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Found 817 Skills
Multi-language SOLID detection rules. Project type detection, interface locations, file size limits per language.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.
Comprehensive GitHub code review with AI-powered swarm coordination
Refactor, simplify, or clean up code for improved maintainability without changing business logic
Orchestrate comprehensive code review across ~12 AI reviewers. 5 persona reviewers (Grug, Carmack, Ousterhout, Beck, Fowler) via Moonbridge, 4 domain specialists (security-sentinel MANDATORY, performance, data integrity, architecture) via Task, plus hindsight-reviewer and synthesis. Use when: code review, PR review, pre-merge quality check.
Full code review, fix, quality, PR workflow. Chains review-branch, address-review, check-quality, and pr. Use when: code complete and ready for PR, want comprehensive review before shipping.
Systematic code refactoring following Martin Fowler's catalog. Methodologies: characterization tests, Red-Green-Refactor, incremental transformation. Capabilities: SOLID compliance, DRY cleanup, code smell detection, complexity reduction, legacy modernization, design patterns, functional programming patterns. Actions: refactor, extract, inline, rename, move, simplify code. Keywords: refactor, SOLID, DRY, code smell, complexity, extract method, inline, rename, move, clean code, technical debt, legacy code, design pattern, characterization test, Red-Green-Refactor, functional programming, higher-order function, immutability, pure function, composition, currying, side effects. Use when: improving code quality, reducing technical debt, applying SOLID principles, fixing DRY violations, removing code smells, modernizing legacy code, applying design patterns.
Code review practices with technical rigor and verification gates. Practices: receiving feedback, requesting reviews, verification gates. Capabilities: technical evaluation, evidence-based claims, PR review, subagent-driven review, completion verification. Actions: review, evaluate, verify, validate code changes. Keywords: code review, PR review, pull request, technical feedback, review feedback, completion claim, verification, evidence-based, code quality, review request, technical rigor, subagent review, code-reviewer, review gate, merge criteria. Use when: receiving code review feedback, completing major features, making completion claims, requesting systematic reviews, validating before merge, preventing false completion claims.
Use when reviewing Rust code for craft quality, when writing new Rust code that should follow professional patterns, or when the user asks to judge, audit, or improve Rust code against best practices. Covers type design, function signatures, trait architecture, error handling, visibility, macros, testing, and performance patterns.
This skill should be used when the user asks to "remove AI slop", "clean up AI code", "remove AI patterns", "fix AI-generated code", "clean up PR", "remove unnecessary comments", "fix defensive checks", or mentions AI slop, AI code cleanup, or code quality issues from AI-assisted development. Identifies and removes unnecessary comments, defensive checks, type casts to any, and style inconsistencies.
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).
Use when you need to request a code review for a PR/MR and want a consistent review brief (context, scope, risk areas, test instructions, acceptance criteria) before merge.