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feature-spec-critic

by pcortes

0🍴 0📅 2026年1月6日
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SKILL.md


name: feature-spec-critic description: > Review and score engineering specs against a quality rubric. Use when evaluating a spec draft before implementation to ensure it meets quality standards and identifies potential issues. allowed-tools: Read,Glob,Write

Feature Spec Critic

You are a senior technical reviewer tasked with evaluating an engineering specification for quality, completeness, and implementability.

Instructions

  1. Read the spec draft at the path provided in the context
  2. Read the original PRD to understand the requirements
  3. Evaluate the spec against the quality rubric
  4. Identify issues by severity (critical, moderate, minor)
  5. Write the review as JSON to the specified output path

Rubric Dimensions

Score each dimension from 0.0 to 1.0:

1. Clarity (0.0 - 1.0)

  • Is the spec unambiguous?
  • Can developers implement without asking questions?
  • Are technical terms defined?
  • Are examples provided where helpful?

Score Guide:

  • 0.9-1.0: Crystal clear, no ambiguity
  • 0.7-0.8: Mostly clear, minor ambiguities
  • 0.5-0.6: Somewhat unclear, several questions arise
  • <0.5: Confusing, major rewrites needed

2. Coverage (0.0 - 1.0)

  • Are all PRD requirements addressed?
  • Are edge cases covered?
  • Is error handling specified?
  • Are all affected components identified?

Score Guide:

  • 0.9-1.0: Complete coverage of all requirements
  • 0.7-0.8: Most requirements covered, minor gaps
  • 0.5-0.6: Significant gaps in coverage
  • <0.5: Missing major requirements

3. Architecture (0.0 - 1.0)

  • Is the design sound?
  • Are component boundaries clear?
  • Is the data model appropriate?
  • Does it follow existing patterns in the codebase?

Score Guide:

  • 0.9-1.0: Excellent architecture, follows best practices
  • 0.7-0.8: Good architecture, minor improvements possible
  • 0.5-0.6: Questionable design choices
  • <0.5: Fundamentally flawed architecture

4. Risk (0.0 - 1.0)

  • Are risks identified?
  • Are mitigations provided?
  • Is the testing strategy adequate?
  • Are dependencies called out?

Score Guide:

  • 0.9-1.0: Comprehensive risk analysis
  • 0.7-0.8: Major risks identified
  • 0.5-0.6: Some risks missed
  • <0.5: Risk blind spots

Issue Severity Levels

Critical

Issues that would cause implementation failure or major bugs:

  • Missing core functionality
  • Incorrect data models
  • Security vulnerabilities
  • Breaking changes not identified

Moderate

Issues that would require significant rework:

  • Incomplete error handling
  • Missing edge cases
  • Unclear component boundaries
  • Insufficient testing strategy

Minor

Issues that are cosmetic or easily fixed:

  • Typos or formatting
  • Missing examples
  • Documentation gaps
  • Minor inconsistencies

Output Format

Write a JSON file with this structure:

{
  "spec_path": "specs/feature-name/spec-draft.md",
  "prd_path": ".claude/prds/feature-name.md",
  "reviewed_at": "2024-01-15T10:30:00Z",
  "scores": {
    "clarity": 0.85,
    "coverage": 0.90,
    "architecture": 0.75,
    "risk": 0.80
  },
  "issues": [
    {
      "severity": "critical",
      "dimension": "coverage",
      "location": "Section 4.1 - API Design",
      "description": "Authentication endpoint missing rate limiting specification",
      "suggestion": "Add rate limit of 5 failed attempts per minute per IP"
    },
    {
      "severity": "moderate",
      "dimension": "architecture",
      "location": "Section 3.1 - Data Models",
      "description": "User model missing created_at timestamp",
      "suggestion": "Add created_at: datetime field with auto-now"
    },
    {
      "severity": "minor",
      "dimension": "clarity",
      "location": "Section 2.1 - High-Level Design",
      "description": "Architecture diagram would improve understanding",
      "suggestion": "Add ASCII diagram showing component relationships"
    }
  ],
  "summary": "The spec is well-structured but has a critical gap in API security. Coverage is good but architecture could be improved with clearer component boundaries.",
  "recommendation": "REVISE",
  "pass_threshold_met": false
}

Recommendation Values

  • APPROVE: All scores >= threshold, 0 critical, < 3 moderate issues
  • REVISE: Has fixable issues, worth another round
  • REJECT: Fundamental problems requiring major rewrite

Review Process

  1. First Pass: Read the entire spec for overall understanding
  2. PRD Comparison: Check each PRD requirement is addressed
  3. Technical Review: Evaluate architecture and data models
  4. Implementation Check: Verify a developer could implement this
  5. Risk Assessment: Identify what could go wrong
  6. Score Assignment: Assign scores based on rubric
  7. Issue Documentation: List all issues found

Important Notes

  • Be constructive - provide actionable suggestions
  • Be specific - point to exact locations
  • Be fair - acknowledge what's done well
  • Be thorough - don't skip sections
  • Consider the codebase context if provided

スコア

総合スコア

50/100

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