Total 43,928 skills, Code Quality has 2059 skills
Showing 12 of 2059 skills
Detects framework-specific anti-patterns, convention violations, and idiom misuse across PHP/Laravel, React/Next.js, and Python/Django/FastAPI codebases. Loads framework-specific reference guides and checks against framework conventions. Generates severity-scored findings with copy-pasteable fix prompts. Trigger phrases: "framework review", "framework check", "laravel best practices", "react best practices", "framework audit", "framework-specific review".
Detects code smells and anti-patterns — long methods, large classes, feature envy, data clumps, primitive obsession, dead code, magic numbers, deep nesting, and more. Uses configurable thresholds from .codeprobe-config.json when available. Trigger phrases: "code smells", "smell check", "anti-patterns", "clean code review".
Analyzes code architecture and structure — layer violations, circular dependencies, god objects, anemic domain models, missing boundaries, directory structure issues, and configuration problems. Generates severity-scored findings with fix prompts. Trigger phrases: "architecture review", "structure check", "layer analysis", "god class".
Audits code for SOLID principle violations — Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, and Dependency Inversion. Identifies classes and methods that violate these principles and generates fix prompts. Trigger phrases: "SOLID check", "solid review", "SRP violation", "dependency inversion".
· Audit AI-generated code slop: hallucinated APIs, over-abstraction, duplicate code, test theater, noisy comments. Triggers: 'slop', 'AI-generated code', 'cleanup', 'overengineered'. Not for prose (use anti-ai-prose).
Codebase intelligence for JavaScript and TypeScript. Free static layer finds unused code (files, exports, types, dependencies), code duplication, circular dependencies, complexity hotspots, architecture boundary violations, and feature flag patterns. Optional paid runtime layer (Fallow Runtime) merges production execution data into the same health report for hot-path review, cold-path deletion confidence, and stale-flag evidence. 90 framework plugins, zero configuration, sub-second static analysis. Use when asked to analyze code health, find unused code, detect duplicates, check circular dependencies, audit complexity, check architecture boundaries, detect feature flags, clean up the codebase, auto-fix issues, merge production coverage, or run fallow.
Automated, project-wide code coverage and CRAP (Change Risk Anti-Patterns) score analysis for .NET projects with existing unit tests. Auto-detects solution structure, runs coverage collection via `dotnet test` (supports both Microsoft.Testing.Extensions.CodeCoverage and Coverlet), generates reports via ReportGenerator, calculates CRAP scores per method, and surfaces risk hotspots — complex code with low test coverage that is dangerous to modify. Use when the user wants project-wide coverage analysis with risk prioritization, coverage gap identification, CRAP score computation across an entire solution, or to diagnose why coverage is stuck or plateaued and identify what methods are blocking improvement. DO NOT USE FOR: targeted single-method CRAP analysis (use crap-score skill), writing tests, running tests without coverage collection, applying test filters, producing TRX reports, or troubleshooting test execution (use run-tests for all of these).
기존 PeachSolution 모듈을 test-data 패턴으로 리팩토링하는 팀 오케스트레이터 스킬. "팀 리팩토링", "레거시 코드 정리", "test-data 패턴으로 변환" 키워드로 트리거. layer=backend|frontend|all 지원, 독립 QA로 확증 편향 방지.
Local-first code intelligence — structural search, symbol context, impact analysis, and dead code detection via typed graph traversal. Use this skill when you need to search a codebase by intent (not just substring), understand how symbols connect, trace change impact before refactoring, find dead code, or get an architecture briefing. Triggers on: search codebase, find symbol, who calls, blast radius, impact analysis, dead code, code graph, structural search, architecture overview, codebase orientation, understand connections, what depends on, find where.
Create a detailed refactor plan with tiny commits via user interview, then file it as a GitHub issue. Use when user wants to plan a refactor, create a refactoring RFC, or break a refactor into safe incremental steps.
Clarify the user’s intent for vague, incomplete, or ambiguous clauses, statements, and requirements before modifying the code.
Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior