Turn trade logs, journal notes, and market observations into ranked trading hypotheses that experiments can test and disprove. Produce cards with experiment designs and stopping criteria, with optional strategy file exports for hypotheses marked for further investigation.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Generate falsifiable trade strategy hypotheses from market data, trade logs, and journal snippets. Use when you have a structured input bundle and want ranked hypothesis cards with experiment designs, kill criteria, and optional strategy.yaml export compatible with edge-finder-candidate/v1.
실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Generate 1-5 structured hypothesis cards from a normalized input bundle, critique and rank them, then optionally export pursue cards into strategy.yaml + metadata.json artifacts.
trade_log, journal_snippets, market_data, observationspyyaml installedprompts/system_prompt.mdprompts/developer_prompt_template.md (inject {{evidence_summary}})prompts/critique_prompt_template.md.pursue hypotheses via Step H strategy exporter.python3 skills/trade-hypothesis-ideator/scripts/run_hypothesis_ideator.py \
--input skills/trade-hypothesis-ideator/examples/example_input.json \
--output-dir reports/
python3 skills/trade-hypothesis-ideator/scripts/run_hypothesis_ideator.py \
--input skills/trade-hypothesis-ideator/examples/example_input.json \
--hypotheses reports/raw_hypotheses.json \
--output-dir reports/ \
--export-strategies
hypothesis_cards_<date>.json — Ranked hypothesis cards with verdicts (pursue, revise, discard)hypothesis_cards_<date>.md — Human-readable summary with experiment designs and kill criteriastrategy_<hypothesis_id>.yaml — (Optional) Edge-finder-compatible strategy export for pursue cardsmetadata_<hypothesis_id>.json — (Optional) Provenance metadata for exported strategiesreferences/hypothesis_types.md — Taxonomy of hypothesis patterns (mean-reversion, momentum, event-driven, etc.)references/evidence_quality_guide.md — Criteria for rating evidence strength and sample size requirements아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Plan and assess backtests, which test trading rules against historical data. Examine sensitivity to rule changes, trading costs, and data bias, then use supplied performance metrics to generate a structured evaluation with reasons that block adoption.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Assess how broadly US stock market gains are shared across stocks using public CSV data and optional charts. Produce English reports covering market conditions, trading signals, scenarios, and positioning for different investment timeframes.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Analyze chart images showing how broadly US stocks are participating in market trends. Assess medium-term conditions and short-term signals, then produce an English report with positioning guidance, alternative scenarios, and risks based on the visible data.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Turn VCP screening results, which identify narrowing price swings, into breakout trade plans. Calculate entry, stop-loss, target prices, and position sizes using worst-case entries, while applying portfolio risk limits and producing Alpaca-compatible order templates.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Screen US growth stocks with William O'Neil's CANSLIM method, which evaluates seven factors including earnings, price strength, trading volume, and market direction. Receive ranked candidates with composite scores, factor breakdowns, market warnings, and data quality notes.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Combine three reports on crowded positions, failed reactions to news, and weekly price reversals into one trading setup status. Identify missing or invalid evidence and determine whether the setup is ready for planning.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.