (rival earns 33.7/run vs N 11.0), 40% on s3, 0.3% on s1. Net-negative time-price cells (s2 p<5c steps 200-999; s2 5-20c and s3 20-80c steps 1600-1899) are -2.3 each, within noise. BATCHES NOW (all against N): r3-extend (27: the nine candidates above x 3 blocks 410500..410999 / 411000..411499 / 411500..411999, keys <key>-a/b/c, merges of 3 in that order: pooled stats and per-seed arrays); r3-final-rc (8: retreat-crossing on 900000..903999, rc-f1..rc-f8); r4-deepen (44, merges of 11: c-* combines of the winners, d-* diagnostic-driven, p-* ports of old-B gains; T 320000..320199, H 430000..430499); r4-fresh (26 new overlay mechanisms, merges of 9); r4-remove (12, merges of 6). Fields as in round 3 plus check_values and python_version; measure items return per_seed [seed, s, d]. NEXT EPISODE (7), in order: 1. r3-final-rc: pool the 8 blocks (mean = S/n, se = sqrt((Q - S*S/n)/(n-1)/n) from n, sum_d, sum_d2), overall and s3. PROMOTE retreat-crossing as the s3 block if n = 4000 complete, 0 failures, check values right, and both the s3 gain and the overall gain exceed 2 se. Record: round 3, spread 3, N -> b5158a96..., F n, gain, se, retail and arb change, N's F mean. Its file is N plus a guarded s3 change, submittable as is; later s3 candidates must beat it (the c-s3-retreat-* combines build on it). Otherwise no promotion yet; the streak stays 0 until round 3's other finalists are decided. 2. r3-extend merges: pooled H2000 per spread per candidate (unselected evidence). Per spread at most one finalist with pooled gain_s > 2 se_s (fall back to > 1.5 se_s if none); spawn r3-final-<key> (8 x 500 over 900000..903999, the measure brief). An s3 finalist other than retreat-crossing only if its pooled s3 gain exceeds retreat-crossing's. 3. r4 merges: scoreboard by spread (drop flagged rows and rows whose incumbent_mean on 430000..430499 differs from the majority); > 1.5 se_s to r4-extend (3 x 500 on 430500..431999); > 3 se_s straight to F (8 x 500) if that spread has no finalist yet. 4. Episode 8: promotions from F per spread; one compose item (N with each promoted spread's block, exact-equality audit against each source on its spread, full code and hash, little else); r4 F finals. Episode 9: last promotions, final compose, ask in `read` for the result carrying the full code. Episode 10: finish. Stop early after two completed rounds in a row without a promotion. SEED LEDGER: exposed below 300000; round 3 T 310000..310199 (fixtures 310000..310999), H 410000..411999 (all used); SEG audit 420000..421999; diagnostics 500000..502499; round 4 T 320000..320199, H 430000..430499, extension 430500..431999; reserved T 330000..330999, H 440000..441999; confirmations free from 510000; F only in final batches. LESSONS: items hit 10-minute tool timeouts near 500 pairs, so briefs say run in the background or in chunks of 50 seeds, and the one-OS-process rule is dropped (pairing is by seed). Never ask an item or a merge for a command's output. A batch over 30 reads needs merges. Write-up limits: F reused across rounds and finalists; H common to a round's items (selected); N adopted from another goal; local paired gains are not a leaderboard result; --sandbox not run.
19 steps
r3-extend, item by item r3-final-rc, item by item r4-deepen, item by item r4-fresh, item by item r4-remove, item by item
Round 7r5-final10 of 10 backr4-extend18 of 18 backr5-deepen32 of 32 back, cancelledr5-fresh11 of 11 back, cancelledr5-removerefused, never ranr5-diagnose2 of 2 back
Agent #1299 planned it, 2 attempts.
The plane refused 4 of its decisions. The next round is told why.
what r5-final was asked
One item measures ONE frozen candidate against ONE frozen comparator on ONE block of 500 seeds, paired by seed. No development, no tuning: change no code. Candidate {{key}} ({{idea}}): {{cand_how}} The SHA-256 of its UTF-8 bytes must be {{cand_sha}}. Comparator {{base_name}}: the `code` field of the JSON at {{base_url}} ; SHA-256 {{base_sha}}. Verify every hash by script before running; on a mismatch report it and run nothing. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig and ParameterVariance, 2000 steps, no --workers, no --sandbox. For each seed from {{start}} to {{end}} inclusive: cfg = sample_config(ChallengeConfig(), ParameterVariance(), seed=seed); run SimulationEngine(cfg, factory, seed=seed).run() once for the comparator and once for the candidate, each with a fresh strategy instance from load_strategy_factory; d = candidate total_edge minus comparator total_edge, unrounded; s = the sampled competitor spread in ticks (1 to 4), checked against the first observed rival quotes (ask minus bid equals 2s-1). Run in chunks of at most 50 seeds per command, each chunk appending to one results file, so a tool timeout loses nothing; before summarising check that every seed has exactly one record per strategy and rerun any seed that is missing or duplicated. Check values first: N on seeds 310000..310003 gives total edge 17.116002, 20.017111, 2.390311, 241.484752 (run N for the checks even when it is not the comparator). Result JSON fields: key, idea, candidate_sha256, comparator_sha256, seeds {start, end}, n, complete (true only when all 500 pairs ran), missing_seeds, failures [{seed, error}], check_values [4 numbers], python_version, seconds_per_simulation, overall {n, sum_d, sum_d2, mean_diff, se, comparator_mean, candidate_mean, retail_diff, arb_diff}, by_spread {"1","2","3","4": the same fields}, per_seed [[seed, s, d to 6 decimals], ...], notes (at most 600 characters). se = sqrt((sum_d2 - sum_d*sum_d/n)/(n-1)/n). Report what ran: a partial run is complete false with its missing seeds listed, never padded or projected. No code in the result.
what r4-extend was asked
One item measures ONE frozen candidate against ONE frozen comparator on ONE block of 500 seeds, paired by seed. No development, no tuning: change no code. Candidate {{key}} ({{idea}}): {{cand_how}} The SHA-256 of its UTF-8 bytes must be {{cand_sha}}. Comparator {{base_name}}: the `code` field of the JSON at {{base_url}} ; SHA-256 {{base_sha}}. Verify every hash by script before running; on a mismatch report it and run nothing. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig and ParameterVariance, 2000 steps, no --workers, no --sandbox. For each seed from {{start}} to {{end}} inclusive: cfg = sample_config(ChallengeConfig(), ParameterVariance(), seed=seed); run SimulationEngine(cfg, factory, seed=seed).run() once for the comparator and once for the candidate, each with a fresh strategy instance from load_strategy_factory; d = candidate total_edge minus comparator total_edge, unrounded; s = the sampled competitor spread in ticks (1 to 4), checked against the first observed rival quotes (ask minus bid equals 2s-1). Run in chunks of at most 50 seeds per command, each chunk appending to one results file, so a tool timeout loses nothing; before summarising check that every seed has exactly one record per strategy and rerun any seed that is missing or duplicated. Check values first: N on seeds 310000..310003 gives total edge 17.116002, 20.017111, 2.390311, 241.484752 (run N for the checks even when it is not the comparator). Result JSON fields: key, idea, candidate_sha256, comparator_sha256, seeds {start, end}, n, complete (true only when all 500 pairs ran), missing_seeds, failures [{seed, error}], check_values [4 numbers], python_version, seconds_per_simulation, overall {n, sum_d, sum_d2, mean_diff, se, comparator_mean, candidate_mean, retail_diff, arb_diff}, by_spread {"1","2","3","4": the same fields}, per_seed [[seed, s, d to 6 decimals], ...], notes (at most 600 characters). se = sqrt((sum_d2 - sum_d*sum_d/n)/(n-1)/n). Report what ran: a partial run is complete false with its missing seeds listed, never padded or projected. No code in the result.
what r5-deepen was asked
One item develops ONE change to the incumbent RC and screens it paired against RC. Idea {{key}}: {{idea}} Spread(s): {{spreads}}. {{change}} Nothing else changes; prefer a wrapper subclass at the end of the file. RC: the `code` field of the JSON at https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb ; SHA-256 3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f. RC is N plus a wrapper subclass at the end of the file: on an exactly-one-tick rival retreat (bid down or ask up) it cancels every own order on that side and suppresses placements there for one callback, spreads 2 and 3 only, clearing that side's probe bookkeeping (pb, pa, last_quote_exposed). Verify the hash by script; on a mismatch report and stop. RC sets self.s (rival spread 1 to 4) at the first step; a run has one spread: act only on target spreads, so off-target d is exactly 0. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig and ParameterVariance, 2000 steps, no --workers, no --sandbox. Check values: report RC's total edge on seeds 310000..310003 as check_values (every item must get the same four numbers). Pair by seed: sample_config(ChallengeConfig(), ParameterVariance(), seed=seed), then SimulationEngine(cfg, factory, seed=seed).run() for RC and for the candidate; d = candidate minus RC total_edge; s = the sampled spread. Run chunks of at most 50 seeds per command, appending to a file; check every seed has one record per strategy. Tuning: seeds 330000..330199, at most 4 variants, pick the best paired mean on the target spread(s), freeze. Holdout: seeds 440000..440499, once, after freezing; never retune on it. Result JSON: key, idea, approach (at most 500 characters), tried (per variant: name, code_sha256, tuning mean_diff, se), next, code (the frozen full file, UTF-8; gzip+base64 with code_encoding if the result would pass 60,000 bytes), code_sha256, comparator_sha256, target_spreads, tuning {seeds, selected, variant stats}, paired {seeds, n, complete, missing_seeds, overall and by_spread "1" to "4": n, sum_d, sum_d2, mean_diff, se, comparator_mean, candidate_mean, retail_diff, arb_diff}, failures, check_values, python_version, seconds_per_simulation. se = sqrt((sum_d2 - sum_d*sum_d/n)/(n-1)/n). No per-seed arrays; a partial run says complete false. A screen, not a promotion.
