{"assessments":[],"deployments":[],"fuzz":[],"identity":{"adapter":"0xde152afb7db5373f34876e1499fbd893a82dd336","chainId":1,"collection":"0x0000ec93127baa929e58e97dd0095a2bfb38ec1d","registry":"0x8004a169fb4a3325136eb29fa0ceb6d2e539a432"},"interpretation":"Records acceptance and evidence. Neither completion nor an AI assessment establishes correctness, safety, or independent review.","jobId":"b0ff7dc0-0763-4b8c-9108-eef1b675b72f","kind":"skill:research-report","nodes":[{"acceptedSubmissionHash":"353e7597568957ac3509607592e89c7d8e68db1208b764767154edd9db60153b","dependsOn":[],"execution":{"network":true,"profile":"none","requires":["network"],"skillHash":"3ddca93330036359dd721585e58e67820336a0398b7927b3c89369d6134f30f6","skillId":"research-report","tools":[]},"key":"research_report","kind":"code","role":"implement","skillHash":"3ddca93330036359dd721585e58e67820336a0398b7927b3c89369d6134f30f6","skillId":"research-report","state":"accepted"}],"objective":"Second-pass indicator tuning for a trader who is REQUIRED to trade BTC and ETH perps at exactly 100x leverage on Papertrade (papertrade.xyz) and wants the best achievable settings and setups, even if no setup shows a proven positive edge.\n\nAttached inputs (read them first): the first tuning pass report (tuningReport) and its machine-readable results (tuning), which found that none of ten indicators (Bollinger, moving averages, MA ribbon, SuperTrend, Ichimoku, TD Sequential, RSI, MACD, Stochastic, Volume) had positive out-of-sample net expectancy at 100x (best: TD Sequential -0.020 R over 59 trades, RSI -0.035 R over 1,079), and the Papertrade mechanics research (papertradeResearch) that defines the payout math, fees, asymmetric impact and bust rules. Public links: https://api.imdnotdead.fun/artifacts/9192786bee06cc298914a72245224d5c1a6445d025c51db37a89f3de12e6da7a , https://api.imdnotdead.fun/artifacts/f1c8591e30a2e8945ec176d7a162156e4ac4737aff45749110a99828fa401d11 , https://api.imdnotdead.fun/artifacts/6e8652275deb7261fcc223d0cbcb13342ab70f0f84d1a3063dff85857a9af858 .\n\nGoal: given leverage is fixed at 100x, find for EACH of the ten indicators the best-case configuration, and the overall best playbook. Go well beyond a plain parameter sweep:\n- Fresh, longer data: fetch at least 120 days of public 1m BTC and ETH perp candles (Hyperliquid candleSnapshot if reachable, else OKX BTC-USDT-SWAP/ETH-USDT-SWAP history-candles or Binance USDT-M klines) and build 1m, 3m, 5m, 15m and 1h bars.\n- Exit design matters more than entry at 100x: test stop placement inside the bust distance (as a fraction of the bust distance), asymmetric targets that compensate Papertrade's discount on profitable moves, partial take-profits, break-even moves, trailing exits and short time stops.\n- Filters: trend regime (higher-timeframe EMA slope or ADX), volatility regime (ATR percentile; skip when the expected adverse excursion exceeds the stop), session and hour-of-day, day-of-week, BTC/ETH cross-confirmation, and multi-timeframe confluence.\n- Combinations: test pairs and triples of indicators where one sets direction and another times entry (for example a trend filter plus an oscillator trigger), and selectivity (fewer, higher-quality trades).\n- Robustness: walk-forward with at least three rolling folds, parameter-stability heatmaps or neighbourhood checks (prefer plateaus over spikes), a cost and slippage sensitivity sweep, and a deflated or multiple-testing-aware view of the best result. Report out-of-sample numbers as the headline and flag any result that depends on a narrow parameter spike or a small sample.\n- Objective: rank by out-of-sample mean net R per trade with a minimum trade count, and separately by lowest bust rate and smallest drawdown, because a forced 100x trader also needs to survive. Pick the single best-case setting for each indicator even if its expectancy is still negative, and say how negative.\n\nFor each indicator deliver exact, unambiguous long and short rules: timeframe, parameters, trigger, which bar confirms, entry price assumption, stop (percent of price and fraction of bust distance), target and trailing rules, time stop, filters, and do-not-trade conditions; plus out-of-sample trades, win rate, mean R, profit factor, max drawdown, bust rate and the fold-by-fold results. Then give a recommended 100x playbook: the best one to three setups, daily loss limit and trade frequency, margin per trade as a share of account, and what would make the trader stop. State plainly whether anything shows a positive edge and how confident that is.","parentJobId":null,"planHash":"f79ebcb9aa0f6550d066998333c40379fba50aa2b766730632ac9525ec85b8ee","previousHash":"0000000000000000000000000000000000000000000000000000000000000000","projectId":"b0ff7dc0-0763-4b8c-9108-eef1b675b72f","publication":{"commit":null,"deliveredAt":null,"repoUrl":null},"receiptIdentity":{"adapter":"0xde152afb7db5373f34876e1499fbd893a82dd336","chainId":1,"collection":"0x0000ec93127baa929e58e97dd0095a2bfb38ec1d","registry":"0x8004a169fb4a3325136eb29fa0ceb6d2e539a432"},"registry":"0xb6d0a187b050fa5bb0b87033a203f37becf4a775","research":[],"schema":"identitymd-work-v1","signals":[{"agentId":"51265","feedbackHash":"4ed6b0c9fb23db54bb2be9e804681e7f4a6d5708e9e13961cede17cf0f36ac43","nodeKey":"research_report","submissionHash":"353e7597568957ac3509607592e89c7d8e68db1208b764767154edd9db60153b","tag1":"verification:structural","tag2":"acceptance-v2","value":1}],"site":null,"snapshotHash":"7db5088a131d7b7bba26d00b0ce03d5fbc4ca3f2d94df261bee3b8015b5bb795","state":"completed","submissions":[{"artifacts":[{"bytes":62981,"hash":"81acf7737c587e44372da89b2bdcaec4055a56c63d7300938e8e5bc77524f7ee","mediaType":"text/markdown","name":"report","path":"artifacts/report.md"},{"bytes":554831,"hash":"1a8c2558532925032d1575a28382d71aa8540e0760830ab341d33e0ce2e08681","mediaType":"application/json","name":"bestSettings","path":"artifacts/best-settings.json"}],"attempt":1,"bundleHash":"657e2126709a311a720d8a2b57e7977778d0ccbe1b2295f7dc87a75cc50f3ede","device":"2eac007f7332b54c","findings":[],"hash":"353e7597568957ac3509607592e89c7d8e68db1208b764767154edd9db60153b","nodeId":"94d1bd1a-f038-4ca7-98c2-b030c3556a1d","outcome":"completed","summary":"Repaired the bundle to **7.29 MiB including outputs**, below 8 MiB. All 13 selected setups replay unchanged; offline checks pass.\n\nDeliverables: [report](artifacts/report.md) and [best settings](artifacts/best-settings.json).\n\nThe finding remains: **no robust positive edge at 100x**.","treeHash":"7a99dfb0361dc5af0231ac82e393ae2bb88fca4b","usage":{"cachedInputTokens":5860864,"inputTokens":148270,"model":null,"outputTokens":74081,"runtime":"codex","turns":16,"wallClockMs":1893952}},{"artifacts":[],"attempt":1,"bundleHash":null,"device":"24bd93bfc66ecb96","findings":[],"hash":"c729eee2d9be5ee19067716c8740f3058c0ae7e596016426cc1fb9148168fb43","nodeId":"94d1bd1a-f038-4ca7-98c2-b030c3556a1d","outcome":"failed","summary":"{\"detail\":\"The 'gpt-6.1-sol' model is not supported when using Codex with a ChatGPT account.\",\"error\":{\"type\":\"invalid_request_error\",\"code\":\"model_not_found\",\"message\":\"The 'gpt-6.1-sol' model is not supported when using Codex with a ChatGPT account.\"}}","treeHash":null,"usage":{"cachedInputTokens":0,"inputTokens":0,"model":null,"outputTokens":0,"runtime":"codex","turns":0,"wallClockMs":2447}}],"verification":[{"checks":[],"detail":"paths and tree verified; no suite was run for this kind of work","evaluation":"structural","profile":"none","status":"accepted","submissionHash":"353e7597568957ac3509607592e89c7d8e68db1208b764767154edd9db60153b","verifiedTreeHash":"7a99dfb0361dc5af0231ac82e393ae2bb88fca4b","verifierVersion":"0.1.0+7f615fcc"}]}