Agent skill

unified-review

Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/unified-review

SKILL.md

Table of Contents

  • Quick Start
  • When to Use
  • Review Skill Selection Matrix
  • Workflow
  • 1. Analyze Repository Context
  • 2. Select Review Skills
  • 3. Execute Reviews
  • 4. Integrate Findings
  • Review Modes
  • Auto-Detect (default)
  • Focused Mode
  • Full Review Mode
  • Quality Gates
  • Deliverables
  • Executive Summary
  • Domain-Specific Reports
  • Integrated Action Plan
  • Modular Architecture
  • Exit Criteria

Unified Review Orchestration

Intelligently selects and executes appropriate review skills based on codebase analysis and context.

Quick Start

bash
# Auto-detect and run appropriate reviews
/full-review

# Focus on specific areas
/full-review api          # API surface review
/full-review architecture # Architecture review
/full-review bugs         # Bug hunting
/full-review tests        # Test suite review
/full-review all          # Run all applicable skills

Verification: Run pytest -v to verify tests pass.

When to Use

  • Starting a full code review
  • Reviewing changes across multiple domains
  • Need intelligent selection of review skills
  • Want integrated reporting from multiple review types
  • Before merging major feature branches

Review Skill Selection Matrix

Codebase Pattern Review Skills Triggers
Rust files (*.rs, Cargo.toml) rust-review, bug-review, api-review Rust project detected
API changes (openapi.yaml, routes/) api-review, architecture-review Public API surfaces
Test files (test_*.py, *_test.go) test-review, bug-review Test infrastructure
Makefile/build system makefile-review, architecture-review Build complexity
Mathematical algorithms math-review, bug-review Numerical computation
Architecture docs/ADRs architecture-review, api-review System design
General code quality bug-review, test-review Default review

Workflow

1. Analyze Repository Context

  • Detect primary languages from extensions and manifests
  • Analyze git status and diffs for change scope
  • Identify project structure (monorepo, microservices, library)
  • Detect build systems, testing frameworks, documentation

2. Select Review Skills

python
# Detection logic
if has_rust_files():
    schedule_skill("rust-review")
if has_api_changes():
    schedule_skill("api-review")
if has_test_files():
    schedule_skill("test-review")
if has_makefiles():
    schedule_skill("makefile-review")
if has_math_code():
    schedule_skill("math-review")
if has_architecture_changes():
    schedule_skill("architecture-review")
# Default
schedule_skill("bug-review")

Verification: Run pytest -v to verify tests pass.

3. Execute Reviews

  • Run selected skills concurrently
  • Share context between reviews
  • Maintain consistent evidence logging
  • Track progress via TodoWrite

4. Integrate Findings

  • Consolidate findings across domains
  • Identify cross-domain patterns
  • Prioritize by impact and effort
  • Generate unified action plan

Review Modes

Auto-Detect (default)

Automatically selects skills based on codebase analysis.

Focused Mode

Run specific review domains:

  • /full-review api → api-review only
  • /full-review architecture → architecture-review only
  • /full-review bugs → bug-review only
  • /full-review tests → test-review only

Full Review Mode

Run all applicable review skills:

  • /full-review all → Execute all detected skills

Quality Gates

Each review must:

  1. Establish proper context
  2. Execute all selected skills successfully
  3. Document findings with evidence
  4. Prioritize recommendations by impact
  5. Create action plan with owners

Deliverables

Executive Summary

  • Overall codebase health assessment
  • Critical issues requiring immediate attention
  • Review frequency recommendations

Domain-Specific Reports

  • API surface analysis and consistency
  • Architecture alignment with ADRs
  • Test coverage gaps and improvements
  • Bug analysis and security findings
  • Performance and maintainability recommendations

Integrated Action Plan

  • Prioritized remediation tasks
  • Cross-domain dependencies
  • Assigned owners and target dates
  • Follow-up review schedule

Modular Architecture

All review skills use a hub-and-spoke architecture with progressive loading:

  • pensive:shared: Common workflow, output templates, quality checklists
  • Each skill has modules/: Domain-specific details loaded on demand
  • Cross-plugin deps: imbue:evidence-logging, imbue:diff-analysis/modules/risk-assessment-framework

This reduces token usage by 50-70% for focused reviews while maintaining full capabilities.

Exit Criteria

  • All selected review skills executed
  • Findings consolidated and prioritized
  • Action plan created with ownership
  • Evidence logged per pensive:shared/modules/output-format-templates

Troubleshooting

Common Issues

If the auto-detection fails to identify the correct review skills, explicitly specify the mode (e.g., /full-review rust instead of just /full-review). If integration fails, check that TodoWrite logs are accessible and that evidence files were correctly written by the individual skills.

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