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Research · Business / AGENT SKILL
edge-strategy-reviewer
0
Review trading strategy drafts for plausible edge, overfitting, sample adequacy, and execution realism.
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.
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Original instructions from the publisher’s SKILL.md
# Edge Strategy Reviewer
Deterministic quality gate for strategy drafts produced by `edge-strategy-designer`.
## When to Use
- After `edge-strategy-designer` generates `strategy_drafts/*.yaml`
- Before exporting drafts to `edge-candidate-agent` via the pipeline
- When manually validating a draft strategy for edge plausibility
## Prerequisites
- Strategy draft YAML files (output of `edge-strategy-designer`)
- Python 3.10+ with PyYAML
## Workflow
1. Load draft YAML files from `--drafts-dir` or a single `--draft` file
2. Evaluate each draft against 8 criteria (C1-C8) with weighted scoring
3. Compute confidence score (weighted average of all criteria)
4. Determine verdict: PASS / REVISE / REJECT
5. Assess export eligibility (PASS + export_ready_v1 + exportable family)
6. Write review output (YAML or JSON) and optional markdown summary
## Review Criteria
| # | 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 |
## Verdict Logic
- C1 or C2 severity=fail → immediate REJECT
- confidence >= 70, no fail findings → PASS
- confidence < 35 → REJECT
- Otherwise → REVISE (with revision instructions)
## Running the Script
```bash
# 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
```
## Output Format
Primary output: `review.yaml` (or `review.json`)
```yaml
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: []
```
## Resources
- `references/review_criteria.md` — Detailed scoring rubric for C1-C8
- `references/overfitting_checklist.md` — Overfitting detection heuristics