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
Biome - Fast all-in-one toolchain for web projects (linter + formatter in Rust, 100x faster than ESLint)
Python code-quality anti-patterns and review checks: exception-hierarchy correctness, singleton identity comparison, narrow exception handling, wildcard-import avoidance, magic-number naming, and dead-local removal. Use when reviewing or self-reviewing Python code for correctness and readability defects that linters and reviewers should catch.
PR quality checklist for ensuring comprehensive, well-documented pull requests. Use before submitting PRs to improve review efficiency and code quality.
Dispatch code-reviewer subagent to review implementation against plan or requirements before proceeding
Create and manage stacked (dependent) pull requests for complex features
Severity-tagged code review checklist (CRITICAL/HIGH/MEDIUM/LOW) used by code-critic agent
Vendor-neutral framework for scoring software health, estimating technical debt, assessing cloud readiness and open-source safety, and communicating quality to business stakeholders. Use when you need to quantify code health at the application or portfolio level rather than fix individual findings.
Visual verification workflow for UI changes to accelerate code review and catch ...
> interface compliance verification, composition, the accept-interfaces-return-structs principle, and common pitfalls. Use when designing interfaces, decoupling packages, defining contracts, reviewing interface usage, or refactoring for testability. "interface compliance", "consumer-side interface", "interface composition". Do NOT use for HTTP handler patterns (use go-api-design) or general code review (use go-code-review).
> Go coding standards and style conventions grounded in Effective Go, Go Code Review Comments, and production-proven idioms. Use when writing or reviewing Go code, enforcing naming conventions, import ordering, variable declarations, struct initialization, or formatting rules. Do NOT use for architecture decisions, concurrency patterns, or performance tuning — use go-architecture-review, go-concurrency-review, or go-performance-review instead.
> Comprehensive code review checklist for Go projects. Evaluates code quality, idiomatic patterns, error handling, naming, package structure, and test coverage. Use when reviewing Go code, PRs, or before merging changes. Do NOT use for security-specific audits (use go-security-audit) or performance-specific analysis (use go-performance-review).
> Go error handling patterns, wrapping, sentinel errors, custom error types, and the errors package. Grounded in Effective Go, Go Code Review Comments, and production-proven idioms. Use when implementing error handling, designing error types, debugging error chains, or reviewing error handling patterns. "sentinel errors", "errors.Is", "errors.As". Do NOT use for panic/recover patterns in middleware (use go-api-design) or test assertion errors (use go-test-quality).
> Structured git commit messages following Conventional Commits format for Go projects. Generates well-scoped, atomic commits with clear descriptions. Use when committing changes, writing commit messages, preparing PRs, or reviewing commit history quality. "prepare PR", "squash commits". Do NOT use for changelog generation (use changelog-generator) or code review (use go-code-review).
> renames, extracting packages, breaking circular dependencies, and strangler migrations — always behind green tests. "break this circular dependency", "split this god package", "migrate callers", "clean up without changing behavior". adopting new language features (use go-modernize), or performance rewrites (use go-performance-review).
> Help users prepare and review pull requests that maintainers actually want to merge. Use this skill whenever someone asks for help writing a PR description, preparing a contribution to an open-source project, reviewing their own PR before submitting, writing a bug fix PR, drafting a feature PR, or asks anything like "how do I make a good pull request", "review my PR", or "why do my PRs keep getting rejected". Also trigger when a user shares a diff or patch and wants help presenting it, when they mention contributing to a repo they don't maintain, when they're preparing their first contribution to a project, or when they want a pre-submission sanity check. Even if the user doesn't explicitly mention "PR" — if they're packaging a code change for someone else to review, this skill applies.
Expert guidance on Swift Concurrency best practices, patterns, and implementation. Use when developers mention: (1) Swift Concurrency, async/await, actors, or tasks, (2) modern concurrency patterns or structured concurrency, (3) migrating to Swift 6 or strict concurrency checking, (4) data races or thread safety issues, (5) refactoring closures to async/await, (6) @MainActor, Sendable, or actor isolation, (7) concurrent code architecture or performance, (8) concurrency-related linter warnings, (9) AsyncSequence, AsyncStream, or task groups, (10) nonisolated, @preconcurrency, or @unchecked Sendable.
Activates Standard of Excellence enforcement for the current session. Load before starting any task to apply completion standards: finish the whole thing, fix the root cause, ship the complete working result. Blocks partial solutions, workarounds, deferred threads, and invented content limits when the permanent solve is within reach. Triggers: 'do the whole thing', 'boil the ocean', 'standard of excellence', 'finish it completely', before starting any implementation, refactoring, or multi-step task where partial output is a risk. Does NOT apply to: read-only queries, one-line typo fixes, pure knowledge questions, or single-output summarize requests.
