Code Review Claude Skills
2 030 code review skills from 387 authors. They read someone else's code and work through changes before those land. Half of them fit into 1 564 tokens or less — that is what one costs your context window when the agent loads it. 210 ship runnable scripts rather than instructions alone. 3 of them cannot work without an MCP server, most often rube. We also found 261 copies of these same skills sitting in other people's repositories — counted once here, not 261 times.
2 030 unique 387 authors 2 updated this month 280 from vendors
Audit an area of the codebase and propose the smallest structural moves that improve it - untangle boundaries, kill duplication, fix seams, break cycles. Produces a prioritized plan and decision records, not a rewrite. Use when a codebase feels tangled, hard to change, or is becoming a ball of mud, or when asked to improve or refactor architecture.
LLM-powered quality verification using prompt hooks. Validates commit messages, code patterns, and conventions using AI before allowing operations. Use to set up intelligent guardrails.
Default code-quality route for broad code review, PR review, maintainability, correctness, and regression-risk checks. Do not use as the primary route for dedicated OWASP/security audits, review-feedback handling, completion verification, AI-code cleanup, or TDD/test-first work.
Discover codebase patterns, conventions, and unwritten rules before making changes. Use when implementing features, fixing bugs, or refactoring code.
Remove AI-generated code slop from a branch: unnecessary comments, redundant defensive checks, boilerplate, style drift, and type casts. Use for cleanup of AI-written code, not for broad code review, security audit, TDD, or final verification.
Prepare and request a code review after implementation or before merge by assembling scope, requirements, git range, and reviewer instructions.
Review-feedback handling route for CodeRabbit, GitHub, PR, or human reviewer comments. Use before implementing suggestions to verify each finding. Do not use for a fresh code review, security audit, TDD, or final completion evidence.
Create or update project governing principles and development guidelines. Use at project start to establish code quality, testing standards, and architectural constraints that guide all development.
Apply modern web development best practices for security, compatibility, and code quality. Use when asked to "apply best practices", "security audit", "modernize code", "code quality review", or "check for vulnerabilities".
Verify whether generated Java classes duplicate openai-java models by comparing fields/types (names may differ). Use when checking for duplicate model coverage.
Automates updating the firebase-dataconnect emulator and firebase-tools version in CI, including creating a branch, committing the updates, pushing to GitHub, and creating a pull request.
Validate changes before submitting a pull request. Run comprehensive checks including lint, tests, alignment review, and RFC analysis. Use before creating a PR, when asked if code is ready for review, or before pushing for PR.
Refactor code after tests pass. The "Refactor" phase of Red-Green-Refactor.
Monitor a PR's CI checks and Greptile code review after submission. Polls CI status, auto-fixes failures via ralph-loop, waits for Greptile review, addresses comments, and iterates until green.
Use when asked to check for SASS (or PTX) changes between commits, branches, or a local changeset; guides normalization, comparison, and reporting of CUDA disassembly diffs.
Evaluate Expo skills in this repo end-to-end - trigger accuracy, generated code quality, and runtime screenshots on iOS simulator and Android emulator via Expo Go (web optional). Use when the user wants to eval an Expo skill, test that a skill produces working code, benchmark a skill with device screenshots, or verify a skill's output renders correctly.
Adversarial verification of finished work. Treats any "done" as a set of claims, then re-runs the claimed verifications, diffs what actually changed, detects weakened tests and false completion claims, and delivers an evidence-based verdict (VERIFIED / VERIFIED WITH CAVEATS / REFUTED). Use after any agent or model claims work is complete - "/fable-judge", "judge this work", "verify what it did", "did that actually work?". Also runs the fable-method trap suite against a skill or model via "/fable-judge suite <target>".
>- Generate ONE reviewer-defensible, implementable research idea with a concrete method and falsification plan from a stated research direction. Use when the user asks for a research idea, novelty analysis, bottleneck diagnosis, or paper-shape suggestion. Skip code review, debugging, and unconstrained brainstorming without research context.
Reduce technical debt and improve code quality by systematically resolving static analysis warnings.
Perform a pedantic, multi-perspective code review on the current diff or git changes against the styleguide and software engineering best practices.
Use when configuring, running, or fixing PHPStan static analysis in WordPress projects (plugins/themes/sites): phpstan.neon setup, baselines, WordPress-specific typing, and handling third-party plugin classes.
