This document covers the type of work that should be performed when doing final code cleanup for a change.

This skill provides access to a searchable history of previous conversations stored in a ChromaDB vector database. It supports both **retrieving** past conversations via semantic search and **saving**

Implement new features using TDD starting from README + Issue (following codegen-test), aligning with existing implementation conventions, and leveraging Serena MCP semantic search/editing to deliver high performance while being mindful of data races.

Analyzes code to identify refactoring opportunities, code duplication, problematic data flows, architectural issues, and code smells. Generates a comprehensive refactoring recommendation plan.

Comprehensive guide for creating, configuring, and troubleshooting codemagic.yaml files for CI/CD workflows. Use when building mobile apps (Flutter, iOS, Android, React Native) with Codemagic, setting up build pipelines, configuring environment variables, implementing code signing, managing artifacts, or debugging workflow issues.

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.

Expert-level CodeQL for static analysis, vulnerability detection, and security code scanning

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Execute CodeQL security scans with language detection, database caching, and SARIF output. Use when performing static security analysis on Python or GitHub Actions code.

Initial Convex workspace setup in Coder workspaces with self-hosted Convex deployment, authentication configuration, Docker setup, and environment variable generation

Self-hosted Convex development in Coder workspaces with authentication, queries, mutations, React integration, and environment configuration

Coder workspace environment for hahomelabs.com deployments. Includes networking, ports, convex config, nhost config

**NEVER call memory MCP tools directly!** Use Task tool with `subagent_type: "general-purpose"` to keep main context clean.

**NEVER call memory MCP tools directly!** Use Task tool with `subagent_type: "general-purpose"` to keep main context clean.

Coder CLI commands for workspace management, templates, and platform operations

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.

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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Expert code writer - produces clean, production-ready code

Create, manage, and optimize GitHub Codespaces cloud development environments. Configure devcontainers, manage resources, and streamline cloud-based development. Use when setting up cloud development environments, configuring devcontainers, or managing Codespaces. Triggers on codespace, devcontainer, cloud IDE, remote development, development environment, container development.

Create, manage, and optimize GitHub Codespaces cloud development environments. Configure devcontainers, manage resources, and streamline cloud-based development. Triggers on codespace, devcontainer, cloud IDE, remote development, development environment, container development.

Analyze code for style violations, pattern compliance, and quality issues

Consolidate Codex macOS app automation worktrees and surface actionable changes. Use for morning triage and to review recommended automations.

Ask OpenAI Codex questions about code to understand implementations, architecture, patterns, and debugging. Use when the user asks how code works, where something is implemented, what patterns are used, or needs to understand existing code. Requires Codex CLI installed.

Execute tasks using OpenAI Codex CLI and analyze results.

Use Codex CLI for sandboxed auditing, debugging, and autonomous prototyping

Setup and manage OpenAI Codex CLI authentication including ChatGPT Plus/Pro OAuth, API keys, and multi-account management. Use when configuring Codex access, switching accounts, or troubleshooting authentication.

Interactive REPL workflows with Codex CLI including session management, multimodal conversations, and automated execution. Use for extended development sessions, debugging, or collaborative problem-solving.

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'.

Bridge between Claude Code and OpenAI Codex CLI - generates AGENTS.md from CLAUDE.md, provides Codex CLI execution helpers, and enables seamless interoperability between both tools

Single source of truth and librarian for ALL OpenAI Codex CLI documentation. Manages local documentation storage, scraping, discovery, and resolution. Use when finding, locating, searching, or resolving Codex CLI documentation; discovering docs by keywords, category, tags, or natural language queries; scraping from llms.txt; managing index metadata (keywords, tags, aliases); or rebuilding index from filesystem. Run scripts to scrape, find, and resolve documentation. Handles doc_id resolution, keyword search, natural language queries, category/tag filtering, alias resolution, llms.txt parsing, markdown subsection extraction for internal use, hash-based drift detection, and comprehensive index maintenance.

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

Manages OpenAI Codex CLI configuration including config.toml settings, MCP servers, model profiles, sandbox modes, approval policies, and skill paths. Use when configuring Codex CLI, setting up model profiles, managing MCP server integrations, troubleshooting Codex configuration issues, or optimizing Codex for different workflows.

Automatically delegate complex, logic-intensive tasks to OpenAI Codex CLI via `codex exec --full-auto`. Claude Code uses this skill to invoke Codex for complex backend logic, intricate algorithms, or persistent bugs. Enables seamless AI-to-AI collaboration where Claude Code analyzes and Codex executes.

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.

Delegiere Aufgaben an OpenAI Codex CLI im Headless-Mode. Nutzt ChatGPT Subscription (KEIN API Key). Nur Workspace-Zugriff, KEIN System-Zugriff. Auto-Accept mit --full-auto. Web-Recherche mit --search.

Invoke OpenAI Codex CLI with the correct configuration for autonomous code generation. Use when you need Codex to generate or regenerate code files, implement features, or execute multi-step coding tasks.

Use Codex CLI in full-auto mode to fix issues iteratively until tests pass. Autonomous debugging and test-fixing loop with sandbox safety.

[DEPRECATED] Run multiple AI agent threads in parallel with bounded concurrency. Use evolving-workflow instead.

[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.

Run the Codex Readiness unit test report. Use when you need deterministic checks plus in-session LLM evals for AGENTS.md/PLANS.md.

Review implementation quality and regression risks via claude-delegator (Code Reviewer expert). Use after implementation for complex tasks, refactors, or API changes.

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.