# Edge Strategy Reviewer

> >

- **Type:** Skill
- **Install:** `agentstack add skill-tradermonty-claude-trading-skills-edge-strategy-reviewer`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [tradermonty](https://agentstack.voostack.com/s/tradermonty)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [tradermonty](https://github.com/tradermonty)
- **Source:** https://github.com/tradermonty/claude-trading-skills/tree/main/skills/edge-strategy-reviewer
- **Website:** https://tradermonty.github.io/claude-trading-skills/

## Install

```sh
agentstack add skill-tradermonty-claude-trading-skills-edge-strategy-reviewer
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [tradermonty](https://github.com/tradermonty)
- **Source:** [tradermonty/claude-trading-skills](https://github.com/tradermonty/claude-trading-skills)
- **License:** MIT
- **Homepage:** https://tradermonty.github.io/claude-trading-skills/

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-tradermonty-claude-trading-skills-edge-strategy-reviewer
- Seller: https://agentstack.voostack.com/s/tradermonty
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.
