Code Review & Quality for Claude Code

Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.

Trace a data flow or bug through the IronClaw codebase end-to-end

Triage open GitHub issues — split into bugs vs features, rank by severity/opportunity, and flag under-specified issues

Classify all open PRs by module, review state, scope, and architectural impact — produces a prioritized triage dashboard

Resolve active pull request comments and prepare replies

Explain recent changes and provide a structured summary with security checks

Review, commit, create PR, then auto-address review comments in a loop.

Start a background loop that monitors PR for new review comments and addresses them.

Review prompt and tool-description changes in a branch or PR. Use when asked to audit system prompts, prompt builders, tool descriptions, prompt inputs, or nearby evals/tests; summarize what changed; identify guidance that feels eval-shaped or too heavy for product use; and find repeated instructions between the main prompt and tool descriptions.

Use when implementation is complete and PR-ready to review the current diff for security, DRY opportunities, simplicity, and abstraction quality.

Parses error messages, traces execution flow through stack traces, correlates log entries to identify failure points, and applies systematic hypothesis-driven methodology to isolate and resolve bugs. Use when investigating errors, analyzing stack traces, finding root causes of unexpected behavior, troubleshooting crashes, or performing log analysis, error investigation, or root cause analysis.

Identifies security vulnerabilities, generates structured audit reports with severity ratings, and provides actionable remediation guidance. Use when conducting security audits, reviewing code for vulnerabilities, or analyzing infrastructure security. Invoke for SAST scans, penetration testing, DevSecOps practices, cloud security reviews, dependency audits, secrets scanning, or compliance checks. Produces vulnerability reports, prioritized recommendations, and compliance checklists.

Reverse-engineering specialist that extracts specifications from existing codebases. Use when working with legacy or undocumented systems, inherited projects, or old codebases with no documentation. Invoke to map code dependencies, generate API documentation from source, identify undocumented business logic, figure out what code does, or create architecture documentation from implementation. Trigger phrases: reverse engineer, old codebase, no docs, no documentation, figure out how this works, in

Generates test files, creates mocking strategies, analyzes code coverage, designs test architectures, and produces test plans and defect reports across functional, performance, and security testing disciplines. Use when writing unit tests, integration tests, or E2E tests; creating test strategies or automation frameworks; analyzing coverage gaps; performance testing with k6 or Artillery; security testing with OWASP methods; debugging flaky tests; or working on QA, regression, test automation, qu

> Open source license compliance check for a dependency list, a single library, or outbound code. Use when reviewing a manifest, SBOM, or repo for copyleft obligations and license compatibility, when asked whether a library can ship, or when preparing code to be open-sourced.

> Review and approve (or reject) pending playbook update proposals from the playbook-monitor agent and apply approved changes to the practice profile. Use when the playbook-monitor agent has surfaced proposals, when the user says "review playbook proposals", "what playbook updates are pending", or wants to step through deviation-driven playbook changes.

你是开发者。你的工作是把功能设计文档变成实际代码，并在收到 review 意见或测试报告之后， 针对性地修复问题、补全缺口。你不需要、也不应该去关心测试用例具体怎么写——那是 tester 的工作，你看不到也不需要看到测试代码的内容（如果环境支持物理隔离）。

基于功能设计文档(由 product-feature-tech-design 产出或等价输入)、源码目录、以及测试所依赖的环境信息(例如 PostgreSQL 插件开发需要的 PG 源码/实例、第三方依赖),编排「开发者 ↔ 评审者 ↔ 测试者」三方隔离的实施循环,直至评审通过、且所有测试(新增 + 已有)通过。三方互不可见,测试者绝对不能看到开发者写的代码。完成后输出 markdown 总结报告到当前项目的 `markdown/` 目录。适用于:实施功能设计文档、按设计稿开发并自验证、闭环式开发流程、PostgreSQL 插件/扩展开发、需要 build + 部署 + 跑测的工程项目、TDD 式实施循环。

你是代码审查者。你的任务是拿设计文档当标尺，去衡量这一轮的增量代码是不是真的实现了设计文档 要求的东西，同时检查代码本身的质量问题。你不写代码，你的产出是判断（通过/不通过）和具体的 问题清单。

| PostgreSQL 核心 committer Tom Lane 的思维框架与表达方式。基于 6 个调研维度（著作、对话、表达 DNA、他者视角、决策、时间线） 共 2421 行 / 160 KB 一手资料的深度调研，提炼 6 个核心心智模型、10 条决策启发式和完整的表达 DNA。 用途：作为思维顾问，用 Tom Lane 的视角分析开源项目治理问题、审视 patch 评审、调试 PostgreSQL 相关决策、 处理"维护者 vs 运动员"张力等场景。 当用户提到「用 Tom Lane 的视角」「tgl 会怎么看」「Tom Lane 模式」「regards, tom lane」「I object, I'll rewrite」 「Tom Lane 风格评审」「patch 评审」「commitfest」「维护者 vs 运动员」「It's hard to argue that」「Let's just」 「undo thinko」「以 PG committer 身份」「core team 视角」时使用。即使用户只是说「帮我用 PG 核心 committer 的角度想想」 「如果 Tom

Comprehensive Python programming reference covering syntax, concurrency, networking, databases, ML/LLM development, and HPC. Use for: Python questions, Python interview preparation, debugging, performance optimization, async patterns, library examples, code review, best practices, MLOps workflows, distributed computing, security implementations, and any Python development tasks.

Readable Python code rules inspired by The Art of Readable Code. Use when writing, reviewing, or refactoring Python code. Enforces short functions, flat control flow, clear naming, readable structure, and Pythonic idioms.

Fetch CodeRabbit review comments on the current PR, classify each finding, apply fixes for valid issues, and reply to each thread. Use before attempting gh pr merge when CodeRabbit has posted a review. Blocks merge on unresolved threads. Routes security-critical findings to a human.

Reviews code changes for architectural consistency, layer violations, API surface changes, and dependency direction in the FastLED codebase

Deep C++ expertise for template metaprogramming, SFINAE, constexpr, type traits, and memory model questions in embedded context

You are a specialized code review agent for FastLED. Review staged and unstaged changes according to these strict rules.

Xtensa Assembly Code Review

Reviews Xtensa assembly code for ESP32 platforms using static analysis

Review RISC-V assembly code for correctness and best practices

Review Xtensa assembly code for ESP32 platforms. Checks for critical errors in inline assembly, ABI compliance, and optimization opportunities. Use after modifying ESP32 assembly or inline asm code.

Review RISC-V assembly code for correctness, ABI compliance, and best practices. Use after modifying RISC-V assembly or inline asm code.

Creates new C++ linter rules for the FastLED codebase. New rules live in the Rust crate (ci/lint_cpp_rs/) by default; Python is reserved for AST ratchets and cross-file structural checks.

Review and implement hardware driver code — DMA safety, interrupt correctness, timing constraints, peripheral register usage, channel drivers, and peripheral mock implementations. Use when writing, modifying, or reviewing LED drivers, SPI/I2S/RMT/UART/PARLIO/LCD_CAM peripherals, GPIO configuration, or peripheral mock code.

Review ESP32 FastLED firmware architecture for RTOS safety, DMA correctness, LED driver patterns, memory management, and peripheral safety. Use before merging significant driver changes, new platform ports, or when auditing existing ESP32 FastLED code.

Fix integer type definitions for specified platform

Search codebase and git history for keywords

Run code linting and formatting checks

Run code linting and formatting checks across the codebase. Use after modifying source files to ensure coding standards are met.

Runs code linting and formatting checks across the codebase