Analyzes code for style consistency and applies project-specific formatting conventions beyond what linters catch. Use when reviewing code, ensuring style consistency, or when user requests code style improvements.
Skills（SKILL.md）は、AIエージェント（Claude Code、Cursor、Codexなど）に特定の能力を追加するための設定ファイルです。
詳しく見る →Analyzes code for style consistency and applies project-specific formatting conventions beyond what linters catch. Use when reviewing code, ensuring style consistency, or when user requests code style improvements.
Code style principle-based review - checks SRP (Single Responsibility Principle), DRY (Don't Repeat Yourself), Simplicity First, YAGNI (You Aren't Gonna Need It), and Type Safety. Also evaluates code structure and naming conventions. Automatically used when code review is needed.
Programmatic code style validation using AST analysis. Complements (not replaces) code-style rules by providing automated checking and instant feedback.
代码风格规范 / Code style conventions。在编写、编辑、评审 Python 代码时使用。包括类型注解、Decimal 精度、Docstring、模块组织等规范。Use when writing, editing, or reviewing Python code. Enforces type hints, Decimal precision, docstrings, and module organization.
Advanced code testing and review expert system that provides comprehensive code quality analysis, security vulnerability assessment, test strategy design, and quality assurance through multi-expert collaboration and intelligent tool integration.
Generate and run comprehensive unit and integration tests following TDD principles with proper fixtures, mocking, and coverage measurement.
Write and generate code using memex-cli with Codex backend. Use when (1) Generating code files and scripts, (2) Refactoring existing code, (3) Writing tests, (4) Creating project scaffolds, (5) Implementing algorithms or features, (6) Code review and optimization, (7) Complex multi-file projects.
Analyze, consolidate, and document codebases through multi-perspective analysis. Use when reviewing project structure, planning refactoring, creating documentation, or assessing technical debt.
Apply code changes to a GitHub repository and automatically create a pull request. Takes user feedback or fix requirements, clones the repo, makes localized changes, commits to a new branch, and opens a PR via GitHub MCP.
Reviews git history to summarize changes merged while you were away from a consulting project, identifying PRs, code changes, and potential concerns to discuss with the development team.
Analyzes code to identify refactoring opportunities, code duplication, problematic data flows, architectural issues, and code smells. Generates a comprehensive refactoring recommendation plan.
Codemod (JSSG, ast-grep, workflows) best practices for writing efficient, safe, and maintainable code transformations. This skill should be used when writing, reviewing, or debugging codemods, AST transformations, or automated refactoring tools. Triggers on tasks involving codemod, ast-grep, JSSG, code transformation, or automated migration.
This skill should be used when CodeRabbit code review feedback needs to be processed and fixed systematically. Use after running `coderabbit --plain` to automatically save feedback, analyze issues using MCP tools, and implement minimal code fixes with proper planning.
Implement fixes for specific CodeRabbit review issues. Runs in isolated subagent context with focused task. Verifies fixes with tests before returning. Use one per issue from triage task list.
Systematic workflow for CodeRabbit reviews - local CLI, PR threads, and commit attribution
Use after completing file changes - strongest for source code (AST-aware linting, security, tests), lighter support for markdown/config. Dispatches CodeRabbit reviewer subagent. ALWAYS request review before considering work complete.
Use CodeRabbit CLI to receive external code review feedback and address identified issues. Invoke this skill when the user requests CodeRabbit review, or proactively after implementing significant code changes to get feedback and improve code quality.
Integrates CodeRabbit for automated PR code review. Use after PR creation to get AI-powered review feedback before human review.
Analyze code review findings and create execution plan. Decides parallel vs sequential fixing based on issue severity and independence. Returns structured task list with clear fixer instructions.
Systematic workflow for CodeRabbit reviews - local CLI, PR threads, and commit attribution
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Hand off a task to Codex CLI for autonomous execution. Use when a task would benefit from a capable subagent to implement, fix, investigate, or review code. Codex has full codebase access and can make changes.
Get a second opinion from OpenAI Codex CLI for plan reviews, code reviews, architecture decisions, and hard problems. Use when you need external validation, want to compare approaches, or are stuck on a difficult problem.
Delegate coding tasks to Codex AI for implementation, analysis, and alternative solutions. Use when you need a second AI perspective, want to explore different approaches, or need specialized Codex capabilities for complex coding tasks.
通过 Codex MCP 工具进行代码审查、算法设计、架构分析和性能优化。适用于复杂技术任务（>10行核心逻辑）、系统级设计、多约束权衡、性能瓶颈分析。触发词：review、code review、代码审查、算法设计、复杂算法、架构分析、架构评审、系统设计、性能优化、瓶颈分析、性能调优。
Consolidate Codex macOS app automation worktrees and surface actionable changes. Use for morning triage and to review recommended automations.
