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Found 819 Skills
Create markdown-based behavioral rules preventing unwanted actions. create hookify rule, behavioral rule, prevent behavior, block command Use when: preventing dangerous commands, blocking debug commits, enforcing conventions DO NOT use when: hook scope (abstract:hook-scope-guide), SDK hooks (abstract:hook-authoring), evaluating hooks (abstract:hooks-eval).
Auto-fix CodeRabbit review comments - get CodeRabbit review comments from GitHub and fix them interactively or in batch
Prepare R packages for CRAN submission by checking for common ad-hoc requirements not caught by devtools::check(). Use when: (1) Preparing a package for first CRAN release, (2) Preparing a package update for CRAN resubmission, (3) Reviewing a package to ensure CRAN compliance, (4) Responding to CRAN reviewer feedback. Covers documentation requirements, DESCRIPTION field standards, URL validation, examples, and administrative requirements.
Adversarial code review using the opposite model. Spawns 1–3 reviewers on the opposing model (Claude spawns Codex, Codex spawns Claude) to challenge work from distinct critical lenses. Triggers: "adversarial review".
Comprehensive code investigation and audit tool. Discovers all project features, then dispatches parallel subagents to analyze issues, risks, dead code, missing functionality, and redundancies. Produces a prioritized risk report. Use this skill when the user asks to "investigate code", "audit project", "find risks", "check code quality", "analyze codebase", "what's wrong with this code", "project health check", "code review entire project", "find dead code", "find redundant code", or any request for a thorough codebase analysis.
Type-driven design principle: transform unstructured data into structured types at system boundaries, making illegal states unrepresentable. Use when writing or reviewing code that validates input, designs data types, defines function signatures, handles errors, or models domain logic. Use when you see validation functions that return void/undefined, redundant null checks, stringly-typed data, boolean flags controlling behavior, or functions that can receive data they shouldn't. Triggers on: "parse don't validate", "type-driven design", "make illegal states unrepresentable", "input validation", "data modeling", "refactor types", "strengthen types", "smart constructor", "newtype", "branded type".
Audit rapidly generated or AI-produced code for structural flaws, fragility, and production risks.
Skill for creating custom lint rules by leveraging the existing linter ecosystems of various programming languages. This is a linter designed for AI Agents rather than humans, and its error messages function as correction instruction prompts for AI. Create custom rules in the `lints/` directory using standard methods for each language, including Rust (dylint), TypeScript/JavaScript (ESLint), Python (pylint), Go (golangci-lint), etc. Use this skill in the following scenarios: (1) When you want AI to enforce project-specific coding rules; (2) When you want to create lint rules that output AI-readable correction instructions when violations occur; (3) When you want to enforce naming conventions, structural patterns, and consistency rules through AI-driven linting. Triggers: "Create a linter rule", "Add a lint rule", "Enforce this pattern", "AI linter", "Custom lint", "Code rules", "Naming rules", "Structural rules", "create a linter rule", "add a lint rule", "enforce this pattern", "AI linter".
Global Agent rules, including language, response style, debugging priority, engineering quality baseline, mandatory code metric limits, security baseline, test verification standards and Skills routing table. Applicable to all programming tasks.
Use when the user asks to perform a code review, review code changes, analyze a diff, or audit code quality. Runs a structured review of git diff output covering security, correctness, performance, maintainability, and style. Produces a markdown report saved as a .md file named after the current branch.
Comprehensive skill for 89 refactoring techniques and code smells with PHP 8.3+ examples. Covers composing methods, moving features, organizing data, simplifying conditionals, simplifying method calls, dealing with generalization, and detecting 22 code smells across bloaters, OO abusers, change preventers, dispensables, and couplers.
Comprehensive Python expertise covering language fundamentals, idiomatic patterns, software design principles, and production best practices. Use when writing, reviewing, debugging, or refactoring Python code. Triggers: Python, .py files, pip, uv, pytest, dataclasses, asyncio, type hints, or any Python library.