what r5-fresh was asked
One item builds ONE overlay mechanism on the incumbent file RC, blind, and screens it paired against RC. Mechanism {{key}}: {{mech}} Act only on spreads {{spreads}} (s = max(1, (ask - bid + 1) // 2) from the rival's first quotes; off-target d must be exactly 0). Blind rule: never open, print, diff or search RC's source, any other strategy for this challenge, a leaderboard entry or an earlier result; read only the simulator and its docs. Get RC by script: write the `code` field of the JSON at https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb to a file, check its UTF-8 SHA-256 is 3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f (stop on a mismatch), and import it as a module you never read. Your overlay subclasses its Strategy, calls super().on_step(state) and edits the returned actions by your one mechanism only (drop, add or resize CancelOrder and PlaceOrder actions), reading StepState only (step, cash, inventory, fills, own orders, rival best bid and ask ticks). With the mechanism off it must return RC's actions unchanged (check 3 seeds, report off_equals_rc). assembled_sha256 = SHA-256 of RC's text with its class Strategy renamed _RC, followed by your overlay whose subclass is named Strategy. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig and ParameterVariance, 2000 steps, no --workers, no --sandbox. Check values: report RC's total edge on seeds 310000..310003 as check_values (every item must get the same four numbers). Pair by seed: sample_config(ChallengeConfig(), ParameterVariance(), seed=seed), then SimulationEngine(cfg, factory, seed=seed).run() for RC and for the candidate; d = candidate minus RC total_edge; s = the sampled spread. Run chunks of at most 50 seeds per command, appending to a file; check every seed has one record per strategy. Tuning: seeds 330000..330199, at most 4 variants, pick the best paired mean on the target spread(s), freeze. Holdout: seeds 440000..440499, once, after freezing; never retune on it. Result JSON: key, mechanism, approach (at most 400 characters), tried (per variant: name, code_sha256, tuning mean_diff, se), next, spreads_acted, off_equals_rc, code (overlay source, at most 10,000 bytes), code_sha256, assembled_sha256, comparator_sha256, tuning stats, paired {seeds, n, complete, missing_seeds, overall and by_spread "1" to "4": n, sum_d, sum_d2, mean_diff, se, comparator_mean, candidate_mean, retail_diff, arb_diff}, failures, check_values, python_version, seconds_per_simulation. se = sqrt((sum_d2 - sum_d*sum_d/n)/(n-1)/n). No per-seed arrays; a partial run says complete false. A screen, not a promotion.
what r5-remove was asked
One item tests ONE deletion from the wrapper that RC adds to N, without tuning, screened paired against RC. Deletion {{key}}: {{idea}} Target spread(s): {{spreads}}. Delete only: {{change}} Everything else stays byte for byte; off-target d must be exactly 0. If the wrapper has no such part, set not_applicable true, say why, and run no simulations. RC: the `code` field of the JSON at https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb ; SHA-256 3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f. RC is N plus a wrapper subclass at the end of the file: on an exactly-one-tick rival retreat (bid down or ask up) it cancels every own order on that side and suppresses placements there for one callback, spreads 2 and 3 only, clearing that side's probe bookkeeping (pb, pa, last_quote_exposed). Verify the hash by script; on a mismatch report and stop. RC sets self.s (rival spread 1 to 4) at the first step; a run has one spread: act only on target spreads, so off-target d is exactly 0. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig and ParameterVariance, 2000 steps, no --workers, no --sandbox. Check values: report RC's total edge on seeds 310000..310003 as check_values (every item must get the same four numbers). Pair by seed: sample_config(ChallengeConfig(), ParameterVariance(), seed=seed), then SimulationEngine(cfg, factory, seed=seed).run() for RC and for the candidate; d = candidate minus RC total_edge; s = the sampled spread. Run chunks of at most 50 seeds per command, appending to a file; check every seed has one record per strategy. Seeds: the holdout 440000..440499 only, once; no tuning. d = deleted version minus RC: negative means the deleted part carries gain, positive means RC is simpler without it. Result JSON: key, idea, what_was_deleted (the removed or replaced lines), not_applicable, code (the full file as UTF-8 text; gzip+base64 with code_encoding if the result would pass 60,000 bytes), code_sha256, comparator_sha256, target_spreads, paired {seeds, n, complete, missing_seeds, overall and by_spread "1" to "4": n, sum_d, sum_d2, mean_diff, se, comparator_mean, candidate_mean, retail_diff, arb_diff}, failures, check_values, python_version, seconds_per_simulation. se = sqrt((sum_d2 - sum_d*sum_d/n)/(n-1)/n). No per-seed arrays; a partial run says complete false. A screen, not a promotion.
what r5-diagnose was asked
One item measures ONE thing about the incumbent N, by rival spread. It builds no candidate and changes no strategy. Measurement {{key}}: {{what}} N: the `code` field of the JSON at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 ; SHA-256 of its UTF-8 bytes bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. You may read it. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified in what it simulates, default ChallengeConfig and ParameterVariance, 2000 steps, no --workers, no --sandbox. You may instrument the simulator in-process (read the true probability path, the arbitrageur's and retail fills, and N's orders each step) as long as N's actions and the scores are unchanged: check that N on seeds 310000..310003 gives total edge 17.116002, 20.017111, 2.390311, 241.484752. Seeds: 510000..510499, one run of N per seed, grouped by the sampled competitor spread s (1 to 4). Run in chunks of at most 50 seeds per command appending to a file. Result JSON fields: key, what, n_seeds, by_spread {"1","2","3","4": the figures the measurement names, each with its count}, finding (at most 700 characters: what spreads 1 to 4 show and what change to N it suggests), method (at most 600 characters), check_values, python_version. No strategy code in the result.
the whole memo
EPISODE 7: no promotion yet; round 4's winner retreat-cancel (5 se on its screen) sent to F; retreat-crossing's F incomplete; round 5 (49 development items) built on retreat-cancel. Spawned 79 items; used after this: 410 of 600. Episodes 8, 9, 10 remain; nothing spawned in 10 can be read. A first try of this episode was rejected for shape: vars as strings, filled briefs under 3000 characters. BEST N (adopted, not promoted): `code` of https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 , SHA-256 bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. LOCAL PROMOTIONS: none. Streak of completed rounds without promotion: 0 (round 3 completes with retreat-crossing's F decision, round 4 with retreat-cancel's; both in episode 8). Check values (N, seeds 310000..310003): 17.116002, 20.017111, 2.390311, 241.484752. RC = d-s23-retreat-cancel, provisional s2/s3 block and round 5's base: `code` of https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb , SHA-256 3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f (verified here: artifact digest, code hash, and the copy in r4-deepen/merge-03 top). It is N's text plus a wrapper subclass at the end: on an exactly-one-tick rival retreat (bid down or ask up) it cancels every own order on that side and suppresses placements there for one callback, spreads 2 and 3 only, clearing pb/pa/last_quote_exposed. Screen H 430000..430499 vs N: overall +0.562 se 0.108; s2 +1.114 se 0.357 (n 120); s3 +1.109 se 0.233 (n 133); retail -0.106, arb +0.669; tuning +0.518 se 0.151; 0 failures. On s1/s4 it equals N. Round-5 items report RC's own values on 310000..310003 as check_values (compare across rows, not with N's). F EVIDENCE (900000..903999 vs N), retreat-crossing b5158a963a479a0919146dc0d56a347b68ddc2d66dd7c467b48473baef8997cf (`code` of https://api.imd.fun/artifacts/459d3ec15ee1323593c23f1933500cb42ac662c51e5e2aa89f9b1befee3640d1 ): 7 of 8 blocks; rc-f1 lost seeds 900000..900051 (n 448), rc-f5 (902000..902499) never ran (no network). Pooled n 3448: overall +0.0974 se 0.0484 (sum_d 335.85), retail +0.004, arb +0.094; s3 n 828 +0.406 se 0.201 (2.0 se). Block s3 means range -0.98 (f8, seed 903655 at -139.6) to +1.09. Extension H 410500..411999: overall -0.064 se 0.144, s3 -0.255 se 0.576. NOT promoted: F incomplete, gain at the gate. r5-final/cross-f1 and cross-f5 rerun those blocks; episode 8 pools all 8 (reruns replace f1 and f5) and promotes only if n 4000, 0 failures, s3 and overall gains both > 2 se. If RC passes F it supersedes retreat-crossing on s3 unless c5-s3-cancel-crossing adds over RC. ROUND 3 EXTENSION (H 410500..411999, n 1500, vs N): all dead; best s3-flow-transfer s3 +0.26 se 0.13; side-jump-budget -0.43 se 0.23; s2-side-risk s2 -0.34. Old stock-entry-gate and side-jump-budget vs N (420000..421999): -1.1 to -2.1 per block. ROUND 4 SCREEN (H 430000..430499 vs N, target spread; art = artifact SHA, code = `code` of https://api.imd.fun/artifacts/<art>): d-s1-retreat-crossing-port bed6def9 s1 +0.851 se 0.400 (art 6b9ed17bf5dea051170d96ecb2a250d14a21d2ff880ecb8f9017883bd03de44b; plane flagged a source). c-s1-queue-postjump 64209895 s1 +0.496 se 0.262 (r4-deepen/merge-01 top, zlib+base64, art 2194012e1ad22d8ec3c929865387870137484f68b7dc438c15bee80be81a9661; flagged). c-s3-retreat-strength 40829d7a s3 +0.94 se 0.50 (same merge top). c-s2-mask-to-ask bf5b107d s2 +0.64 se 0.78 (merge-02 top, art 30904b002314c987d356340c07addc67067aaf7c2dc4125646e7709f7e3bcce7). d-s2-lowp-early-bids c3f52bdf s2 +0.117 se 0.054 (art b4a68d2dd1bbd03bdc96072615ada1d5c5f27cafdf897c1bfac5913f5996be0c). d-s3-mid-size-up 1317a49c s3 +0.174 se 0.105 (art f3f50cdb058d56b7842ec97f345bc7c11858d0b3b5370ea620fc66c593229e03). remove-s4-ask-risk-premium 324acde8 s4 +0.34 se 0.28 (r4-remove/merge-01 top, plain code, art e019e7d93ce9c99453526d9d2113561d4c4ec0de062a50c42b51edd9edd62a5e). Harmful: every own-fill pull (-5 to -36), join-mid (-20 s2), noquote-bid-withdraw -4.0, markout-widen -4.1, deletions of s3 qa cap, s4 cheap bids, s4 bid tranches, s2 old-price queue (-0.3 to -0.5), joint deletions. All 26 r4-fresh overlays at or below zero (56 blind overlays in two rounds, none gained), so round 5's fresh lane tests one StepState signal each as an overlay on RC. BATCHES NOW: - r5-final (10, read item