Generates and commits conventional-commits messages by analyzing staged git diffs — fast and fork-context safe. Use when the user asks to commit staged changes, needs a type-scope-description message generated from the current diff, or wants scope selection guidance and pre-commit hook handling.
Analyze git branches and generate structured MR/PR descriptions with domain-based change categorization — bug fixes, enhancements, technical debt, documentation, testing, build/CI, and non-functional changes. Use when preparing merge request descriptions, pull request bodies, writing changelogs from git diffs, documenting branch changes, or generating release notes. Works with GitHub and GitLab without requiring JIRA or issue tracker integration.
Strategic rebase with mandatory pre-analysis. Use when asked to rebase a branch onto main (or any target). Runs a file-level diff of both sides before touching git, produces a per-file disposition plan (KEEP/MERGE/DROP/REWRITE), and only then executes the rebase. Prevents surprise conflicts and silent data loss from rebasing without knowing what changed on both sides. Triggers: 'rebase', 'rebase onto main', 'rebase this branch', 'rebase and merge', 'update branch from main'.
Recipes and patterns for Claude Code multi-agent swarms. Use when building parallel specialist reviews, pipeline workflows, self-organizing swarms, research-then-implement flows, plan approval gates, coordinated multi-file refactoring, or any divide-and-conquer orchestration pattern requiring TeamCreate, TaskCreate, SendMessage, or Agent tool coordination.
This skill should be used when the user asks to "lint bash script", "run shellcheck", "format shell script", "use shfmt", "fix shellcheck errors", or mentions shell script linting, formatting, code quality, or pre-commit hooks for bash.
When setting up commit message validation for a project. When project has commitlint.config.js or .commitlintrc files. When configuring CI/CD to enforce commit format. When extracting commit rules for LLM prompt generation. When debugging commit message rejection errors.
When writing a git commit message. When task completes and changes need committing. When project uses semantic-release, commitizen, git-cliff. When choosing between feat/fix/chore/docs types. When indicating breaking changes. When generating changelogs from commit history.
Loaded automatically when reviewing Claude skills or agent definitions — covers SKILL.md structure, frontmatter validity, token budget, description quality, and agent contract compliance.
Reviews CLI application code for correctness and quality. Use when reviewing tools that use argparse, click, typer, commander.js, or similar argument parsers — covers exit codes, help flags, stdin/stdout/stderr separation, non-interactive operation, signal handling, argument validation, ANSI color safety, and dry-run support for destructive operations.
Use when reviewing AI/ML code or LLM integration — activates on prompt templates, model selection logic, token budget concerns, or evaluation harness code. Enforces prompt hygiene, model tier matching, context window management, token economics, structured output validation, temperature settings, retry logic, streaming error handling, and PII/safety rules.
Applies Node.js-specific code review patterns for async I/O, streams, security, process management, and dependency hygiene. Use when reviewing Node.js server code, route handlers, middleware, or any JavaScript file alongside package.json without TypeScript. Triggers on sync I/O in request paths, missing stream backpressure, process.exit misuse, eval/exec injection risks, wildcard version ranges, missing lockfiles, EventEmitter cleanup gaps, and unvalidated environment variables at startup.
Provides Python-specific code review rules for the dh code-reviewer agent. Activates on pyproject.toml or *.py file detection — enforces uv, ruff, ty, pytest, type annotation, error handling, and Python 3.11+ idioms including pathlib, match statements, and modern union syntax.
Provides TypeScript-specific code review patterns covering strict mode, ESM, type safety, branded types, discriminated unions, async patterns, runtime safety, and common anti-patterns. Activates on detection of tsconfig.json, *.ts, or *.tsx files during code review — loaded automatically by dh:code-reviewer.
Use when reviewing web frontend code — HTML, CSS, JSX, or browser-targeted JavaScript. Enforces accessibility (WCAG AA, aria labels, focus management), XSS prevention (innerHTML, dangerouslySetInnerHTML), performance (layout thrash, CLS, lazy loading), CSS design tokens, form labeling, and event listener cleanup. Loaded by dh:code-reviewer on *.html, *.css, *.jsx detection.
Use when all tasks for a feature are marked COMPLETE — runs holistic quality gates including code review, feature verification, integration check, documentation drift audit and update, and context refinement. Creates follow-up task files when issues are found.
