2 028 code review skills from 387 authors. They read someone else's code and work through changes before those land. Half of them fit into 1 567 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 250 copies of these same skills sitting in other people's repositories — counted once here, not 250 times.
2 028 unique 387 authors 1 260 updated this month 273 from vendors
Configures and implements git hooks using pre-commit or prek (Rust-based drop-in replacement) for automated code quality checks, formatting, linting, and commit message processing. Use when setting up .pre-commit-config.yaml, implementing prepare-commit-msg or commit-msg stage hooks, designing .pre-commit-hooks.yaml hook definitions for distribution, troubleshooting hook installation or execution, or managing hook stages across multi-language projects.
Use when working with Python tooling — uv package management, Hatchling build backend, ty or mypy type checker configuration, ruff linting, pre-commit hook setup, TOML read-write with tomlkit or tomllib, or PyPI packaging and release workflows. Routes to standalone specialist skills for deep dives on any single tool.
Reviews Python code across 9 dimensions — type safety, error handling, security, performance, modern patterns, design clarity, typed-boundary compliance, test quality, and documentation. Use when performing code review, PR review, pre-merge quality checks, or assessing Python for security vulnerabilities, bare except clauses, Any usage outside boundaries, or missing input validation at system boundaries.
Executes the implementation phase of the python-engineering stinkysnake modernization workflow. Use when stinkysnake phases 1-8 are complete — modernization plan reviewed, interfaces designed, and failing tests written. Implements functions in dependency order (types, data structures, utilities, core logic, integration, entry points) applying modern Python patterns (Protocol, dataclass, Pydantic, modern type annotations, httpx, orjson). Runs iterative pytest loops until all tests pass, then verifies with static analysis via prek or ruff. Success criteria — all tests pass, no type errors, no lint errors, coverage meets project threshold.
Nine-phase Python quality improvement system for file paths passed as arguments. Runs prek/ruff/ty static analysis with auto-fixes, inventories Any types and typing gaps, plans Protocol/Generic/TypeGuard/TypedDict/dataclass modernization, forks a code-reviewer agent to critique the plan, refines the plan, discovers documentation changes, designs interfaces first, forks python-pytest-architect for failing tests, then hands off to snakepolish for implementation. Use when eliminating Any types, addressing technical debt, applying modern Python 3.11+ patterns, modernizing library usage (httpx, orjson), or refactoring for stronger type safety.
Use when orchestrating a Python development task via specialized agents. Activates on "build a Python CLI", "add a feature", "write tests", "refactor Python code", "debug Python", "code review", or any multi-agent Python workflow. Invoke as /orchestrate with a task description or alone to use conversation context.
Use when setting up automated code quality checks on git commit, configuring .pre-commit-config.yaml, implementing git hooks for formatting or linting, creating prepare-commit-msg hooks, or distributing a tool as a pre-commit hook. Covers pre-commit and prek for multi-language projects.
Comprehensive Python code review checking patterns, types, security, and performance. Use when reviewing Python code for quality issues, when auditing code before merge, or when assessing technical debt in a Python codebase.
Use as the routing layer for Python development tasks — matches task descriptions against trigger lists and activates specialist skills before starting work. Covers Typer, Rich, Textual, FastMCP/MCP, ty type checker, uv, Hatchling, TOML editing, pre-commit/prek, async Python, PyPI packaging, complex linting, and technical debt modernization.
Progressive Python quality improvement with static analysis, type refinement, modernization planning, plan review, and test-driven implementation. Use when addressing technical debt, eliminating Any types, applying modern Python patterns, or refactoring for better design.
Swift iOS architecture guidance and playbooks for MVVM, MVI, TCA, Clean Architecture, VIPER, MVP, Coordinator, and Reactive patterns. Use when designing, implementing, refactoring, or reviewing the architecture of a SwiftUI or UIKit feature, module, or codebase.
>- Use this skill BEFORE drafting any agentic primitive module (skill, persona scoping file, scope-attached rule file, orchestrator workflow) or when refactoring an existing one. Activate whenever the task asks to design, restructure, or critique an agentic module across any agent harness (Claude Code, Copilot, Cursor, OpenCode, Codex), or when the task asks to make a workflow cost-effective, route model calls by capability, design for cache discipline, prune token spend, or pick a model class. This skill drives an 8-step disciplined design process whose output is mermaid diagrams + an interface sketch + a persisted plan (including a cost projection) that the calling thread (or a coder persona it loads) then turns into natural-language modules. Do not skip to natural-language drafting before the design artifacts exist.
Refactor discipline for existing codebases. Enforces scope control, migration safety, compatibility, observability, and tests to keep refactors reviewable and low-risk.
Use when reviewing implemented Kotlin Multiplatform / Compose Multiplatform code for architecture consistency, business-logic placement, state correctness, concurrency, Compose quality, design-system usage, security, performance, resilience, and maintainability.
Use when designing, reviewing, or refactoring module boundaries in KMP or Android projects — feature, data, app, and common modules, dependency direction, visibility control, and granularity.
SOLID principles, design patterns, DRY, KISS, and clean code fundamentals. Use when reviewing architecture, checking code quality, refactoring, or discussing design decisions. Triggers on "review architecture", "check code quality", "SOLID principles", "design patterns", or "clean code".
Detect AI-generated code patterns ("slop") in PHP/Laravel and TypeScript/React source — comment narration, generic naming, premature interfaces, defensive overdose, mock-everything tests, and the absence of human "scars". Use when reviewing AI-assisted PRs, auditing code for taste/quality (not metrics — that's technical-debt), or hardening a code-review checklist. Triggers on "review for AI slop", "find AI patterns", "check code feels human", "audit code-quality taste".
PHP 8.x modern patterns, PSR standards, and SOLID principles. Use when reviewing PHP code, checking type safety, auditing code quality, or ensuring PHP best practices. Triggers on "review PHP", "check PHP code", "audit PHP", or "PHP best practices".
Technical debt inventory, prioritization, and audit for PHP/Laravel (MySQL) and Node/TypeScript/React projects. Use when assessing code health, identifying refactoring candidates, planning debt paydown, or auditing a codebase for accumulated debt. Triggers on "audit technical debt", "find tech debt", "debt inventory", "what should we refactor first", or tasks involving code health, security debt, performance debt, data debt, observability debt, debt prioritization, or remediation planning.
| Before ANY significant development task (new feature, refactor, integration, migration), run a complete planning ritual by orchestrating other skills in (estimate time) -> final confirmation. Do not start coding until the battle plan is approved.
| Before adding abstraction, asks "do we need this now?" Activates when proposing factories, abstract classes, config-driven behavior, or "for future extensibility." Resists over-engineering. Three similar lines are better than a premature abstraction.
| Before starting ANY significant task (feature build, refactor, integration, migration, or architectural change), first imagine the project has failed. Generate 3-5 specific failure scenarios, assess risk levels, identify mitigations, then adjust the implementation plan to address high-risk items FIRST. Do not start coding until the pre-mortem is acknowledged.
| When refactoring, rewriting, or migrating critical code paths, orchestrate a and prove-it with built-in implementation phase. Prevents "refactor broke production" disasters. Activates on "refactor", "rewrite", "migrate", or "clean up" for non-trivial code.
| Before making changes, verifies they match what was actually requested. Activates when about to modify files, add features, or refactor code. Catches scope creep before it happens - no "while I'm here" improvements.
>- This skill is specifically for the Clawpatch CLI (openclaw/clawpatch, says "review with clawpatch", "run clawpatch", "clawpatch fix", "find bugs with clawpatch", "clawpatch report/findings", "clawpatch open-pr", wants to dispatch subagents to fix Clawpatch findings in parallel, or otherwise names Clawpatch or one of its commands. Do NOT use it for generic "review this code", "find bugs", or "code review" requests that don't involve Clawpatch — those belong to a different tool.
Diagnose data races, convert callback-based code to async/await, implement actor isolation patterns, resolve Sendable conformance issues, and guide Swift 6 migration. Use when developers mention: (1) Swift Concurrency, async/await, actors, or tasks, (2) "use Swift Concurrency" or "modern concurrency patterns", (3) migrating to Swift 6, (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 optimization, (8) concurrency-related linter warnings (SwiftLint or similar; e.g. async_without_await, Sendable/actor isolation/MainActor lint).
Write, review, or improve SwiftUI code following best practices for state management, view composition, performance, macOS-specific APIs, and iOS 26+ Liquid Glass adoption. Use when building new SwiftUI features, refactoring existing views, reviewing code quality, or adopting modern SwiftUI patterns.
Build and TypeScript error resolution specialist. Use PROACTIVELY when build fails or type errors occur. Fixes build/type errors only with minimal diffs, no architectural edits. Focuses on getting the build green quickly.
Expert code review specialist. Proactively reviews code for quality, security, and maintainability. Use immediately after writing or modifying code. MUST BE USED for all code changes.
Expert planning specialist for complex features and refactoring. Use PROACTIVELY when users request feature implementation, architectural changes, or complex refactoring. Automatically activated for planning tasks.
Dead code cleanup and consolidation specialist. Use PROACTIVELY for removing unused code, duplicates, and refactoring. Runs analysis tools (knip, depcheck, ts-prune) to identify dead code and safely removes it.