by item): cancel-f1..f8 = RC vs N on 900000..903999 in 500-seed blocks; cross-f1 (900000..900499) and cross-f5 (902000..902499) = retreat-crossing reruns. Fields: overall and by_spread n, sum_d, sum_d2, mean_diff, se, retail_diff, arb_diff; per_seed; complete; failures. - r4-extend (18, merges of 3 in item order: 01 cancel, 02 s1-port, 03 s1-postjump, 04 s2-lowp, 05 s3-midsize, 06 s4-norisk), each vs N on 430500..430999 / 431000..431499 / 431500..431999: unselected replication of the round 4 screen. - r5-deepen (32, merges of 8, vs RC; T 330000..330199, H 440000..440499): ports of the cancel to s1 and s4 (d5-s1/s4-cancel-port, -any-outward), 21 cancel-mechanic variants on s2/s3 (d5-s23-cancel-*), d5-s2-retreat-posterior, combines c5-s3-cancel-crossing, c5-s2-cancel-lowp, c5-s3-cancel-midsize, c5-s1-port-postjump, c5-s1-port-cancel, c5-s2-cancel-mask-to-ask. Keys in the merges' rows. - r5-fresh (11, merges of 6, blind overlays on RC vs RC, one rival-quote or own-fill signal each, keys f5-*). - r5-remove (6, merges of 3, vs RC on H 440000..440499): drop the bid or ask trigger on s2 or s3, drop the suppression, drop the probe clearing. Negative d = the part carries gain. - r5-diagnose (2, item by item, N on 510000..510499): d5-diag-retreat, d5-diag-advance (next-step move and arb change after each rival-quote event, by spread). NEXT EPISODE (8), in order: 1. Pool r5-final per candidate (mean = S/n, se = sqrt((Q - S*S/n)/(n-1)/n)), overall and per spread. PROMOTE RC as the s2 and s3 block if n 4000, 0 failures, check values right, and s2, s3 and overall gains each exceed 2 se (if only one spread clears, promote that spread alone; the compose item narrows the wrapper's guard). Record: round 4, spreads, N -> 3c07bdcd..., F n, gain, se, retail and arb change, N's F mean. Decide retreat-crossing on s3 as above. 2. Round 5 scoreboard from the merges' rows (vs RC): drop flagged rows and rows whose comparator_mean on 440000..440499 differs from the majority. Target gain > 1.5 se: extend on 440500..441999 (3 x 500, measure brief with base RC); > 3 se: straight to F (8 x 500 vs RC) where that spread has no F finalist. s1 and s4 have none; r4-extend merges decide between the s1 candidates. 3. Spawn one compose item once a promotion exists: N with each promoted block, exact-equality audit against each source on its spread over 100 seeds, full code and hash, little else (gzip+base64 if needed). 4. Episode 9: last promotions from round 5's F, final compose, and ask in `read` for the result carrying the full code. Episode 10: finish; the write-up needs the best's full code, its F evidence and the ranked promotion table. 5. Stop early after two completed rounds in a row without a promotion. SEED LEDGER: exposed below 300000; round 3 T 310000..310199, H 410000..411999; SEG audit 420000..421999; diagnostics 500000..502499, 510000..510499; round 4 T 320000..320199, H 430000..431999 (all used); round 5 T 330000..330199, H 440000..440499, extension 440500..441999; reserved T 340000..340999, H 450000..451999; confirmations free from 520000; F only in final batches (used by retreat-crossing and RC). LESSONS: measure items must rerun lost seeds; never ask an item or a merge for a command's output; merges carry full code gzip+base64 in `top`, and `input_sources` gives each item's result SHA = its artifact URL. Write-up limits: F reused across rounds and finalists; H common to a round's items; N adopted from another goal; local paired gains are not a leaderboard result; --sandbox not run; round 5 is under the requester's 100 items because distinct ideas ran out, not budget.
13 steps
r5-final, item by item r4-extend, item by item r5-deepen, item by item r5-fresh, item by item r5-diagnose, item by item
Round 8r6-port14 of 14 backr6-fresh7 of 7 backr6-base-f8 of 8 back
Agent #2 planned it.
what r6-port was asked
One item ports ONE idea onto the incumbent MA and screens it paired against MA, by rival spread. Idea {{key}}: {{idea}} Target spread(s): {{spreads}}. Source: {{source}} Port: {{change}} MA (m-plus-a, our live entry): the `code` field of the JSON at https://api.imd.fun/artifacts/149883fee797ad95a91e535b7a74453587a3eb19ca87ab95f7d8585db160a8f4 ; SHA-256 of its UTF-8 bytes 5d1bd5272884f513b19f0e66a7c235f6c188a08e4f7787ac9346f1614dda3ed3. N (the file the sources changed): `code` of https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 . MA keeps self.s (1 to 4, from the rival's first quotes), pb, pa, ahead, res and last_quote_exposed like N. Layout: MA's text unchanged, two newlines, then `_IncumbentStrategy = Strategy` and `class Strategy(_IncumbentStrategy):` whose on_step calls super().on_step and alters the actions; edit MA's body only where a wrapper cannot express the idea. Guard by self.s: on every off-target spread the actions must equal MA's exactly (paired d exactly 0; check it). Verify hashes by script first. Simulator: github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, defaults, 2000 steps, one process, no --sandbox or --workers; per seed run runner.sample_config and SimulationEngine(config, factory, seed=seed) for both files; d = candidate total_edge - MA total_edge; s = max(1, (ask - bid + 1) // 2) from the rival's first quotes. MA's total_edge on seeds 310000..310003 must be 17.116002, 23.820392, 2.376144, 243.87214. Tune at most 3 variants on T = 340000..340199; freeze the best by paired mean on the target spread; holdout H = 450000..450999 (1000 pairs). Chunk 50 seeds a command, rerun lost seeds, never report a partial block; touch no seed in 700000..709999 or 900000..903999. Result JSON (under 64000 bytes): key, idea, spreads, approach, tried, next, port_kind (wrapper|body|not_applicable), code (full file, gzip+base64), code_sha256 (plain file), base_sha256, check_values, python_version, tuning {seeds, variants [{name, code_sha256, mean_diff, se, by_spread}], selected}, paired {seeds, n, complete, missing_seeds, failures, overall and by_spread 1..4 each with n, sum_d, sum_d2, mean_diff, se, base_mean, retail_diff, arb_diff; off_target_zero; per_seed [[seed, s, d]...]}, worst_seeds (five most negative d), notes (under 1500 characters). se = sqrt((sum_d2 - sum_d*sum_d/n)/(n-1)/n). Fields only, never a command's output.
what r6-fresh was asked
One item builds ONE overlay mechanism on the incumbent file MA, blind, and screens it paired against MA. Mechanism {{key}}: {{mech}} Act only on spreads {{spreads}} (s = max(1, (ask - bid + 1) // 2) from the rival's first quotes); elsewhere return MA's actions unchanged, so paired d there is exactly 0. Blind rule: never open, print, diff or search MA's source, any other strategy for this challenge, a leaderboard entry or an earlier result; read only the simulator and its docs. Get MA by script: write the `code` field of the JSON at https://api.imd.fun/artifacts/149883fee797ad95a91e535b7a74453587a3eb19ca87ab95f7d8585db160a8f4 to a file, check its UTF-8 SHA-256 is 5d1bd5272884f513b19f0e66a7c235f6c188a08e4f7787ac9346f1614dda3ed3, never display it. Candidate layout: MA's text unchanged, two newlines, then `_IncumbentStrategy = Strategy` and `class Strategy(_IncumbentStrategy):` whose __init__ calls super().__init__() and whose on_step(state) calls super().on_step(state) and then drops, adds, resizes or re-prices orders (PlaceOrder, CancelOrder from orderbook_pm_challenge.types) using only the StepState and its own state; read no attribute of the base class. Simulator: github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, defaults, 2000 steps, one process, no --sandbox or --workers; per seed run runner.sample_config and SimulationEngine(config, factory, seed=seed) for both files; d = candidate total_edge - MA total_edge. MA's total_edge on seeds 310000..310003 must be 17.116002, 23.820392, 2.376144, 243.87214. Tune at most 3 variants on T = 340200..340399; freeze the best by paired mean on the target spreads; holdout H = 450000..450499 (500 pairs). Chunk 50 seeds a command, rerun lost seeds, never report a partial block; touch no seed in 700000..709999 or 900000..903999. Result JSON (under 64000 bytes): key, mechanism, spreads_acted, approach, tried, next, overlay_code (your appended source, plain text), overlay_sha256, code_sha256 (whole assembled file), base_sha256, check_values, python_version, tuning {seeds, variants [{name, code_sha256, mean_diff, se, by_spread}], selected}, paired {seeds, n, complete, missing_seeds, failures, overall and by_spread 1..4 each with n, sum_d, sum_d2, mean_diff, se, base_mean, retail_diff, arb_diff; off_target_zero; per_seed [[seed, s, d]...]}, worst_seeds (five most negative d), notes (under 1500 characters). se = sqrt((sum_d2 - sum_d*sum_d/n)/(n-1)/n). Fields only, never a command's output.
what r6-base-f was asked
One item measures ONE frozen candidate against ONE frozen comparator on ONE block of 500 seeds, paired by seed. No development, no tuning: change no code. Candidate {{cand_name}}: the `code` field of the JSON at {{cand_url}} ; SHA-256 of its UTF-8 bytes {{cand_sha}}. Comparator {{base_name}}: the `code` field of the JSON at {{base_url}} ; SHA-256 {{base_sha}}. Verify both hashes by script before running; on a mismatch report it and run nothing. Simulator: https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig and ParameterVariance, 2000 steps, one Python process, no --sandbox, no --workers. Seeds {{seed_start}}..{{seed_end}} inclusive, every one of them. For each seed run runner.sample_config(base, var, seed=seed) and SimulationEngine(config, factory, seed=seed) for both strategies with a fresh strategy instance; d = candidate total_edge - comparator total_edge; spread s of a seed = max(1, (ask - bid + 1) // 2) from the rival's first quotes. Check values: the comparator's total_edge on seeds 310000..310003 must be {{base_check}} (6 decimals); stop and report if not. Run in chunks of 50 seeds, in the background if a command times out; rerun lost seeds; the block is complete only when all 500 seeds have both runs; never report a partial block as the measurement. Touch no other seed. Result JSON (at most 64000 bytes): key, candidate_sha256, comparator_sha256, seeds {start, end}, n, complete, missing_seeds, failures, check_values, python_version, seconds_per_simulation, overall {n, sum_d, sum_d2, mean_diff, se, comparator_mean, candidate_mean, retail_diff, arb_diff}, by_spread {1, 2, 3, 4: the same fields}, per_seed [[seed, s, d to 6 decimals]...], worst_seeds (five most negative d with seed and s), notes (at most 1000 characters). se = sqrt((sum_d2 - sum_d*sum_d/n)/(n-1)/n). Report fields only, never a command's output.
the whole memo
EPISODE 8: base moved to MA on the requester's 00:30Z note; round 6 = 14 ports/deepen on MA, 7 blind overlays on MA, 8 blocks of MA vs N on F; r5-deepen and r5-fresh (RC-based, 33 held) cancelled. Spawned 29; used after this about 400 of 600. Episodes 9 and 10 remain; nothing spawned in 10 can be read: episode 9 spawns the last F finals and compose items, episode 10 promotes and finishes. STANDINGS (requester, not live-checked): 1st Ponxter v23 110.69, us 2nd 110.21 (entry #1042 = m-plus-a or m-plus-b), 3rd 109.59. Gap 0.48. BASE MA (m-plus-a; adopted, not promoted): `code` of https://api.imd.fun/artifacts/149883fee797ad95a91e535b7a74453587a3eb19ca87ab95f7d8585db160a8f4 , SHA-256 5d1bd5272884f513b19f0e66a7c235f6c188a08e4f7787ac9346f1614dda3ed3, 37922 bytes. Its artifact: +2.43 se 0.22 over the 108.47 file (s1 +2.76, s2 +3.12, s3 +1.18, s4 +2.61). MB (m-plus-b, +2.21 se 0.17): https://api.imd.fun/artifacts/6b40ef6fdf9512700501e6b92fb5c920955a97b29111faada6d411074173b7cd . N (previous base) bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae at https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6 . MA CHECK VALUES (run here, unmodified simulator b244530e, seeds 310000..310003 total_edge): 17.116002, 23.820392, 2.376144, 243.87214. N's: 17.116002, 20.017111, 2.390311, 241.484752. MA has one `class Strategy(BaseStrategy):` and N's attributes. RC WRAPPER PORTS TO MA: RC's text from its line `_IncumbentStrategy = Strategy` to the end (1948 bytes, SHA-256 accbde6a21b3b86b3bb95db393a74b6c9f20fde939f031db29d7d00dda13ca19) appended to MA after two newlines gives MARC, SHA-256 0d627e80d1c3ecb98da2ccddf7406e301c76e59ab86c4ee068e508b6074f76ac (N + two newlines + wrapper reproduces RC exactly). Checked on 5 seeds: MARC differs from MA on spreads 2 and 3, equals it on 1 and 4. RC-on-MA/MB is measured by goal 75dd8e1e on 700000..709999: do not duplicate; expect the requester to post it. If positive, episode 9's s2/s3 finals run stacked on MARC; else vs MA. LOCAL PROMOTIONS: none. Base chain: combine-cash (start) -> N (adopted 11-06) -> MA (adopted 11-07). Streak of completed rounds without promotion: 0 (rounds 3 and 4 complete with the F decisions below; round 5 was cancelled when the base moved, not a failed round). F EVIDENCE vs N (900000..903999), RC 3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f (https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb): f1 +0.467 se 0.111, f3 +0.470 se 0.162, f4 +0.560 se 0.118; pooled n 1500: +0.499 se 0.076 (sum_d 748.66, sum_d2 13438.05), s2 n 383 +0.845 se 0.198, s3 n 344 +1.235 se 0.242, d = 0 on every s1/s4 seed, retail -0.24 arb +0.74, 0 failures, worst seed -25.4. f2, f5, f6, f7, f8 still running (asked for). Episode 9: pool all 8 (mean = S/n, se = sqrt((Q - S*S/n)/(n-1)/n)); record RC as round 4's promotion over N on s2/s3 if n 4000, 0 failures, s2, s3 and overall each > 2 se; as an entry it is superseded by MA, so its live value depends on 75dd8e1e. retreat-crossing b5158a96 (s3): 7 of 8 blocks n 3448 +0.097 se 0.048, s3 n 828 +0.406 se 0.201; cross-f1 and cross-f5 rerun the lost blocks; promote on s3 over N only if all 8 complete and s3 and overall > 2 se; RC dominates it on s3 either way. ROUND 4 SCREEN vs N (H 430000..430499; r4-extend replicates on 430500..431999, merges 01 cancel, 02 s1-port, 03 s1-postjump, 04 s2-lowp, 05 s3-midsize, 06 s4-norisk): d-s1-retreat-crossing-port s1 +0.851 se 0.400; c-s1-queue-postjump s1 +0.496 se 0.262; c-s3-retreat-strength s3 +0.94 se 0.50; d-s2-lowp-early-bids s2 +0.117 se 0.054; d-s3-mid-size-up s3 +0.174 se 0.105; remove-s4-ask-risk-premium s4 +0.34 se 0.28. Use the merges to weigh r6-port's screens (same ideas on MA). Dead vs N: r3 extension rows (best s3-flow-transfer s3 +0.26 se 0.13), side-jump-budget, stock-entry-gate, all 56 blind overlays, every own-fill pull. Handed this episode, nothing new: sjb-b/c/d, reference-h-a-replica. ROUND 6 BATCHES (on MA, paired vs MA, d = 0 required off target, per-seed arrays, worst seeds): - r6-port (14, merges of 7 in item order: 01 = the five s1 items, p6-s4-retreat-cancel, p6-s4-no-ask-risk-premium; 02 = c6-s4-cancel-norisk and the s2/s3 items; T 340000..340199, H 450000..450999): p6-s1-retreat-crossing, p6-s1-queue-postjump, p6-s1-queue-safety, p6-s1-retreat-cancel (RC's wrapper guarded to s1), c6-s1-crossing-postjump, p6-s4-retreat-cancel, p6-s4-no-ask-risk-premium, c6-s4-cancel-norisk, p6-s2-lowp-early-bids, d6-s2-retreat-posterior, p6-s3-retreat-crossing, p6-s3-retreat-strength, p6-s3-mid-size-up, p6-s3-flow-transfer. All vs MA alone (a stacked check did not fit the brief). STACKING RECIPE for a wrapper port P on RC: MARC + two newlines + P's text from its line `_IncumbentStrategy = Strategy` to the end (the rebinding makes P subclass RC's class); a body-edit port needs a compose item. Each result carries the full file gzip+base64 and code_sha256; the merge's `top` carries the three best. - r6-fresh (7 blind overlays, merges of 4; T 340200..340399, H 450000..450499): f6-rival-vanish, f6-rival-two-tick, f6-retreat-both-sides, f6-rival-mid-shift, f6-advance-opposite, f6-consecutive-retreats, f6-retreat-size-half (rival-quote signals RC does not use, mostly s1 and s4). - r6-base-f (8 x 500, merges of 4): MA vs N on 900000..903999, keys base-f1..f8: MA's F means per block (the comparator means every episode-9 final must reproduce) and the chain's evidence N -> MA. - r5-diagnose (2, N on 510000..510499): d5-diag-retreat, d5-diag-advance (for the write-up). NEXT EPISODE (9), in order: 1. Integrity: drop rows with off_target_zero false, wrong check values, incomplete n, a flag, or a base mean on the same seeds unequal to the other rows'. 2. Scoreboard vs MA by spread from the r6 merges. Finalists: per spread the best row with gain_s > 2 se_s (fall back to > 1.5 se_s, at most one per spread), code as frozen in the merge's top. If RC-on-MA is reported positive, s2/s3 finals use comparator MARC and the stacking recipe (wrapper ports only). 3. Spawn r6-final-<key>: 8 x 500 over 900000..903999 per finalist, the r6-base-f brief with the candidate's result URL and hash and MA (or MARC) as comparator; merges of 4; read both merges. 4. Spawn r6-compose (2 items): compose-all = MA (+ RC's wrapper if positive) plus every finalist's wrapper chained in spread order, each guarded; compose-s14 = only the s1 and s4 finalists. Each: exact-equality audit against each source on its spread over 100 seeds (450000..450099) and against MA elsewhere, full code gzip+base64, code_sha256, little else. Also 8 x 500 F blocks of compose-all vs MA so the final file has its own F evidence. About 200 items remain: 8 a finalist plus 16 for the composed file. 5. Episode 10: promote per spread where pooled F gain_s > 2 se_s with 4000 complete and 0 failures; finish; the write-up takes the full code from the compose result (or the single finalist's result), F evidence from the finals, and the promotion table: round, spread, old and new hash, URL, F n, gain, se, retail and arb change. SEED LEDGER: exposed below 300000; round 3 T 310000..310199, H 410000..411999; SEG audit 420000..421999; diagnostics 500000..502499, 510000..510499; round 4 T 320000..320199, H 430000..431999; round 5 T 330000..330199, H 440000..440499; round 6 T 340000..340399, H 450000..450999; reserved T 350000.., H 460000..; never 700000..709999 (goal 75dd8e1e); F 900000..903999 only in final batches. LESSONS: never ask an item or a merge for a command's output; vars are strings; filled briefs under 3000 characters (URLs and hashes eat most of it); results under 64000 bytes; a result is served at https://api.imd.fun/artifacts/<its SHA-256>. Write-up limits: F reused across rounds and finalists; H common to a round's items; N and MA adopted from other goals; local paired gains are not a leaderboard result; --sandbox not run; round 6 is small because the base moved with two episodes left.
6 steps
r6-port, item by item r6-fresh, item by item r6-base-f, item by item
Round 9r7-compose2 of 2 back, cancelledr7-p-f8 of 8 back, cancelledr7-ma-fresh5 of 5 back, cancelledr7-s4-f5 of 5 back, cancelledr7-s4-fresh8 of 8 back, cancelledr7-dev5 of 13 back, 8 heldr7-remove4 of 6 back, 1 held, 1 failed
Agent #2 planned it, 3 attempts.
r7-ma-fresh: 5 released, 11 held.
r7-s4-f: 5 released, 3 held.
r7-dev: 5 released, 8 held.
r7-remove: 5 released, 1 held.
what r7-compose was asked
Audit item: {{idea}}. Simulator github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default config, 2000 steps, one process, never --workers or --sandbox; call sample_config, SimulationEngine and load_strategy_factory yourself per seed in chunks of 50 so no tool call passes 10 minutes; rerun lost seeds. Build the texts below; verify every sha first and stop on a mismatch, naming the part. Sources are the `code` field of the JSON at https://api.imd.fun/artifacts/<art>; hashes are SHA-256 of UTF-8 text; NL = two newlines; X[a -> b] = X with text a replaced by b. MA: art 149883fee797ad95a91e535b7a74453587a3eb19ca87ab95f7d8585db160a8f4, sha 5d1bd5272884f513b19f0e66a7c235f6c188a08e4f7787ac9346f1614dda3ed3. MB: art 6b40ef6fdf9512700501e6b92fb5c920955a97b29111faada6d411074173b7cd, sha 4f9167dddd457f394e988bf9c9e2576dd6120834bfb8d93573ce9451fd587598. W = RC (art 2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb) from its line `_IncumbentStrategy = Strategy` to the end. B_RC = MB + NL + W, sha 02696ea6fd0922f64167a1153748f6a38bf2fd5d87c7a4ac6cb974bb9482f57c. {{extra_defs}}{{recipe}}Run {{files}} on every seed 460000..460199; {{rule}} List failing seeds with both edges; report, do not repair. Result JSON under 64,000 bytes: key, idea, code (the whole {{main}} file, gzip then base64), code_sha256 (raw UTF-8), part_sha256 (each text), audit {seeds, n_by_spread, mismatches [seed, s, got, expected], all_equal}, seconds_per_simulation per file overall and by spread, python_version, check_values ({{main}} on seeds 310000..310003), failures, notes under 500 characters. Tune nothing.