Codex architecture consulting (third brain). Get Codex architecture advice during design phase, forming dual perspective with Claude.
Orchestrates a triple-AI engineering loop where Claude plans, Codex validates logic and reviews code, and Cursor implements, with continuous feedback for optimal code quality
Dual-AI engineering loop orchestrating Claude Code (planning/implementation) and Codex (validation/review). Use when (1) complex feature development requiring validation, (2) high-quality code with security/performance concerns, (3) large-scale refactoring, (4) user requests codex-claude loop or dual-AI review. Do NOT use for simple one-off fixes or prototypes.
OpenAI Codex CLI orchestration for AI-assisted development using gpt-5.2-codex model. Capabilities: code generation, refactoring, automated editing, parallel task execution, session management, code review, architecture analysis, and MCP integration. Actions: analyze, implement, review, fix, refactor with Codex. Keywords: Codex CLI, gpt-5.2-codex, codex exec, code generation, refactoring, parallel execution, session resume, code review, second opinion, independent review, architecture validation, Context7 MCP. Use when: delegating complex code tasks to Codex, running multi-agent workflows, executing automated reviews, implementing features with AI assistance, resuming previous sessions, querying OpenAI documentation. Triggers: 'use codex', 'codex exec', 'run with codex', 'codex resume', 'implement with codex', 'review with codex', 'codex docs'.
Use Codex CLI (not MCP) to review uncommitted changes. Codex explores the codebase independently with full disk read access.
OpenAI Codex CLI fundamentals for code analysis, review, and validation. Use when (1) executing codex commands for code review/analysis, (2) configuring models (gpt-5.2-codex/gpt-5.2/gpt-5.1-codex-max/codex-mini), sandbox modes (read-only/workspace-write), or reasoning effort (low/medium/high/xhigh), (3) managing Codex sessions with resume, (4) integrating Codex into automation scripts. Do NOT use for orchestration patterns (use codex-claude-loop instead).
Code review skill with rubric and templates
This skill provides a systematic, iterative code review workflow powered by zen mcp's codex tool. It automatically checks recently modified code files against project standards (CLAUDE.md requirements
Comprehensive code review with Codex (gpt-5.2).
Codex CLI integration for code review and consultation. Use when: (1) code needs review before commit, (2) need expert consultation on implementation approach, (3) debugging assistance needed. This skill provides Codex interaction patterns only - workflow orchestration is defined in project CLAUDE.md.
Invoke Codex CLI as a coworker for implementation, brainstorming, specs, and reviews. Use when you want parallel thinking, cheap execution, or a second opinion. Codex tokens are cheaper than yours — delegate aggressively. Keywords: codex, delegate, implement, draft, review, brainstorm, write tests, code review.
Git-aware development workflows with Codex CLI including intelligent commits, PR automation, branch management, and diff application. Use for git operations, PR reviews, or automated git workflows.
[CLAUDE CODE ONLY] Leverage Codex CLI for AI peer review, second opinions on architecture and design decisions, cross-validation of implementations, security analysis, and alternative approach generation. Requires terminal access to execute Codex CLI commands. Use when making high-stakes decisions, reviewing complex architecture, or when explicitly requested for a second AI perspective. Must be explicitly invoked using skill syntax.
[TMUX MODE] Send plan to Codex via tmux file-based IPC. Only use when user explicitly runs /codex-plan-review command. For natural language requests, use the delegate_codex_plan_review MCP tool instead.
Review implementation quality and regression risks via claude-delegator (Code Reviewer expert). Use after implementation for complex tasks, refactors, or API changes.
Git管理外のファイルをcodex CLIでレビュー。「このファイルをcodexでレビュー」「設定ファイルをレビュー」時に使用
Professional code review with auto CHANGELOG generation, integrated with Codex AI
Automated code review workflow using OpenAI Codex CLI. Implements iterative fix-and-review cycles until code passes validation or reaches iteration limit. Use when building features requiring automated code validation, security checks, or quality assurance through Codex CLI.
Validate integration impact and regression risks via claude-delegator (Code Reviewer expert). Use for complex tasks or API integration.
Validate architecture/plan quality via claude-delegator (Plan Reviewer expert). Use after writing context.md for complex feature/refactor work.
Provides coding assistance with best practices and code review
Provides coding style rules for Python and PowerShell. Apply when writing, editing, reviewing, or debugging code.
Best practices for writing clear, actionable error messages in code.
Enforce ThemeGPT complexity budgets and prevent over-engineering. Activates automatically when writing, reviewing, or refactoring code. Validates against 6 anti-patterns from SynthAI archaeology (Specification Inflation, Enterprise Pattern Obsession, Premature Abstraction, Configuration Explosion, Framework Absorption, Test Suite Inflation). Use when creating features, adding abstractions, writing tests, or configuring projects.