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
Remove AI-generated code slop from a branch. Use when cleaning up AI-generated code, removing unnecessary comments, defensive checks, or type casts. Checks diff against main and fixes style inconsistencies.
Find bugs, security vulnerabilities, and code quality issues in local branch changes. Use when asked to review changes, find bugs, security review, or audit code on the current branch.
Analyzes Move language packages against the official Move Book Code Quality Checklist. Use this skill when reviewing Move code, checking Move 2024 Edition compliance, or analyzing Move packages for best practices. Activates automatically when working with .move files or Move.toml manifests.
查看/更新 GitHub Issue、PR（含评论与 diff），并按团队规范非交互创建或修改 PR；涉及 GitHub Issue/PR 的操作时使用。
查看/更新 GitLab Issue、MR（含评论与 diff），并按团队规范非交互创建或修改 MR/Issue；涉及 GitLab（含自建实例）Issue/MR 的操作时使用。
| Provides thorough code review guidance when users ask for code reviews, PR reviews, or feedback on their code. Activates when users mention reviewing code, checking for issues, or want feedback on implementations.
Maintain consistent code formatting, naming conventions, type safety, and automated code quality standards across PHP and TypeScript/JavaScript. Use this skill when writing or editing any PHP files (.php), TypeScript/JavaScript files (.ts, .tsx, .js, .jsx), when implementing type declarations and return types, when running code formatters (Laravel Pint, Ultracite) or linters, when running static analysis tools (Larastan), when naming variables, functions, classes, or files, when applying DRY principles, when removing dead code, or when preparing code for review or commit.
Follow consistent project structure, version control practices, environment configuration, code review processes, and development conventions across the entire application. Use this skill when organizing project files and directories, when writing commit messages or creating pull requests, when managing environment variables and configuration, when participating in code reviews, when defining testing requirements, when using feature flags, when maintaining changelogs, when documenting setup instructions, or when establishing consistent development practices across the team.
Implement, review, or improve SwiftUI features using the iOS 26+ Liquid Glass API. Use when asked to adopt Liquid Glass in new SwiftUI UI, refactor an existing feature to Liquid Glass, or review Liquid Glass usage for correctness, performance, and design alignment.
Audit and improve SwiftUI runtime performance from code review and architecture. Use for requests to diagnose slow rendering, janky scrolling, high CPU/memory usage, excessive view updates, or layout thrash in SwiftUI apps, and to provide guidance for user-run Instruments profiling when code review alone is insufficient.
Best practices and example-driven guidance for building SwiftUI views and components. Use when creating or refactoring SwiftUI UI, designing tab architecture with TabView, composing screens, or needing component-specific patterns and examples.
Refactor and review SwiftUI view files for consistent structure, dependency injection, and Observation usage. Use when asked to clean up a SwiftUI view’s layout/ordering, handle view models safely (non-optional when possible), or standardize how dependencies and @Observable state are initialized and passed.
Handle code review feedback with technical rigor. Don't blindly agree - verify before implementing.
> Pedantic backend pre-commit and atomic commit Skill for Django/Optimo-style repos. Enforces local AGENTS.md / CLAUDE.md, pre-commit hooks, .security/* helpers, and Monty’s backend engineering taste – with no AI signatures in commit messages.
> Generates weekly code-review digest docs from PR review comments for any GitHub repository. If present, follows project-specific docs/review-digests/AGENTS.md guidelines. Use this to turn a date-bounded set of PR reviews into a structured markdown “newsletter” that captures themes, repeated issues, and concrete takeaways.
> Hyper-pedantic code review skill that emulates Monty's Django4Lyfe backend engineering philosophy and review style. Use this when reviewing or refactoring Python/Django code in this backend repo and you want a strict, correctness-first, multi-tenant-safe, deeply nitpicky review.
> Process code review findings interactively - fix or skip issues from monty-code-review output. Presents issues in severity order, applies fixes, runs quality checks, and updates review documents with status markers.
Request and process code reviews with proper context. Use after completing significant implementation work.
Enforce RED-GREEN-REFACTOR cycle. Use when implementing features, fixing bugs, or writing any production code.
Comprehensive PR review using multi-agent swarm with specialized reviewers for security, performance, style, tests, and documentation. Provides detailed feedback with auto-fix suggestions and merge readiness assessment.
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
Lightning-fast quality check using parallel command execution. Runs theater detection, linting, security scan, and basic tests in parallel for instant feedback on code quality.
Comprehensive code review workflow coordinating quality, security, performance, and documentation reviewers. 4-hour timeline for thorough multi-agent review.
Audits code against CI/CD style rules, quality guidelines, and best practices, then rewrites code to meet standards without breaking functionality. Use this skill after functionality validation to ensure code is not just correct but also maintainable, readable, and production-ready. The skill applies linting rules, enforces naming conventions, improves code organization, and refactors for clarity while preserving all behavioral correctness verified by functionality audits.
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
| Detects non-functional "theater" code that appears complete but doesn't actually work. Use this skill to identify code that looks correct in static analysis but fails during execution, preventing fake implementations from reaching production. Scans for suspicious patterns, validates actual functionality, and reports findings with recommendations.
