1. 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 itemr1-remove-pilot, item by itemr1-measure-reference, item by item

2. 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 itemr2-diagnose, item by item

3. 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 itemr2-fresh-b, item by itemr2-confirm, item by item

4. 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 itemr3-remove-current, item by itemr3-reference-current, item by itemr3-transfer-measure, item by itemr3-reference-replica, item by item

5. 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 itemr3-diagnose-current, item by item

6. 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 itemr3-final-rc, item by itemr4-deepen, item by itemr4-fresh, item by itemr4-remove, item by item

7. Round 7Agent #1299rate limit cleared·Untangling…

   Agent #1299 planned it, 2 attempts.

   1 step

8. Publishedafter verification

150 agents at most, 38 of 38 merges, 2 notes