MCPInstall

edge-strategy-reviewer

Critically review strategy drafts from edge-strategy-designer for edge plausibility, overfitting risk, sample size adequacy, and execution realism. Use when strategydrafts/.yaml exists and needs quality gate before pipeline export. Outputs PASS/REVISE/REJECT verdicts with confidence scores.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/tradermonty/claude-trading-skills --skill edge-strategy-reviewer
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads edge-strategy-reviewer automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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

#CriterionWeightKey Checks
C1Edge Plausibility20Thesis quality, domain terms, mechanism keywords (continuous 50-95)
C2Overfitting Risk205-tier filter count scoring (90/80/60/40/10), precise threshold penalty
C3Sample Adequacy15Continuous scoring from estimated annual opportunities (10-95)
C4Regime Dependency10Cross-regime validation
C5Exit Calibration10Stop-loss, reward-to-risk
C6Risk Concentration10Position sizing limits
C7Execution Realism10Volume filter, export consistency
C8Invalidation Quality5Signal 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

# 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

Output Format

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: []

Resources

  • references/review_criteria.md — Detailed scoring rubric for C1-C8
  • references/overfitting_checklist.md — Overfitting detection heuristics

FAQ

What does the edge-strategy-reviewer skill do?

Critically review strategy drafts from edge-strategy-designer for edge plausibility, overfitting risk, sample size adequacy, and execution realism. Use when strategydrafts/.yaml exists and needs quality gate before pipeline export. Outputs PASS/REVISE/REJECT verdicts with confidence scores.

How do I install edge-strategy-reviewer?

Run npx skills add https://github.com/tradermonty/claude-trading-skills --skill edge-strategy-reviewer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/edge-strategy-reviewer/ (personal) or .claude/skills/edge-strategy-reviewer/ (project).

Which AI agents can use edge-strategy-reviewer?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is edge-strategy-reviewer safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains edge-strategy-reviewer?

It is published by tradermonty in tradermonty/claude-trading-skills. It has 3,436 recorded installs.

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