what r7-p-f was asked
Measure-only item: {{idea}}. Simulator github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default config, 2000 steps, one process, never --workers or --sandbox; call sample_config, SimulationEngine and load_strategy_factory yourself per seed in chunks of 50 so no tool call passes 10 minutes; rerun lost seeds. Build C and K from the texts below and verify every SHA-256 first (on a mismatch report it and stop); run both on every seed {{start}}..{{end}} inclusive, the same seed each; d = C total_edge - K total_edge (unrounded); s = max(1, (ask - bid + 1)//2) from the first competitor quotes. Result JSON under 64,000 bytes: key, idea, candidate_sha256, comparator_sha256, seeds {start, end}, n, complete, missing_seeds, failures, check_values (K on seeds 310000..310003; {{check}}), python_version, seconds_per_simulation {candidate, comparator} overall and by spread (wall time of engine.run), overall and by_spread (1..4) each {n, sum_d, sum_d2, mean_diff, se, comparator_mean, retail_diff, arb_diff}, per_seed [seed, s, d] to 6 decimals for every seed, worst_seeds (10 lowest d: seed, s, d, both edges), off_target_zero (true iff d == 0 on every seed of spreads {{zero}}), notes under 600 characters. se = sd(d)/sqrt(n). A partial run is incomplete, never the measurement. No tuning, no code changes. Sources are the `code` field of the JSON at https://api.imd.fun/artifacts/<art>; hashes are SHA-256 of UTF-8 text; NL = two newlines; X[a -> b] = X with text a replaced by b. MA: art 149883fee797ad95a91e535b7a74453587a3eb19ca87ab95f7d8585db160a8f4, sha 5d1bd5272884f513b19f0e66a7c235f6c188a08e4f7787ac9346f1614dda3ed3. MB: art 6b40ef6fdf9512700501e6b92fb5c920955a97b29111faada6d411074173b7cd, sha 4f9167dddd457f394e988bf9c9e2576dd6120834bfb8d93573ce9451fd587598. W = RC (art 2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb) from its line `_IncumbentStrategy = Strategy` to the end. B_RC = MB + NL + W, sha 02696ea6fd0922f64167a1153748f6a38bf2fd5d87c7a4ac6cb974bb9482f57c. P = MA[`class Strategy(BaseStrategy):` -> `class _S1(BaseStrategy):`] + NL + MB[that line -> `class _S234(BaseStrategy):`] + NL + W[`_IncumbentStrategy = Strategy` -> `_IncumbentStrategy = _S234`, `class Strategy(` -> `class _BRC(`] + NL + PICK, these 10 lines exactly (4-space indents, one final newline): class Strategy(BaseStrategy): def __init__(self): self._inner = None def on_step(self, state): if self._inner is None: cb = state.competitor_best_bid_ticks or 0 ca = state.competitor_best_ask_ticks or 100 self._inner = _S1() if max(1, (ca - cb + 1) // 2) == 1 else _BRC() return self._inner.on_step(state) P sha 44f64ab14cfb4f0d0b88c5c42b1125d4950eb688117398a3ba0688c734ef1700. C = P. K = B_RC.
what r7-ma-fresh was asked
Measure-only item: {{idea}}. Simulator github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default config, 2000 steps, one process, never --workers or --sandbox; call sample_config, SimulationEngine and load_strategy_factory yourself per seed in chunks of 50 so no tool call passes 10 minutes; rerun lost seeds. Build C and K from the texts below and verify every SHA-256 first (on a mismatch report it and stop); run both on every seed {{start}}..{{end}} inclusive, the same seed each; d = C total_edge - K total_edge (unrounded); s = max(1, (ask - bid + 1)//2) from the first competitor quotes. Result JSON under 64,000 bytes: key, idea, candidate_sha256, comparator_sha256, seeds {start, end}, n, complete, missing_seeds, failures, check_values (K on seeds 310000..310003; {{check}}), python_version, seconds_per_simulation {candidate, comparator} overall and by spread (wall time of engine.run), overall and by_spread (1..4) each {n, sum_d, sum_d2, mean_diff, se, comparator_mean, retail_diff, arb_diff}, per_seed [seed, s, d] to 6 decimals for every seed, worst_seeds (10 lowest d: seed, s, d, both edges), off_target_zero (true iff d == 0 on every seed of spreads {{zero}}), notes under 600 characters. se = sd(d)/sqrt(n). A partial run is incomplete, never the measurement. No tuning, no code changes. Sources are the `code` field of the JSON at https://api.imd.fun/artifacts/<art>; hashes are SHA-256 of UTF-8 text; NL = two newlines; X[a -> b] = X with text a replaced by b. MA: art 149883fee797ad95a91e535b7a74453587a3eb19ca87ab95f7d8585db160a8f4, sha 5d1bd5272884f513b19f0e66a7c235f6c188a08e4f7787ac9346f1614dda3ed3. MB: art 6b40ef6fdf9512700501e6b92fb5c920955a97b29111faada6d411074173b7cd, sha 4f9167dddd457f394e988bf9c9e2576dd6120834bfb8d93573ce9451fd587598. W = RC (art 2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb) from its line `_IncumbentStrategy = Strategy` to the end. B_RC = MB + NL + W, sha 02696ea6fd0922f64167a1153748f6a38bf2fd5d87c7a4ac6cb974bb9482f57c. C = MA. K = B_RC.
what r7-s4-f was asked
Measure-only item: {{idea}}. Simulator github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default config, 2000 steps, one process, never --workers or --sandbox; call sample_config, SimulationEngine and load_strategy_factory yourself per seed in chunks of 50 so no tool call passes 10 minutes; rerun lost seeds. Build C and K from the texts below and verify every SHA-256 first (on a mismatch report it and stop); run both on every seed {{start}}..{{end}} inclusive, the same seed each; d = C total_edge - K total_edge (unrounded); s = max(1, (ask - bid + 1)//2) from the first competitor quotes. Result JSON under 64,000 bytes: key, idea, candidate_sha256, comparator_sha256, seeds {start, end}, n, complete, missing_seeds, failures, check_values (K on seeds 310000..310003; {{check}}), python_version, seconds_per_simulation {candidate, comparator} overall and by spread (wall time of engine.run), overall and by_spread (1..4) each {n, sum_d, sum_d2, mean_diff, se, comparator_mean, retail_diff, arb_diff}, per_seed [seed, s, d] to 6 decimals for every seed, worst_seeds (10 lowest d: seed, s, d, both edges), off_target_zero (true iff d == 0 on every seed of spreads {{zero}}), notes under 600 characters. se = sd(d)/sqrt(n). A partial run is incomplete, never the measurement. No tuning, no code changes. Sources are the `code` field of the JSON at https://api.imd.fun/artifacts/<art>; hashes are SHA-256 of UTF-8 text; NL = two newlines; X[a -> b] = X with text a replaced by b. MB: art 6b40ef6fdf9512700501e6b92fb5c920955a97b29111faada6d411074173b7cd, sha 4f9167dddd457f394e988bf9c9e2576dd6120834bfb8d93573ce9451fd587598. W = RC (art 2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb) from its line `_IncumbentStrategy = Strategy` to the end. B_RC = MB + NL + W, sha 02696ea6fd0922f64167a1153748f6a38bf2fd5d87c7a4ac6cb974bb9482f57c. W4 = W with every `_IncumbentStrategy` -> `_IncumbentStrategy4`, `_retreat_previous` -> `_retreat4_previous`, `_retreat_left` -> `_retreat4_left`, and `if self.s not in (2, 3):` -> `if self.s != 4:`. B_RC4 = B_RC + NL + W4, sha 27cef4140f19ecf15aeaa82c8a4bc70f9f066083a5bed10bcb963d8ecbb9b8aa. C = B_RC4. K = B_RC.
what r7-s4-fresh was asked
Measure-only item: {{idea}}. Simulator github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default config, 2000 steps, one process, never --workers or --sandbox; call sample_config, SimulationEngine and load_strategy_factory yourself per seed in chunks of 50 so no tool call passes 10 minutes; rerun lost seeds. Build C and K from the texts below and verify every SHA-256 first (on a mismatch report it and stop); run both on every seed {{start}}..{{end}} inclusive, the same seed each; d = C total_edge - K total_edge (unrounded); s = max(1, (ask - bid + 1)//2) from the first competitor quotes. Result JSON under 64,000 bytes: key, idea, candidate_sha256, comparator_sha256, seeds {start, end}, n, complete, missing_seeds, failures, check_values (K on seeds 310000..310003; {{check}}), python_version, seconds_per_simulation {candidate, comparator} overall and by spread (wall time of engine.run), overall and by_spread (1..4) each {n, sum_d, sum_d2, mean_diff, se, comparator_mean, retail_diff, arb_diff}, per_seed [seed, s, d] to 6 decimals for every seed, worst_seeds (10 lowest d: seed, s, d, both edges), off_target_zero (true iff d == 0 on every seed of spreads {{zero}}), notes under 600 characters. se = sd(d)/sqrt(n). A partial run is incomplete, never the measurement. No tuning, no code changes. Sources are the `code` field of the JSON at https://api.imd.fun/artifacts/<art>; hashes are SHA-256 of UTF-8 text; NL = two newlines; X[a -> b] = X with text a replaced by b. MB: art 6b40ef6fdf9512700501e6b92fb5c920955a97b29111faada6d411074173b7cd, sha 4f9167dddd457f394e988bf9c9e2576dd6120834bfb8d93573ce9451fd587598. W = RC (art 2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb) from its line `_IncumbentStrategy = Strategy` to the end. B_RC = MB + NL + W, sha 02696ea6fd0922f64167a1153748f6a38bf2fd5d87c7a4ac6cb974bb9482f57c. W4 = W with every `_IncumbentStrategy` -> `_IncumbentStrategy4`, `_retreat_previous` -> `_retreat4_previous`, `_retreat_left` -> `_retreat4_left`, and `if self.s not in (2, 3):` -> `if self.s != 4:`. B_RC4 = B_RC + NL + W4, sha 27cef4140f19ecf15aeaa82c8a4bc70f9f066083a5bed10bcb963d8ecbb9b8aa. C = B_RC4. K = B_RC.
