tomwangowa

spec-review-assistant

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# Install this skill:
npx skills add tomwangowa/agent-skills --skill "spec-review-assistant"

Install specific skill from multi-skill repository

# Description

Review specification documents before implementation to identify gaps, ambiguities, and potential issues. Use when the user provides a spec document or asks to review requirements, design, or tasks.

# SKILL.md


name: spec-review-assistant
description: Review specification documents before implementation to identify gaps, ambiguities, and potential issues. Use when the user provides a spec document or asks to review requirements, design, or tasks.


Spec Review Assistant

Purpose

This Skill performs pre-implementation reviews of specification documents to:
1. Completeness Check: Identify missing sections or information
2. Feasibility Assessment: Evaluate technical approach and identify risks
3. Clarity Check: Detect ambiguous descriptions and contradictions
4. Workload Estimation: Assess task breakdown and identify missing subtasks
5. Codebase Integration (Optional): Verify alignment with existing architecture

The Skill helps prevent costly rework by catching specification gaps early.


Instructions

When the user requests a spec review (for example: "review this spec", "check my requirements doc", "audit this design document"), follow these steps:

Execution Steps

  1. Locate the specification document
  2. Ask for the file path if not provided
  3. Confirm the document format (should be Markdown)
  4. Read the entire document

  5. Run the review script
    bash bash scripts/review_spec.sh <spec_file_path> [--with-codebase]

  6. Use --with-codebase flag if reviewing for an existing project
  7. The script will analyze the document across all dimensions

  8. Present the structured review report

  9. Display the complete report with severity levels
  10. Highlight critical issues first
  11. Provide actionable recommendations

  12. Offer next steps

  13. Ask if the user wants to:
    • Address specific issues
    • Generate an improved version of the spec
    • Add missing sections
    • Clarify ambiguous parts

Review Dimensions

1. Completeness Check

Verifies presence of essential sections:
- Background/Context: Why this project exists
- Requirements: Functional and non-functional requirements
- Technical Design: Architecture, data models, APIs
- Error Handling: Edge cases and error scenarios
- Security Considerations: Auth, data protection, vulnerabilities
- Testing Strategy: Unit, integration, E2E tests
- Deployment Plan: How to roll out
- Success Metrics: How to measure success

2. Feasibility Assessment

Evaluates technical approach:
- Technology choices alignment with stack
- Performance implications
- Scalability concerns
- Third-party dependencies risks
- Timeline realism
- Resource requirements

3. Clarity Check

Identifies unclear descriptions:
- Vague terms: "fast", "simple", "appropriate", "should be good"
- Undefined acronyms or jargon
- Contradictory statements
- Inconsistent terminology
- Missing acceptance criteria

4. Workload Estimation

Analyzes task breakdown:
- Tasks too large to estimate
- Missing subtasks (testing, documentation, error handling)
- Underestimated complexity
- Dependencies not accounted for
- Suggested task decomposition

5. Codebase Integration (Optional)

When --with-codebase is used:
- Scan existing code structure
- Compare naming conventions
- Check API design patterns
- Identify architectural misalignment
- Suggest integration points


Output Format

The script generates a structured Markdown report:

# Spec Review Report: [Document Name]

**Review Date**: YYYY-MM-DD
**Document Version**: [if specified]
**Reviewer**: Spec Review Assistant

---

## Executive Summary

**Overall Assessment**: ⚠️ Needs Improvement
**Critical Issues**: 3
**Important Issues**: 7
**Suggestions**: 12

**Recommendation**: Address critical and important issues before implementation.

---

## 1. Completeness Check

### ✅ Present Sections
- Background
- Requirements
- Technical Design

### ❌ Missing Sections (Critical)
1. **Error Handling Strategy**
   - Impact: High risk of undefined behavior
   - Recommendation: Add section covering error scenarios, retry logic, fallback behavior

2. **Security Considerations**
   - Impact: Potential vulnerabilities
   - Recommendation: Document authentication, authorization, input validation, data encryption

### ⚠️ Incomplete Sections
1. **Requirements** (Line 23-45)
   - Issue: Missing non-functional requirements
   - Recommendation: Add performance, scalability, availability requirements

---

## 2. Feasibility Assessment

### 🟢 Strengths
- Technology stack is well-established
- Architecture follows existing patterns

### 🔴 Concerns
1. **Database Schema Complexity** (Line 89)
   - Issue: Proposed schema requires 5 joins for main query
   - Risk: Performance degradation at scale
   - Recommendation: Consider denormalization or caching layer

2. **Third-Party API Dependency** (Line 112)
   - Issue: Critical flow depends on external service with 99% SLA
   - Risk: 1% downtime = user-facing failures
   - Recommendation: Implement circuit breaker and fallback mechanism

---

## 3. Clarity Check

### Ambiguous Descriptions
1. **Line 56**: "The system should respond quickly"
   - Issue: "Quickly" is subjective
   - Recommendation: Specify target: "p95 latency < 200ms"

2. **Line 78**: "Handle errors appropriately"
   - Issue: "Appropriately" is undefined
   - Recommendation: Specify: log, retry, user notification strategy