Dispatches four parallel perspective reviewers (Security, Performance, Quality, Accessibility) against a diff via TeamCreate and dh:task-worker. Creates an ephemeral SAM plan with four tasks, collects structured verdicts via SendMessage, prints one summary line per perspective, and exits non-zero if any perspective returns REJECT. SKIP is a passing outcome.
Runs information completeness pre-pass before task decomposition and plan generation. Use when grooming backlog items, generating plans, decomposing tasks under uncertainty, or working in brownfield and refactor scenarios. Localizes missing inputs to affected tasks only — does not block plan generation. Produces completeness summary (APPROVED-FOR-PLANNING, APPROVED-WITH-GAPS, or BLOCKED-FOR-PLANNING), missing input report with dependency mapping, required unblock actions, and planning annotations for downstream tasks. Non-blocking sister to dh:rt-ica — use dh:rt-ica at the S2 implementation gate where missing inputs must halt execution.
Scientific validation protocol for verifying fixes work through observation, not assumption. Use when claiming a bug fix, code change, refactoring, or implementation is complete — enforces reproduce-broken-state then define-success-criteria then apply-fix then verify-outcome. Success means observing intended behavior, not absence of errors.
Orchestrator delegation workflows for linting. Guides orchestrators on when and how to delegate to linting-root-cause-resolver and post-linting-architecture-reviewer agents. Use when orchestrating linting tasks, delegating quality checks, or reading linting resolution reports.
Linter-specific resolution workflows for ruff, mypy, pyright, and basedpyright. Provides systematic root-cause analysis procedures, suppression gates, and verification steps. Use when resolving linting errors as a sub-agent, implementing fixes systematically, or conducting type flow analysis.
Comprehensive linting and formatting verification workflows. Provides automatic format-lint-resolve pipelines for orchestrators and sub-agents. Use when running linters, fixing ruff/mypy/bandit errors, ensuring code quality before completion, or resolving linting issues systematically.
This skill should be used when the user asks to lint Perl code, run perlcritic, check Perl style, format Perl code, run perltidy, or mentions Perl Critic policies, code formatting, or style checking.
Assess a plugin and create refactoring task files for parallel agent execution. Use when you need to analyze a plugin structure, score its quality, and generate a phased refactoring plan with design map and implementation tasks.
Design pattern for converting rule-following, checklist, or rubric skills into a fan-out map-reduce ensemble of parallel rigid sub-agents with corroboration-weighted merge; worker model tier and diversity are knobs matched to inference load and stakes, not fixed values. Apply when creating or refactoring a skill or agent that applies 10+ independent criteria in a single pass. Triggers on: 'review against a checklist', 'fan out', 'map reduce review', 'ensemble', 'split the rules', 'apply rubric', or any large ruleset being applied by one agent in one pass. NOT for tight single-pass transforms or rulesets under 5 criteria.
Use when refactoring is complete and needs validation. Performs holistic review of completed plugin refactoring, validates improvements against original assessment score, checks for documentation drift, and creates follow-up task files if issues remain
Use when a refactoring task file exists from /assessor and tasks need execution. Reads task files, resolves dependencies, delegates to specialist agents (SKILL_SPLIT, AGENT_OPTIMIZE, DOC_IMPROVE), and tracks completion with parallel orchestration
Use when checking skill quality, validating frontmatter before commit, or diagnosing validator warnings. Runs the plugin validator on a skill, agent, or plugin directory — reports token complexity, broken links, frontmatter issues, and structural problems. Pass the path as an argument.
Start a complete plugin refactoring workflow that analyzes plugin structure, creates a refactoring plan with tasks, and guides through execution. Use when you need to refactor an entire plugin — triggers assessment, design, planning, and parallel agent execution phases.
Assess and refactor oversized or multi-domain skills. First determines whether splitting or references/ extraction is appropriate — then executes the correct action. Use when a skill exceeds token thresholds (SK006/SK007) or covers multiple independent domains. Performs candidate assessment before any structural changes; cohesive single-intent skills are redirected to references/ extraction instead of splitting. When splitting is warranted — domain analysis gate, split plan, new SKILL.md generation, validation, and backwards-compatible facade conversion.
Start or complete a specific refactoring task from a task file. Use when a sub-agent needs to pick up a refactoring task, update its status, implement acceptance criteria, and run verification steps.
Runs structured Python cleanup and modernization — static analysis via prek/ruff, smell investigation to root cause, typed-boundary hardening by inventorying Any usage, and modernization within the project's requires-python lane. Use when refactoring Python code, removing dead code, hardening type boundaries, or running a modernization pass on a file or scope.