Write readable, maintainable code through disciplined naming, small functions, and clean error handling. Use when the user mentions "clean up this code", "this function is too long", "code smells", "naming conventions", "boy scout rule", "single responsibility", or "unit test quality". Also trigger when reviewing a pull request for readability, untangling a messy function, debating comment styles, or improving error-handling patterns. Covers SRP, comment discipline, formatting, and unit testing. For refactoring techniques, see refactoring-patterns. For architecture and dependency rules, see clean-architecture.
Guided journey from a shipped app that works but feels rough to a product that fits the job, flows without friction, reads clearly, and persuades honestly. Orchestrates nine skills phase by phase - jobs-to-be-done, ux-heuristics, design-everyday-things, refactoring-ui, microinteractions, made-to-stick, influence-psychology, high-perf-browser, steve-jobs-design-review - asking the user questions at every decision point and recording results in the project docs/ folder (CUSTOMER.md, DESIGN.md, POSITIONING.md, IMPROVE-APP-PLAN.md) so the journey resumes across sessions. Use when the user wants to fix a clunky product, cut UX friction, sharpen in-app copy and prompts, or says ''the app works but feels rough''. Do not use for code, tests, or production hardening - use improve-code-quality (fresh prototype) or remove-technical-debt (aged codebase); no app yet, create-app; needs growth loops, grow-app; marketing-site friction, improve-website. For one framework in isolation, invoke that skill directly.
Guided journey from a working-but-untested vibe-coded prototype to a production-ready product with tests, clean structure, a business-rules boundary, and resilience at scale. Orchestrates nine skills phase by phase - working-with-legacy-code, clean-code, refactoring-patterns, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, system-design, ddia-systems - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, RELIABILITY.md, IMPROVE-CODE-QUALITY-PLAN.md) so the journey resumes across sessions. Use when the user wants to harden an AI-generated prototype, add tests before refactoring, make code safe to change, or says ''this works on my machine but I am scared to touch it''. For a large aged codebase, use remove-technical-debt; to decide structure before building, use design-code-architecture; for a product and UX pass, use improve-app. For one framework in isolation, invoke that skill directly.
Design the small details -- triggers, rules, feedback, loops and modes -- that separate good products from great ones. Use when the user mentions "microinteraction", "button feedback", "loading state", "toggle design", "animation detail", "state transitions", "input feedback", "the interface feels dead", "make the UI feel responsive", or "add polish to interactions". Also trigger when designing form-validation responses, progress indicators, confirmation dialogs, or any element where the user expects immediate feedback. Covers trigger design, state rules, feedback mechanisms, and progressive loops. For overall UI polish, see refactoring-ui. For affordance design, see design-everyday-things.
Apply meta-principles of software craftsmanship: DRY, orthogonality, tracer bullets, and design by contract. Use when the user mentions "best practices", "pragmatic approach", "broken windows", "tracer bullet", "software craftsmanship", "avoid technical debt", "code ownership", or "how do I become a better developer". Also trigger when evaluating build-vs-buy decisions, designing estimation approaches, or choosing between reversible and irreversible architectural decisions. Covers estimation, domain languages, and reversibility. For code-level quality, see clean-code. For refactoring techniques, see refactoring-patterns.
Apply named refactoring transformations to improve code structure without changing behavior. Use when the user mentions "refactor this", "code smells", "extract method", "replace conditional", "technical debt", "move method", "inline variable", "decompose conditional", or "clean up this messy code". Also trigger when cleaning up legacy code, preparing code for new features by restructuring, or identifying which transformation fits a specific code smell. Covers smell-driven refactoring, safe transformation sequences, and testing guards. For code-quality foundations, see clean-code. For managing complexity, see software-design-philosophy.
Guided journey from a large aged codebase everyone fears to touch to one that is safe to change, legible, bounded, and resilient - paid down in place without a rewrite. Orchestrates eight skills phase by phase - working-with-legacy-code, refactoring-patterns, clean-code, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, domain-driven-design - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, REMOVE-TECHNICAL-DEBT-PLAN.md) so the journey resumes across sessions. Use when the user wants to tame a legacy codebase, pay down technical debt safely, avoid a big-bang rewrite, or says ''we are afraid to touch this code''. For a fresh prototype or vibe-coded app going to production, use improve-code-quality; for greenfield structure, use design-code-architecture; for a product-and-UX pass rather than code-only, use improve-app. For one framework in isolation, invoke that skill directly.
Manage software complexity through deep modules, information hiding, and strategic programming. Use when the user mentions "module design", "API too complex", "shallow class", "complexity budget", "strategic vs tactical", "deep module", "information leakage", "pass-through method", "this code is over-engineered", or "simplify this design". Also trigger when reviewing an interface for simplicity, evaluating whether an abstraction is pulling its weight, deciding whether a comment is worth writing, or choosing between general-purpose and special-purpose approaches. Covers deep vs shallow modules, red flags for complexity, and comments as design documentation. For code quality, see clean-code. For architecture boundaries, see clean-architecture.
