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mphinance/alpha-skills

edge-strategy-reviewer

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.

First seen May 9, 2026

Installation

$ npx skills add mphinance/alpha-skills --skill edge-strategy-reviewer
View on skills.sh ↗ GitHub repository ↗

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Also listed on

Alternate registries and mirrors of this skill.

Repository health

Stars 21
License LICENSE
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,553 B
  • docs README.md 3,553 B
  • docs SUMMARY.md 323 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 86 installs

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 + exportreadyv1 + 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

# 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)

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