# edge-strategy-reviewer

A deterministic quality gate for strategy drafts: checks edge plausibility, overfitting risk and execution realism, then returns PASS, REVISE or REJECT.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 3400 installs · ★ 3267
- Author: tradermonty
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/tradermonty/claude-trading-skills/tree/HEAD/skills/edge-strategy-reviewer/SKILL.md
- Updated: 2026-10-24
- HTML: https://affpapa.org/en/nevibecode/skills/edge-strategy-reviewer

## What it does

The skill reads YAML drafts produced by `edge-strategy-designer` and scores each one against eight weighted criteria. Those cover edge plausibility (weight 20), overfitting risk (20), sample adequacy (15), regime dependency, exit calibration, risk concentration, execution realism and invalidation quality. A weighted average becomes the confidence score, and the score drives the verdict.

The verdict logic is blunt. A fail on C1 or C2 means an immediate REJECT. Confidence of 70 or higher with no fail findings gives PASS, anything below 35 is REJECT, and the rest lands in REVISE with revision instructions attached. Export eligibility is checked separately: you need PASS, `export_ready_v1` and an exportable family.

Everything runs through `review_strategy_drafts.py`. It needs Python 3.10+ with PyYAML, plus either a `--drafts-dir` directory or a single `--draft` file. Flags include `--format json`, `--markdown-summary`, `--strict-export` and `--bias-checklist`. That last one acts as a mandatory strategy-research bias gate: leave a required item unaddressed and a PASS drops to REVISE with export eligibility gone. No PyYAML means the script never starts, so check that first.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill edge-strategy-reviewer -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/edge-strategy-reviewer/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/edge-strategy-reviewer/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill edge-strategy-reviewer -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/edge-strategy-reviewer/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill edge-strategy-reviewer -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/edge-strategy-reviewer/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install tradermonty/claude-trading-skills edge-strategy-reviewer
```

2. **Manually: put the files in place**
- File: `.github/skills/edge-strategy-reviewer/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill edge-strategy-reviewer -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/tradermonty/claude-trading-skills --path skills/edge-strategy-reviewer
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/edge-strategy-reviewer/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill edge-strategy-reviewer -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/tradermonty/claude-trading-skills/tree/HEAD/skills/edge-strategy-reviewer/SKILL.md

## When to use it
- filter overfit strategy drafts before they reach export
- replace a gut feeling with a numeric confidence score
- check whether the sample actually supports the claimed edge
- see which criteria failed and what to rewrite
- block export of a strategy with an unaddressed research bias

## Example prompts
- review the drafts in reports/edge_strategy_drafts/ and list the verdicts
- run review_strategy_drafts.py on draft_xxx.yaml with json output
- run the check with --bias-checklist and tell me which items are unaddressed

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: e12d58e30d146311.

BEGIN THIRD-PARTY FILE e12d58e30d146311
````text
---
name: edge-strategy-reviewer
description: >
  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.
---

# 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 \
````
END THIRD-PARTY FILE e12d58e30d146311

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