Use when separating logic from SwiftUI views, choosing architecture patterns, refactoring view files, or asking 'where should this code go', 'how do I organize my SwiftUI app', 'MVVM vs TCA vs vanilla SwiftUI', 'how do I make SwiftUI testable' - comprehensive architecture patterns with refactoring workflows for iOS 26+
Use when implementing navigation patterns, choosing between NavigationStack and NavigationSplitView, handling deep links, adopting coordinator patterns, or requesting code review of navigation implementation - prevents navigation state corruption, deep link failures, and state restoration bugs for iOS 18+
Create or update GitHub pull requests using the repository-required workflow and template compliance. Use when asked to create/open/update a PR so the assistant reads `.github/pull_request_template.md`, fills every template section, preserves markdown structure exactly, and marks missing data as N/A or None instead of skipping sections.
Automated code review for local branches, PRs, commits, and files. Supports single-agent review with interactive fix selection, or multi-agent deep review with reviewer-verifier adversarial mechanism and risk-based auto-fix.
Rich downstream visualisation and reporting for bulk RNA-seq differential expression and scRNA marker/contrast outputs.
Facilitates deliberate skill development during AI-assisted coding. Offers interactive learning exercises after architectural work (new files, schema changes, refactors). Use when completing features, making design decisions, or when user asks to understand code better. Supports the user's stated goal of understanding design choices as learning opportunities.
Write, review, or improve Swift APIs using Swift API Design Guidelines for naming, argument labels, documentation comments, terminology, and general conventions. Use when designing new APIs, refactoring existing interfaces, or reviewing API clarity and fluency.
> Create high-quality Pull Requests with conventional commits and proper descriptions.
FastAPI best practices and conventions. Use when working with FastAPI APIs and Pydantic models for them. Keeps FastAPI code clean and up to date with the latest features and patterns, updated with new versions. Write new code or refactor and update old code.
Provides CI/CD pipeline configuration using GitHub Actions for Golang projects. Covers testing, linting, SAST, security scanning, code coverage, Dependabot, Renovate, GoReleaser, code review automation, and release pipelines. Use this whenever setting up CI for a Go project, configuring workflows, adding linters or security scanners, setting up Dependabot or Renovate, automating releases, or improving an existing CI pipeline. Also use when the user wants to add quality gates to their Go project.
Provides linting best practices and golangci-lint configuration for Go projects. Covers running linters, configuring .golangci.yml, suppressing warnings with nolint directives, interpreting lint output, and managing linter settings. Use this skill whenever the user runs linters, configures golangci-lint, asks about lint warnings or suppressions, sets up code quality tooling, or asks which linters to enable for a Go project. Also use when the user mentions golangci-lint, go vet, staticcheck, revive, or any Go linting tool.
Continuously modernize Golang code to use the latest language features, standard library improvements, and idiomatic patterns. Use this skill whenever writing, reviewing, or refactoring Go code to ensure it leverages modern Go idioms. Also use when the user asks about Go upgrades, migration, modernization, deprecation, or when modernize linter reports issues. Also covers tooling modernization: linters, SAST, AI-powered code review in CI, and modern development practices. Trigger this skill proactively when you notice old-style Go patterns that have modern replacements.
Configures ESLint v9 flat config and neostandard for JavaScript and TypeScript projects, including migrating from legacy `.eslintrc*` files or the `standard` package. Use when you need to set up or fix linting with `eslint.config.js` or `eslint.config.mjs`, troubleshoot lint errors, configure neostandard rules, migrate from `.eslintrc` to flat config, or integrate linting into CI pipelines and pre-commit hooks.
Master ES6+ features including async/await, destructuring, spread operators, arrow functions, promises, modules, iterators, generators, and functional programming patterns for writing clean, efficient JavaScript code. Use when refactoring legacy code, implementing modern patterns, or optimizing JavaScript applications.
NestJS best practices and architecture patterns for building production-ready applications. This skill should be used when writing, reviewing, or refactoring NestJS code to ensure proper patterns for modules, dependency injection, security, and performance.
Standards for Static Analysis (Detekt, Ktlint) and CI/CD Checks. Use when adding or tuning Detekt/Ktlint rules, setting Android Lint as a CI gate, suppressing lint warnings with @Suppress, or configuring code quality checks on pull requests. (triggers: build.gradle.kts, detekt.yml, .detekt/config.yml, detekt, ktlint, lint, @Suppress, abortOnError, jlleitschuh)
Standards for high-quality, persona-driven code reviews. Use when reviewing PRs, critiquing code quality, or analyzing changes for team feedback.