Review trading strategy drafts against eight criteria, including the rationale for an advantage, overfitting to past data, sample size, and realistic execution. Produce a scored verdict, revision instructions, and eligibility for export to the next pipeline stage.
中文简介正在准备中。当前显示英语简介。
Critically review strategy drafts from edge-strategy-designer for edge plausibility, overfitting risk, sample size adequacy, and execution realism. Use when strategy_drafts/*.yaml exists and needs quality gate before pipeline export. Outputs PASS/REVISE/REJECT verdicts with confidence scores.
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Deterministic quality gate for strategy drafts produced by edge-strategy-designer.
edge-strategy-designer generates strategy_drafts/*.yamledge-candidate-agent via the pipelineedge-strategy-designer)--drafts-dir or a single --draft file| # | Criterion | Weight | Key Checks |
|---|---|---|---|
| C1 | Edge Plausibility | 20 | Thesis quality, domain terms, mechanism keywords (continuous 50-95) |
| C2 | Overfitting Risk | 20 | 5-tier filter count scoring (90/80/60/40/10), precise threshold penalty |
| C3 | Sample Adequacy | 15 | Continuous scoring from estimated annual opportunities (10-95) |
| C4 | Regime Dependency | 10 | Cross-regime validation |
| C5 | Exit Calibration | 10 | Stop-loss, reward-to-risk |
| C6 | Risk Concentration | 10 | Position sizing limits |
| C7 | Execution Realism | 10 | Volume filter, export consistency |
| C8 | Invalidation Quality | 5 | Signal count and specificity |
# Review all drafts in a directory
python3 skills/edge-strategy-reviewer/scripts/review_strategy_drafts.py \
--drafts-dir reports/edge_strategy_drafts/ \
--output-dir reports/
# Single draft review
python3 skills/edge-strategy-reviewer/scripts/review_strategy_drafts.py \
--draft reports/edge_strategy_drafts/draft_xxx.yaml \
--output-dir reports/
# JSON output with markdown summary
python3 skills/edge-strategy-reviewer/scripts/review_strategy_drafts.py \
--drafts-dir reports/edge_strategy_drafts/ \
--output-dir reports/ \
--format json \
--markdown-summary
# Strict export mode: export-eligible drafts with any warn → REVISE
python3 skills/edge-strategy-reviewer/scripts/review_strategy_drafts.py \
--drafts-dir reports/edge_strategy_drafts/ \
--output-dir reports/ \
--strict-export
# Bias checklist (issue #297): mandatory strategy-research bias gate.
# Uses the bundled checklist unless a custom YAML path is supplied.
# A draft leaving any required item unaddressed is downgraded PASS → REVISE
# and loses export eligibility.
python3 skills/edge-strategy-reviewer/scripts/review_strategy_drafts.py \
--drafts-dir reports/edge_strategy_drafts/ \
--output-dir reports/ \
--bias-checklist
Primary output: review.yaml (or review.json)
generated_at_utc: "2026-02-28T12:00:00+00:00"
source:
drafts_dir: "/path/to/strategy_drafts"
draft_count: 4
summary:
total: 4
PASS: 1
REVISE: 2
REJECT: 1
export_eligible: 1
reviews:
- draft_id: "draft_xxx_core"
verdict: "PASS"
confidence_score: 80
export_eligible: true
findings: [...]
revision_instructions: []
references/review_criteria.md — Detailed scoring rubric for C1-C8references/overfitting_checklist.md — Overfitting detection heuristics还没有评价。欢迎分享你的使用感受。
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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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。