what r7-dev was asked
Development item, one idea, spread {{spread}} only: {{idea}}. Simulator github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default config, 2000 steps, one process, never --workers or --sandbox; call sample_config, SimulationEngine and load_strategy_factory yourself per seed in chunks of 50 so no tool call passes 10 minutes; rerun lost seeds. Base {{base_name}}: {{base_def}}Verify its SHA-256 first. The candidate is a complete file: the base's text, two newlines, and a wrapper starting with the line `_IncumbentStrategy = Strategy` that defines `class Strategy(_IncumbentStrategy)` whose on_step calls super().on_step and then drops, adds or resizes actions (edit the base's body only where a wrapper cannot express the idea, and say so). Guard it with `self.s` so that on every other spread the candidate equals the base exactly (d == 0). Tune at most 3 settings on seeds 350000..350149 against the base, pick the best by paired mean, freeze, then measure the frozen file on holdout seeds 460200..460699, base and candidate on the same seeds, s = max(1, (ask - bid + 1)//2) from the first competitor quotes. Time both files (wall seconds per engine.run); an idea over 15% slower than the base on its spread is too slow. Result JSON under 64,000 bytes: key, idea, spread, base_sha256, approach (under 600 characters), tried (each setting with its tuning paired mean and se), next (one sentence), code (the whole candidate file, gzip then base64), code_sha256 (raw UTF-8), tuning {n, mean_diff, se}, holdout {n, complete, missing_seeds, failures, comparator_mean, mean_diff, se, sum_d, sum_d2, retail_diff, arb_diff}, by_spread (the same for 1..4), off_target_zero, worst_seeds (5 lowest holdout d: seed, s, d), seconds_per_simulation {candidate, base} on the target spread, check_values (the base's total_edge on seeds 310000..310003; {{check}}), python_version, notes under 600 characters. Never run seeds 900000..903999 or 700000..709999. An unfinished holdout is reported as incomplete.
what r7-remove was asked
Removal item, one deletion, no tuning: {{idea}}. Simulator github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default config, 2000 steps, one process, never --workers or --sandbox; call sample_config, SimulationEngine and load_strategy_factory yourself per seed in chunks of 50 so no tool call passes 10 minutes; rerun lost seeds. Base B_RC: MB: art 6b40ef6fdf9512700501e6b92fb5c920955a97b29111faada6d411074173b7cd, sha 4f9167dddd457f394e988bf9c9e2576dd6120834bfb8d93573ce9451fd587598. W = RC (art 2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb) from its line `_IncumbentStrategy = Strategy` to the end. B_RC = MB + NL + W, sha 02696ea6fd0922f64167a1153748f6a38bf2fd5d87c7a4ac6cb974bb9482f57c. Verify its SHA-256 first. Make the one deletion inside W's wrapper class (the last class of the file) and nothing else, so the candidate equals B_RC exactly on every spread the deletion does not touch. Measure the candidate against B_RC on seeds 460200..460699, both on the same seeds, s = max(1, (ask - bid + 1)//2) from the first competitor quotes. Result JSON under 64,000 bytes: key, idea, what_was_removed (the exact lines, under 600 characters), base_sha256, code (the whole candidate file, gzip then base64), code_sha256 (raw UTF-8), holdout {n, complete, missing_seeds, failures, comparator_mean, mean_diff, se, sum_d, sum_d2, retail_diff, arb_diff}, by_spread (the same for 1..4), off_target_zero, worst_seeds (5 lowest d: seed, s, d), seconds_per_simulation {candidate, comparator}, check_values (B_RC's total_edge on seeds 310000..310003; B_RC's are 17.512655, 24.258579, 2.390311, 249.541133), python_version, notes under 600 characters. A negative mean_diff means the removed part carries gain. Never run seeds 900000..903999 or 700000..709999.
the whole memo
EPISODE 9 (last spawning episode): RC promoted over N on spreads 2 and 3 from complete F evidence; base is the requester's B_RC; the picker P (MA on spread 1, B_RC elsewhere) and the spread-4 retreat cancel B_RC4 are deterministic texts sent to F now, with 13 development and 6 removal screens. Spawned 61 items in 7 batches; used after this about 494 of 600. Episode 10 reads, promotes per spread and finishes; it can spawn nothing readable. STANDINGS (requester 11-07 01:30Z, not live-checked): 1st Ponxter 110.69; 2nd us 110.43 with B_RC. Paradigm's sandbox stops a submission at about 270 s for 200 runs; B_RC took 215 s; MA plus RC's wrapper failed twice. Drop any candidate over 15% slower than B_RC (every batch reports seconds per simulation for both files by spread). BASE CHAIN (adopted, not promoted by our gate): combine-cash -> N (11-06) -> MA (11-07 00:30Z) -> B_RC (11-07 01:30Z). code = `code` field of https://api.imd.fun/artifacts/<art>; verified here. - N bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae. - MA 5d1bd5272884f513b19f0e66a7c235f6c188a08e4f7787ac9346f1614dda3ed3 (art 149883fee797ad95a91e535b7a74453587a3eb19ca87ab95f7d8585db160a8f4); check values (seeds 310000..310003) 17.116002, 23.820392, 2.376144, 243.87214. - MB 4f9167dddd457f394e988bf9c9e2576dd6120834bfb8d93573ce9451fd587598 (art 6b40ef6fdf9512700501e6b92fb5c920955a97b29111faada6d411074173b7cd). - RC 3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f (art 2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb) = N + "\n\n" + W; W = RC's text from `_IncumbentStrategy = Strategy` to the end. - B_RC = MB + "\n\n" + W, 02696ea6fd0922f64167a1153748f6a38bf2fd5d87c7a4ac6cb974bb9482f57c (the requester's hash); check values 17.512655, 24.258579, 2.390311, 249.541133. Goal 75dd8e1e: B_RC over MB +0.40 se 0.04. - P (picker) = MA renamed _S1, MB renamed _S234, W rebased on _S234 as _BRC, then a 10-line class Strategy reading s = max(1,(ask-bid+1)//2) from the first competitor quotes as MA and MB do and delegating on_step to _S1() if s == 1 else _BRC(); 44f64ab14cfb4f0d0b88c5c42b1125d4950eb688117398a3ba0688c734ef1700; recipe in the r7-compose and r7-p-f briefs. Smoke run here (seeds 310000..310009): P equals MA on spread-1 seeds and B_RC on the rest; about 1.4 s a simulation each. - W4 = W with `_IncumbentStrategy`->`_IncumbentStrategy4`, `_retreat_previous`->`_retreat4_previous`, `_retreat_left`->`_retreat4_left`, `if self.s not in (2, 3):`->`if self.s != 4:`. B_RC4 = B_RC + "\n\n" + W4, 27cef4140f19ecf15aeaa82c8a4bc70f9f066083a5bed10bcb963d8ecbb9b8aa (smoke: differs from B_RC only on s4). P4 = P with W4 rebased on _BRC as _BRC4 and the picker choosing _BRC4 for s != 1; ffa425242e7514591810c2b9d7873495d8ee17b68d523566895359744ef385d3 (smoke: MA on s1, B_RC4 on s4, B_RC elsewhere). PROMOTIONS (ranked, for the write-up): 1. Round 4, spreads 2 and 3, N -> RC: F 900000..903999 complete, n 4000, 0 failures, hashes verified; overall +0.537 se 0.048; s2 n 1017 +1.079 se 0.145; s3 n 961 +1.093 se 0.123; d = 0 on every s1/s4 seed; retail about -0.12, arb about +0.66 per run; worst seed -25.4; blocks +0.35 to +0.72 (f7 source-flagged, numbers agree); N's F mean about 103.5. The same wrapper makes B_RC. Runner-up, not promoted: retreat-crossing b5158a963a479a0919146dc0d56a347b68ddc2d66dd7c467b48473baef8997cf (s3 posterior reweight on a one-tick rival retreat) vs N, n about 3948: overall +0.108 se 0.043, s3 n 951 +0.45 se 0.18; clears the gate on s3, but RC gains twice as much there and the combination on RC screened -0.18 se 0.18, so RC holds s3. Streak without promotion: 0 (round 4 promoted; round 5 cancelled when the base moved; round 6 still runs). OTHER EVIDENCE: MA vs N on F 900000..901999 (n 2000): +1.020 se 0.167 (s1 +1.00/0.54, s2 +2.06/0.35, s3 +0.60/0.17, s4 +0.41/0.10; worst s1 seeds -98.5, -93.9). Round 4 extension vs N (1500 seeds): d-s3-mid-size-up s3 +0.32 se 0.14 (ported now); remove-s4-ask-risk-premium s4 -0.68 se 0.28 (raised now); s1 ports dead. Round 5 vs RC: nothing positive; best d5-s4-cancel-port s4 +0.36 se 0.26 (hence B_RC4 to F); 67 blind overlays over four rounds, none gained: fresh lane closed, width went to measurement. Diagnostics on N: same-side arb loss after a one-tick rival retreat 2.40/1.93/1.81/1.04 per run for spreads 1..4 (s1, s4 untreated); after rival inward moves or both-quote shifts the next-step move rate is 22-29% vs 14-15%: these drive r7-dev. BATCHES NOW (measure items return per_seed [seed, s, d], worst seeds, timing by spread, off_target_zero): - r7-compose (2, handed as items): compose-p audits P = MA on s1 seeds and = B_RC elsewhere over 460000..460199 and times P, MA, B_RC; compose-p4 likewise for P4. Each returns the full file gzip+base64 and its SHA (must match above). - r7-p-f (8 x 500 over F, merges of 4): P vs B_RC; only s1 may differ (d == 0 on s2-4 seeds is the equality audit at scale). - r7-ma-fresh (16 x 500 over 920000..927999, merges of 4): MA vs B_RC per spread; its s1 d equals P's, so it replicates r7-p-f on s1 (pool by sum_d/sum_d2); s2-4 show which base wins where. - r7-s4-f (8 x 500 over F) and r7-s4-fresh (8 x 500 over 930000..933999), merges of 4: B_RC4 vs B_RC; only s4 differs. - r7-dev (13, merges of 4; T 350000..350149, H 460200..460699; keys d7-*): three s1 ideas on MA (bid cancel on rival ask-down, ask cancel on bid-up, both-shift pause); on B_RC: bid cancel on ask-down and both-shift pause for s2, s3, s4; s3 mid-size-up; s4 retreat cancel bid-only and with a 2-callback cooldown; s4 ask-risk premium up. Full file gzip+base64 and SHA each; merges' `top` holds the best two. - r7-remove (6, merges of 3, vs B_RC on 460200..460699; keys x7-*): drop the bid or ask trigger on s2 or s3, drop the suppression, drop the probe clearing; negative d = the part carries gain. - Still running: r6-port (14 on MA), r6-fresh (7), r6-base-f merge-02; merges asked for. EPISODE 10, in order: 1. Integrity: a block counts only if complete (n 500), 0 failures, hashes as above, check values right, off_target_zero true where required; pool by mean = S/n, se = sqrt((Q - S*S/n)/(n-1)/n), overall and per spread. 2. Spread 1: promote P over B_RC if r7-p-f is complete (n 4000) and its s1 gain > 2 se, with r7-ma-fresh's s1 as replication (report both and the pool), compose-p all_equal, P's timing within 15% of B_RC's. Spread 4: promote B_RC4 (as P4 if s1 is also promoted) if r7-s4-f's s4 gain > 2 se with n 4000, r7-s4-fresh agreeing in sign, compose-p4 all_equal, timing within 15%. The final file is then P4, P, B_RC4 or B_RC, each with its hash above; the write-up's code is the compose item's `code` (decoded SHA must match) or B_RC by recipe. 3. Promotion table rows: round, spread, old and new hash, URL or recipe, F n, gain, se, retail and arb change, worst seeds, timing. RC's row first. 4. r7-dev, r7-remove, r6-port and r6-fresh are screens (500 seeds, selected): list them ranked per spread as next candidates with hashes, never as promotions; name any over 15% slower. 5. Set finish=true. Write-up: the final file's full code and hash, its F evidence per spread, the promotion table, the base chain, and the limits: F reused across rounds and finalists; H common to a round's items; N, MA and B_RC adopted, not promoted; local paired gains are not a leaderboard result; --sandbox not run; the 270 s limit known only as worker-machine timing. SEED LEDGER: exposed below 300000; T 310000..350149 by round; H 410000..411999, 430000..431999, 440000..440499, 450000..460699; diagnostics 420000..421999, 500000..502499, 510000..510499; fresh measure 920000..933999; never 700000..709999 (goal 75dd8e1e); F 900000..903999 used by RC, retreat-crossing, MA vs N, P, B_RC4. LESSONS: filled briefs under 3000 characters, merge briefs under 1500, vars strings under 1000 (two attempts of this episode failed on these); never ask for a command's output; results under 64,000 bytes, served at https://api.imd.fun/artifacts/<its SHA-256>.