Review designs, products, and features with Steve Jobs'' standards: ruthless simplicity, focus, and end-to-end excellence. Use when the user mentions "Steve Jobs review", "design review", "product review", "what would Steve do", "insanely great", "this feels too complicated", "too many features", "product taste", "saying no", or "is this good enough to ship". Also trigger when critiquing a UI, feature, or roadmap for focus and simplicity, cutting scope to the essential, or pressure-testing the whole experience from first run to daily use. Covers the simplicity audit, the no list, design-is-how-it-works, end-to-end ownership, demo culture, and a Jobs-style review protocol with binary verdicts. For visual design fundamentals, see refactoring-ui. For usability audits, see ux-heuristics. For detail polish, see microinteractions.
Use before MR handoff or when reviewing DCGM Exporter changes.
Address PR review comments by fixing code, replying to each comment, and re-requesting review. Use this skill when the user wants to handle, fix, resolve, or address PR feedback, review comments, or code review suggestions. Also use when the user says things like "fix the PR comments", "handle review feedback", "address the review", or "respond to PR feedback".
AST-aware Java refactoring using OpenRewrite. Use when asked to structurally refactor Java code, change class names, change method signatures/overloads, replace builder patterns, modify annotations, or perform cross-file structural replacements. Note: Renaming fields or local variables/parameters is not supported natively via simple YAML recipes in the standard openrewrite modules.
Prepare a pull request by running presubmit with fixes. Use when preparing to commit or send a PR.
General workflow for fetching, inspecting, reviewing GitHub Pull Requests using the gh CLI, drafting user-aligned review comments, and securing approval before posting. Use when asked to review a GitHub PR or pull request.
DevTools repository-specific PR review workflow enforcing DevTools style guidelines and common review patterns. Use when reviewing pull requests in the flutter/devtools repository.
Use when building or maintaining a personal LLM-powered knowledge base. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki quality, 'add to wiki', 'what do I know about', or any mention of 'LLM wiki' or 'Karpathy wiki'.
> Use when writing or reviewing code that must work in both CMake Presets and Kits/Variants modes. Covers configure, build, test, environment, and generator
> Verify that a pull request into microsoft/vscode-cmake-tools meets contribution requirements. Use when preparing, reviewing, or finalizing a PR to check for a descriptive title, a meaningful description, a properly formatted CHANGELOG entry, code correctness, regression risks, adherence to existing patterns, and whether documentation updates are needed.
> Creates a validation project for testing a specific vscode-cmake-tools pull request. Use this skill when asked to create a validation project, test a PR, validate a pull request, or set up a PR validation environment. The skill creates a structured project directory with documentation, metadata, and checklists for systematically validating PR changes.
Drive a GitHub pull request through repeated rounds of Copilot code review until convergence. Use when the user asks to "request Copilot review", "run a Copilot review loop", iterate on Copilot feedback, or wants automated triage-and-respond on Copilot PR comments. Covers re-request mechanics, open-thread filtering, fix-vs-decline triage, reply-and-resolve, and end-of-loop cleanup.
Leverage OpenAI Codex/GPT models for autonomous code implementation, code review, and plan review. Triggers: "codex", "use gpt", "gpt-5", "let openai", "full-auto", "adversarial review", "second opinion review", "用codex", "让gpt实现", "对抗式审查", "让codex审查计划", "第二意见". Use this skill whenever the user wants to delegate coding tasks to OpenAI models, run code or plan reviews via codex, get a second-opinion review from a different model, or execute tasks in a sandboxed environment.
Review changes in clickhouse-java for correctness, compatibility, API stability, and missing tests. Use when reviewing pull requests, commits, diffs, patches, or when the user asks for a code review.
Diagnose Swift Concurrency issues, refactor callback-based code to async/await, and guide Swift 6 migration when working with tasks, actors, @MainActor, Sendable, data races, thread safety, or concurrency-related compiler and linter warnings.
GitHub patterns using gh CLI for pull requests, stacked PRs, code review, branching strategies, and repository automation. Use when working with GitHub PRs, merging strategies, or repository management tasks.
AI DevKit · Publish a ready feature branch for review. Use when the user wants to sync, push, and open or update a code review request on GitHub, GitLab, or another Git host.
AI DevKit · Final code review phase guidance for holistic pre-push review. Use when the user wants code review, final lifecycle review, design alignment checks, integration risk review, or dev-lifecycle phase 9.