### Contradictions
1. **Lines 34 vs 67**
   - Line 34: "Real-time updates required"
   - Line 67: "Polling every 30 seconds"
   - Recommendation: Clarify: use WebSocket for real-time or adjust requirement

### Undefined Terms
- **MTP** (Line 45): Not defined - clarify if "Minimum Testable Product"
- **Quantum sync** (Line 92): Unclear technical term

---

## 4. Workload Estimation

### Task Breakdown Analysis

#### ✅ Well-Defined Tasks
- "Implement user authentication API" - clear scope

#### ⚠️ Tasks Needing Decomposition
1. **"Build dashboard"** (Task #3)
   - Too broad - suggest breakdown:
     - Design dashboard layout
     - Implement data fetching layer
     - Create chart components
     - Add filtering and sorting
     - Write unit tests
     - Add E2E tests

2. **"Integrate payment gateway"** (Task #5)
   - Missing subtasks:
     - Research gateway options
     - Handle webhook setup
     - Implement refund flow
     - Add fraud detection
     - Test in sandbox

#### Missing Tasks
- Database migration scripts
- API documentation
- Monitoring and alerting setup
- Performance testing
- Security audit

---

## 5. Codebase Integration Analysis

### Alignment with Existing Code
✅ **Follows existing patterns**:
- REST API conventions match current endpoints
- Error response format consistent

⚠️ **Deviations detected**:
1. **Naming Convention** (Line 89)
   - Spec uses: `getUserData()`
   - Codebase uses: `fetchUserProfile()`
   - Recommendation: Align with `fetch*` pattern

2. **Database Access**
   - Spec proposes: Direct SQL queries
   - Current pattern: ORM (Prisma)
   - Recommendation: Use existing ORM or document rationale for change

---

## Summary of Recommendations

### 🔴 Critical (Must Fix Before Implementation)
1. Add error handling strategy section
2. Document security considerations
3. Define ambiguous performance requirements
4. Clarify contradictions (real-time vs polling)

### 🟡 Important (Address Soon)
1. Decompose overly broad tasks
2. Add missing testing and documentation tasks
3. Specify concrete acceptance criteria
4. Align naming conventions with codebase

### 🟢 Nice to Have
1. Add sequence diagrams for complex flows
2. Include rollback procedures
3. Document monitoring strategy

---

## Next Steps

1. **Immediate**: Address all critical issues
2. **Before kickoff**: Resolve important issues
3. **Optional**: Implement nice-to-have improvements
4. **Re-review**: Run this check again after updates

---

**Generated by**: Spec Review Assistant (Claude Code Skill)
**Powered by**: Gemini AI for semantic analysis

Constraints

  • Only works with Markdown (.md) files
  • Requires Gemini CLI for AI-powered semantic analysis
  • Codebase integration requires being run from project root
  • Best results with specs following a standard template

Trigger Phrases

Users can invoke this Skill by saying:
- "Review this spec"
- "Check my requirements document"
- "Audit this design doc"
- "Validate the specification"
- "Find gaps in this spec"
- "Is this spec ready for implementation?"


Examples

Example 1: Basic Spec Review

User:

Review the spec in docs/user-auth-spec.md

Expected behavior:
1. Read the spec document
2. Run review_spec.sh docs/user-auth-spec.md
3. Display structured review report
4. Offer to help address identified issues


Example 2: Spec Review with Codebase Integration

User:

Check if docs/payment-integration.md fits our existing architecture

Expected behavior:
1. Read the spec document
2. Run review_spec.sh docs/payment-integration.md --with-codebase
3. Scan existing codebase for patterns
4. Report both spec issues and architectural alignment
5. Suggest integration points


Example 3: Targeted Review

User:

Does this spec have all the required sections?

Expected behavior:
1. Run completeness check specifically
2. List missing sections
3. Suggest templates for missing parts


Best Practices

For Spec Authors

  • Use clear, specific language
  • Include acceptance criteria
  • Document assumptions explicitly
  • Add diagrams for complex flows

For Reviewers

  • Run this check before design review meetings
  • Address critical issues first
  • Use the report as discussion guide
  • Re-run after making changes

Integration with Workflow

1. Author writes spec → 2. Run Spec Review Skill → 3. Address issues →
4. Team review meeting → 5. Final approval → 6. Begin implementation

Git Hook Integration (Optional)

Add to .git/hooks/pre-commit:

# Auto-review specs before committing
if [[ "$file" == docs/specs/*.md ]]; then
  claude-skill spec-review-assistant "$file"
fi

Future Enhancements

  • Support for other formats (Google Docs, Notion)
  • Template library for common spec types
  • Automated spec improvement suggestions
  • Integration with project management tools
  • Historical analysis (compare spec vs actual implementation)

  • pr-review-assistant: Reviews code changes
  • commit-msg-generator: Generates commit messages
  • code-review-gemini: Reviews code quality

Use Spec Review Assistant BEFORE implementation, and PR Review Assistant DURING/AFTER implementation.

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.