1 step
r7-compose, item by item r7-p-f, item by item r7-ma-fresh, item by item r7-s4-f, item by item r7-s4-fresh, item by item r7-dev, item by item r7-remove, item by item
Round 10r8-t-ablaterefused, never ranr8-t-frefused, never ranr8-t-portrefused, never ran
Agent #2 planned it.
The plane refused 18 of its decisions. The next round is told why.
what r8-t-ablate was asked
Measure-only item, no development, no tuning: {{idea}}. Simulator github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig and ParameterVariance, 2000 steps, one process, never --workers or --sandbox; call sample_config, SimulationEngine and load_strategy_factory yourself per seed in chunks of 50 so no tool call passes 10 minutes; rerun lost seeds. Comparator K = {{base_def}} Candidate C = {{cand_def}} Verify every SHA-256 by script before running; on a mismatch report it and run nothing. Check values first: K on seeds 310000..310003 gives total_edge {{k_check}}; C gives {{c_check}}; report both with pass flags and stop if either differs. Then run C and K on every seed {{start}}..{{end}} (500 seeds, the same seed to both). Per seed record s = the sampled config's competitor.spread_ticks (1 to 4; a run has one spread), d = C total_edge minus K total_edge, and the retail and arbitrage parts of d. {{zero_rule}} Result JSON under 60000 bytes: key, candidate_sha256, comparator_sha256, seeds, n, complete (true only if all 500 seeds ran; else missing seeds), failures (count and seeds), check_values, python_version, seconds_per_simulation for C and for K, overall {n, sum_d, sum_d2, mean_diff, se, comparator_mean, candidate_mean, retail_diff, arb_diff}, by_spread {the same for s = 1, 2, 3, 4}, off_target_zero, per_seed as a list of [seed, s, d to 6 decimals], worst_seeds (the five lowest d with seed, s, d), notes under 1000 characters. se = sqrt((sum_d2 - sum_d*sum_d/n)/(n-1)/n). Never report a partial block as the measurement. Use no seed outside the range given. Report fields only, never a command's output, and nothing about the machine you run on.
what r8-t-f was asked
Measure-only item, no development, no tuning: {{idea}}. Simulator github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default ChallengeConfig and ParameterVariance, 2000 steps, one process, never --workers or --sandbox; call sample_config, SimulationEngine and load_strategy_factory yourself per seed in chunks of 50 so no tool call passes 10 minutes; rerun lost seeds. Comparator K = {{base_def}} Candidate C = {{cand_def}} Verify every SHA-256 by script before running; on a mismatch report it and run nothing. Check values first: K on seeds 310000..310003 gives total_edge {{k_check}}; C gives {{c_check}}; report both with pass flags and stop if either differs. Then run C and K on every seed {{start}}..{{end}} (500 seeds, the same seed to both). Per seed record s = the sampled config's competitor.spread_ticks (1 to 4; a run has one spread), d = C total_edge minus K total_edge, and the retail and arbitrage parts of d. {{zero_rule}} Result JSON under 60000 bytes: key, candidate_sha256, comparator_sha256, seeds, n, complete (true only if all 500 seeds ran; else missing seeds), failures (count and seeds), check_values, python_version, seconds_per_simulation for C and for K, overall {n, sum_d, sum_d2, mean_diff, se, comparator_mean, candidate_mean, retail_diff, arb_diff}, by_spread {the same for s = 1, 2, 3, 4}, off_target_zero, per_seed as a list of [seed, s, d to 6 decimals], worst_seeds (the five lowest d with seed, s, d), notes under 1000 characters. se = sqrt((sum_d2 - sum_d*sum_d/n)/(n-1)/n). Never report a partial block as the measurement. Use no seed outside the range given. Report fields only, never a command's output, and nothing about the machine you run on.
what r8-t-port was asked
Development item, spread {{spread}} only: port {{key}} onto T as one more ON-table entry and screen it paired against T. Idea: {{idea}}. Simulator github.com/danrobinson/prediction-market-challenge at b244530ee2a6247b5f930830eeca9dd950da0e7e, unmodified, default config, 2000 steps, one process, never --workers or --sandbox; seeds in chunks of 50 so no tool call passes 10 minutes. T (live entry): the `code` field of the JSON at https://api.imd.fun/artifacts/79af781a0f1882f2a291e045f803714b52128f9938480d54fb43360417b381ac ; SHA-256 9fba1eb5659d5b0ac9b7273a968a520ef9a95551c697be22020993005af70192. T is MA plus changes gated per spread by its line 34 `ON = dict(cancel=(2, 3, 4), cut=(1, 4), postjump=(1,), premium=(), deadband=(3,))`. MA: the `code` field of the JSON at https://api.imd.fun/artifacts/149883fee797ad95a91e535b7a74453587a3eb19ca87ab95f7d8585db160a8f4 ; SHA-256 5d1bd5272884f513b19f0e66a7c235f6c188a08e4f7787ac9346f1614dda3ed3. Source S = MA plus this change, screened vs MA on 1000 seeds: {{screen}}. S is the `code` field of the JSON at https://api.imd.fun/artifacts/{{src}} (gzip+base64 of the full file, or plain text); decoded SHA-256 {{src_sha}}. Verify all three hashes by script; stop on a mismatch. Port: diff S against MA; apply the same change to T, every changed behaviour guarded by a new entry {{entry}} in ON on line 34: entry empty = T exactly, ({{spread}},) = acts on spread {{spread}} only; keep the source's constants, tune nothing. Checks: T on seeds 310000..310003 gives total_edge 17.899934, 24.258579, 2.433424, 259.215142; the candidate with the entry empty must match; report both, stop if not. Then run the candidate (entry ({{spread}},)) and T on every seed {{start}}..{{end}} (1000 seeds, the same seed to both); per seed record s = the sampled config's competitor.spread_ticks, d = candidate total_edge minus T total_edge, and its retail and arbitrage parts; d must be exactly 0 where s is not {{spread}}. If not all seeds finish, report complete chunks and the missing seeds, never a partial chunk. Result JSON under 60000 bytes: key, entry, code (full candidate file, gzip+base64, under 48000 bytes), code_sha256 (of the decoded text), port_notes (lines changed, under 1200 characters), check_values, python_version, seconds_per_simulation for candidate and T, n, complete, missing_seeds, failures, overall {n, sum_d, sum_d2, mean_diff, se, comparator_mean, retail_diff, arb_diff}, by_spread {the same for s = 1..4}, off_target_zero, per_seed [seed, s, d to 6 decimals] written compactly, worst_seeds (five lowest d), next (under 400 characters). se = sqrt((sum_d2 - sum_d*sum_d/n)/(n-1)/n). Never seeds 900000..903999. Report fields only, never a command's output, nothing about your machine.
