GitHub
skill-orchestrator
Orchestrate the full implementation workflow: implement -> architecture review -> code review. Use when you need a complete implementation with reviews. Triggers on: full implementation, implement with review,...
Résultats pour « code review »
Skills correspondant au nom, à la description ou à l’auteur GitHub.
Catégories: Contenu et médias
Explorer
GitHub
review
Code review workflow for PRs and local changes. Integrates code-review and security-review agents.
GitHub
code-review
Perform language-agnostic code reviews focusing on correctness, regressions, security, and tests. Use when the user asks for a review.
GitHub
17th-test-analyzer
Use this skill when user asks about test coverage, test sufficiency, or whether tests cover requirements. Analyzes staged changes against task spec using GPT-5.2-Codex to find gaps in happy cases and edge cases...
GitHub
git-pr-workflows-git-workflow
Orchestrate a comprehensive git workflow from code review through PR creation, leveraging specialized agents for quality assurance, testing, and deployment readiness. This workflow implements modern g
GitHub
coderabbit
Runs AI code reviews using CodeRabbit CLI. Use when reviewing uncommitted changes, preparing PRs, checking for security issues, scanning for hardcoded secrets, or verifying code quality before committing.
GitHub
loop-codex-review
Automated code review loop with progressive reasoning levels. Runs n parallel Codex reviews (configurable via -n), Claude addresses findings, climbs from low→xhigh reasoning until fixed point (all n clean). Hum...
GitHub
moai-workflow-testing
Comprehensive development workflow specialist combining TDD, debugging, performance optimization, code review, PR review, and quality assurance into unified development workflows
GitHub
code-reviewer
Elite code review expert specializing in modern AI-powered code analysis, security vulnerabilities, performance optimization, and production reliability. Masters static analysis tools, security scanning, and co...
Catégories populaires
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.