Comprehensive PR review with multi-agent swarm specialization for security, performance, style, tests, and documentation
Comprehensive GitHub pull request code review using multi-agent swarm with specialized reviewers for security, performance, style, tests, and documentation. Coordinates security-auditor, perf-analyzer, code-analyzer, tester, and reviewer agents through mesh topology for parallel analysis. Provides detailed feedback with auto-fix suggestions and merge readiness assessment. Use when reviewing PRs, conducting code audits, or ensuring code quality standards before merge.
| Use when conducting comprehensive code review for pull requests across multiple quality dimensions. Orchestrates 12-15 specialized reviewer agents across 4 phases using star topology coordination. Covers automated checks, parallel specialized reviews (quality, security, performance, architecture, documentation), integration analysis, and final merge recommendation in a 4-hour workflow.
Comprehensive quality verification and validation through static analysis, dynamic testing, integration validation, and certification gates
Document technical debt, anti-patterns, and patterns to avoid from analyzed frameworks. Use when (1) creating a "Do Not Repeat" list from framework analysis, (2) categorizing observed code smells and issues, (3) assessing severity of architectural problems, (4) generating remediation suggestions, or (5) synthesizing lessons learned across multiple frameworks.
Complete code review workflow for both requesting and receiving reviews. Use when creating PRs, reviewing code, or responding to feedback.
Enforce file line count limits (200 recommended, 300 max) for CODE IMPLEMENTATION files only. Use this when reviewing code, creating files, or when files exceed line limits and need modularization.
Forbid hardcoded values in code. Use this when reviewing code, writing new features, or when magic numbers/strings are detected. Enforces constants, env variables, and config files.
Automatically backs up files, saves diffs, uses agents/skills, and ensures modular code (<200 lines) before any implementation. Use this skill for ALL code changes to ensure safe, reversible, and clean implementations.
语法感知的代码搜索、linting 和重写工具。支持基于 AST 的结构化代码搜索和批量代码转换。
Search GitHub issues, pull requests, and discussions across any repository. Activates when researching external dependencies (whisper.cpp, NAudio), looking for similar bugs, or finding implementation examples.
Use when completing tasks, implementing major features, or before merging to verify work meets requirements - dispatches code-reviewer subagent to review implementation against plan or requirements before proceeding
Use when you've developed a broadly useful skill and want to contribute it upstream via pull request - guides process of branching, committing, pushing, and creating PR to contribute skills back to upstream repository
Follow project-wide development conventions including project structure, version control practices, environment configuration, documentation, dependency management, and code review processes. Use this skill when organizing files/directories, writing commit messages, managing branches, configuring environments, handling secrets, maintaining documentation, or establishing team workflows. Apply when working with project structure, README files, .gitignore, environment variables, dependency files (package.json, requirements.txt), feature flags, changelogs, or any aspect of project organization and team collaboration that requires consistency across the development lifecycle.
This skill should be used when updating the project CHANGELOG, tracking requirement changes, recording design decisions, or documenting version history. Uses git-diff to detect and categorize changes to both code and requirements. Trigger on "changelog", "version history", "what changed", or after significant commits.
Automatically trigger review agents after task completion. Use when strategic-planner finishes planning tasks (calls plan-consultant) or when main agent completes coding tasks in /implement workflow (calls code-reviewer). Triggers on phrases like "plan complete", "implementation done", "coding finished", "ready for review".
AI-powered code review tool that analyzes code for bugs, style issues, and improvements
Review code for bugs, security vulnerabilities, performance issues, and best practices. Use this skill whenever the user asks for a code review, shares code and wants feedback, mentions "review this", "check my code", "what's wrong with this code", pastes a diff or PR, or asks about code quality. Also trigger when users share code snippets and ask general questions that would benefit from a thorough review, even if they don't explicitly say "review".
Write AST-based code search and rewrite rules using ast-grep YAML. Create linting rules, code modernizations, and API migrations with auto-fix. Use when the user mentions ast-grep, tree-sitter patterns, code search rules, lint rules with YAML, AST matching, or code refactoring patterns.
Analyze code quality based on "Clean Code" principles. Identify naming, function size, duplication, over-engineering, and magic number issues with severity ratings and refactoring suggestions. Use when the user requests code review, quality check, refactoring advice, Clean Code analysis, code smell detection, or mentions terms like 代码体检, 代码质量, 重构检查.
Refactor high-complexity React components in Dify frontend. Use when `pnpm analyze-component --json` shows complexity > 50 or lineCount > 300, when the user asks for code splitting, hook extraction, or complexity reduction, or when `pnpm analyze-component` warns to refactor before testing; avoid for simple/well-structured components, third-party wrappers, or when the user explicitly wants testing without refactoring.
Implement, review, or improve SwiftUI features using the iOS 26+ Liquid Glass API. Use when asked to adopt Liquid Glass in SwiftUI UI, refactor to Liquid Glass, or review Liquid Glass usage.