the whole memo
EPISODE 10 (last): the goal is reached and finish is set. The requester's 02:05Z note: we are 1st on Paradigm's board at 110.87 (2nd Ponxter 110.69, 3rd 109.59) with file T, goal 7be68b75's x-plus-b, which carries this goal's retreat cancel (RC), a belief cut after a one-tick retreat and the spread-1 postjump wrapper, gated per spread by one ON table. T replaces B_RC as the file to beat. This episode spawned the requester's two remaining asks (45 items, all against T) and cancelled the P/B_RC measurements T supersedes; their results are public artifacts for the requester whether or not a write-up step reads them. Used after this about 519 of 600. FINAL FILE T (adopted, verified here): the `code` field of https://api.imd.fun/artifacts/79af781a0f1882f2a291e045f803714b52128f9938480d54fb43360417b381ac , SHA-256 9fba1eb5659d5b0ac9b7273a968a520ef9a95551c697be22020993005af70192, 43168 bytes, 897 lines, submittable as is (the write-up's code is this field; the artifact digest and code hash both verified). Check values (unmodified simulator b244530e, seeds 310000..310003, total_edge): 17.899934, 24.258579, 2.433424, 259.215142; MA's on the same seeds 17.116002, 23.820392, 2.376144, 243.87214. Timing here: T 1.35 s a simulation, MA 1.37. T = MA plus, on line 34, `ON = dict(cancel=(2, 3, 4), cut=(1, 4), postjump=(1,), premium=(), deadband=(3,))`: cancel = RC's wrapper (one-callback cancel of the side whose rival quote retreated one tick), cut = belief weight x0.016 on the stale side after a one-tick retreat, postjump = spread-1 jump-withhold wrapper plus qb_z = 4, premium = spread-4 ask risk premium change (off), deadband = keep_lo replaced by 1 in add_b/add_a. T's own evidence (its artifact): over MA on seeds 170000..170999 +1.227 se 0.354 (s1 +1.40/0.75, s2 +0.63/0.18, s3 +1.13/0.51, s4 +1.68/1.02); on Paradigm +0.66; its per-entry keep decisions rest on 60 runs a spread (cancel s3 +1.16 se 0.30 and s4 +0.66 se 0.22 clearest; cut s1 +0.91 se 0.43; cancel s1 dropped at +0.91 se 1.05; cut s2 -1.30 se 2.68, s3 -0.23 se 0.39). BASE CHAIN (adopted on requester notes, not promoted by our gate): combine-cash baef955e (start) -> N bf0d179f (11-06; +1.45 se 0.16 over the 108.47 file) -> MA 5d1bd527 (11-07 00:30Z; https://api.imd.fun/artifacts/149883fee797ad95a91e535b7a74453587a3eb19ca87ab95f7d8585db160a8f4) -> B_RC 02696ea6 (01:30Z; MB 4f9167dd + RC's wrapper; +0.40 se 0.04 over MB, goal 75dd8e1e) -> T (02:05Z). F evidence for the chain on 900000..903999 vs N: MA n 4000 in two halves, 900000..901999 +1.020 se 0.167 (r6-base-f/merge-01) and 902000..903999 +1.496 se 0.476 (merge-02; one seed 903835 at +904; without it +1.044 se 0.150), per spread on the second half s1 +1.28/0.30, s2 +3.51/1.84, s3 +0.54/0.16, s4 +0.60/0.13, arb +1.94 retail -0.44. r8-t-f (8 x 500 on F) adds T vs MA. PROMOTION TABLE (ranked; only one promotion passed our gate): 1. Round 4, spreads 2 and 3, N -> RC 3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f (https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb = N plus the cancel wrapper): F 900000..903999 complete, n 4000, 0 failures (r5-final/cancel-f1..f8): overall +0.537 se 0.048; s2 n 1017 +1.079 se 0.145; s3 n 961 +1.093 se 0.123; d = 0 on every s1/s4 seed; retail about -0.12, arb +0.66 per run; worst seed -25.4; blocks +0.35 to +0.72; N's F mean about 103.5. The same wrapper is T's cancel entry (on 2, 3, 4) and B_RC's, which carried the board from 110.21 to 110.43. Runner-up, not promoted: retreat-crossing b5158a96 (s3 belief reweight on a one-tick retreat) vs N, n 3948: overall +0.108 se 0.043, s3 +0.45 se 0.18; RC gains twice as much on s3 and their combination on RC screened -0.18 se 0.18. T's cut entry is this family's descendant. ROUND 6 SCREENS ON MA (H 450000..450999, candidate minus MA, target spread; r6-port/merge-02; selected 1000-seed screens, not promotions; code in the merge's top gzip+base64): d6-s2-retreat-posterior 58daa7d8 s2 n 270 +1.958 se 0.382 (retail +2.20), overall +0.529 se 0.107; p6-s3-retreat-strength d79cf349 s3 +0.689 se 0.209; p6-s3-mid-size-up d2daff28 s3 +0.217 se 0.089 (on N: +0.32 se 0.14 over 1500 seeds); p6-s3-retreat-crossing b4a16d6c s3 +0.378 se 0.213; p6-s2-lowp-early-bids a99aded5 s2 +0.123 se 0.091; c6-s4-cancel-norisk e37648a8 s4 +0.546 se 0.414; p6-s3-flow-transfer cc046a2f s3 +0.176 se 0.190. r6-port/merge-01 (five s1 ports, two s4) was still waiting on one item. Blind overlays: all 7 of r6-fresh at or below zero on their targets (74 blind overlays over five rounds, none gained). r7-dev (13 screens on MA/B_RC) and r7-remove (6 deletions of the wrapper's parts on B_RC) were still in their canaries; read as screens if handed. SPAWNED NOW, all paired against T: - r8-t-ablate (32 = 4 variants x 8 blocks of 500 on fresh seeds 940000..943999; merges 01 cancel, 02 cut, 03 pjpr, 04 dead): the requester's ask (a). Each variant is T with its line 34 replaced, so one variant's per-spread d tests one ON entry per spread (off where T had it on, on where off). V-cancel 90b340f87fe2db61623bb201f21460d38e9d07f2be9a8845b585be017cc1146a (cancel=(1,)); V-cut 92504562 (cut=(2, 3)); V-pjpr 3df90643 (postjump=(), premium=(4,); d = 0 on s2/s3); V-dead 81302517 (deadband=(1, 2, 4)). All four ran here on the check seeds without failures at T's speed. Reading: an entry flips when the pooled d on its spread exceeds 2 se in the direction of the change; n about 1000 a spread. - r8-t-f (8 x 500 on F 900000..903999, merges of 4): T vs MA, the chain's last link on the finalist seeds. - r8-t-port (5, one merge): the requester's ask (b), ports of the round-6 winners onto T as new ON entries, each screened on 1000 fresh seeds (950000..954999): posterior on s2 twice (independent ports, different seeds), strength on s3, midsize on s3, lowp on s2. Each returns a complete file gzip+base64 with its SHA and timing; a port over 15 percent slower than T is dropped. Pool everything by mean = S/n, se = sqrt((Q - S*S/n)/(n-1)/n) from n, sum_d, sum_d2, overall and per spread; a block counts only if complete (n 500), 0 failures, hashes as above, check values right. Cancelled: r7-p-f, r7-ma-fresh, r7-s4-f, r7-s4-fresh, r7-compose (P and B_RC4 measurements; T is MA-based and the requester moved the base). WRITE-UP: the full code is T's `code` field (hash above) with the ON line explained; evidence = T's own holdout and board figures, the chain's F evidence (MA vs N complete; T vs MA from r8-t-f if handed), RC's F promotion row, and the ablation verdicts per entry if handed (which entries to flip); the ranked table has one promotion (RC) and the runner-up. Limits to state: F reused across rounds and finalists; H common to a round's items (screens are selected); N, MA, B_RC and T were adopted from sibling goals on the requester's notes, not promoted through our gate; local paired gains are not a leaderboard result; --sandbox was never run; Paradigm's 270 s limit is known only from the requester and worker timing; the ablation and port results, if not handed, are public at https://api.imd.fun/artifacts/<result SHA-256> under batches r8-t-ablate, r8-t-f and r8-t-port. SEED LEDGER: exposed below 300000; T 310000..350149; H 410000..411999, 430000..431999, 440000..440499, 450000..460699; diagnostics 420000..421999, 500000..502499, 510000..510499; measure 920000..933999 (cancelled), 940000..943999, 950000..954999; never 700000..709999 (goal 75dd8e1e), never 150000..150999 or 170000..170999 (T's own); F 900000..903999 used by RC, retreat-crossing, MA vs N, P, B_RC4 (cancelled) and T vs MA.
1 step
Write-upAgent #1299accepted
Its attempts
JudgeAgent #204accepted
Its attempts
Publishedresearch report
Onchain2 receiptson Ethereum mainnet
receipt
receipt 1 · transaction · record
receipt
receipt 2 · transaction · record
scores
written, with no entries recorded on it · block 26,360,538 · transaction
scores
written, with no entries recorded on it · block 26,360,512 · transaction

150 agents at most, 55 of 72 merges, judge accepted, 5 notes

Outputs

1,005 files accepted

batches/55 files2.1 MB
- r2-deepen-b/merges/01/result.md48 KB
- r2-deepen-b/merges/02/result.md45 KB
- r2-deepen-b/merges/03/result.md50 KB
- r2-deepen-b/merges/04/result.md42 KB
- r2-diagnose/merges/01/result.md54 KB
- r2-diagnose/merges/02/result.md62 KB
- r2-fresh-b/merges/01/result.md33 KB
- r2-fresh-b/merges/02/result.md36 KB
- r2-fresh-b/merges/03/result.md24 KB
- r3-deepen-current/merges/01/result.md61 KB
- r3-deepen-current/merges/02/result.md60 KB
- r3-deepen-current/merges/03/result.md43 KB
- r3-deepen-current/merges/04/result.md63 KB
- r3-extend/merges/01/result.md52 KB
- r3-extend/merges/02/result.md31 KB
- r3-extend/merges/03/result.md33 KB
- r3-extend/merges/04/result.md35 KB
- r3-extend/merges/05/result.md27 KB
- r3-extend/merges/06/result.md34 KB
- r3-extend/merges/07/result.md30 KB
- r3-extend/merges/08/result.md24 KB
- r3-extend/merges/09/result.md25 KB
- r3-fresh-overlay/merges/01/result.md20 KB
- r3-fresh-overlay/merges/02/result.md25 KB
- r3-fresh-overlay/merges/03/result.md20 KB
- r3-fresh-overlay/merges/04/result.md28 KB
- r3-fresh-overlay/merges/05/result.md27 KB
- r3-remove-current/merges/01/result.md60 KB
- r3-remove-current/merges/02/result.md30 KB
- r4-deepen/merges/01/result.md43 KB
- r4-deepen/merges/02/result.md36 KB
- r4-deepen/merges/03/result.md45 KB
- r4-deepen/merges/04/result.md62 KB
- r4-extend/merges/01/result.md38 KB
- r4-extend/merges/02/result.md48 KB
- r4-extend/merges/03/result.md31 KB
- r4-extend/merges/04/result.md30 KB
- r4-extend/merges/05/result.md40 KB
- r4-extend/merges/06/result.md34 KB
- r4-fresh/merges/01/result.md52 KB
- r4-fresh/merges/02/result.md58 KB
- r4-fresh/merges/03/result.md53 KB
- r4-remove/merges/01/result.md60 KB
- r4-remove/merges/02/result.md11 KB
- r5-deepen/merges/01/result.md54 KB
- r5-deepen/merges/02/result.md47 KB
- r5-deepen/merges/03/result.md55 KB
- r5-deepen/merges/04/result.md50 KB
- r5-fresh/merges/01/result.md27 KB
- r5-fresh/merges/02/result.md22 KB
- r6-base-f/merges/01/result.md6 KB
- r6-base-f/merges/02/result.md7.1 KB
- r6-fresh/merges/01/result.md16 KB
- r6-fresh/merges/02/result.md26 KB
- r6-port/merges/02/result.md62 KB
episodes/10 files518 KB
items/940 files14 MB

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