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Found 819 Skills
Comprehensively reviews Python libraries for quality across project structure, packaging, code quality, testing, security, documentation, API design, and CI/CD. Provides actionable feedback and improvement recommendations. Use when evaluating library health, preparing for major releases, or auditing dependencies.
QLTY During Development
Research-to-implement pipeline chaining 5 MCP tools with graceful degradation
Execute implementation plan tasks with TDD workflow, auto-commit, and phase gates. Use when user says "build it", "start building", "execute plan", "implement tasks", "ship it", or references a track ID. Do NOT use for planning (use /plan) or scaffolding (use /scaffold).
Comprehensive pull request review using specialized agents
Bootstrap new projects with strong typing, linting, formatting, and testing. Supports Python, TypeScript, and other languages with research fallback.
This skill should be used when cleaning up codebases that have accumulated dead code, redundant implementations, and orphaned artifacts — especially codebases maintained by coding agents. Triggers on "find dead code", "clean up unused code", "remove redundant code", "prune this codebase", "dead code sweep", "code cleanup", or when a codebase has gone through multiple agent-driven refactors and likely contains overlooked remnants. Systematically identifies cruft, categorizes findings, and removes confirmed dead code with user approval.
Conduct rigorous, adversarial code reviews with zero tolerance for mediocrity. Use when users ask to "critically review" my code or a PR, "critique my code", "find issues in my code", or "what's wrong with this code". Identifies security holes, lazy patterns, edge case failures, and bad practices across Python, R, JavaScript/TypeScript, SQL, and front-end code. Scrutinizes error handling, type safety, performance, accessibility, and code quality. Provides structured feedback with severity tiers (Blocking, Required, Suggestions) and specific, actionable recommendations.
Universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development.
Applies a modified Fagan Inspection methodology to systematically resolve persistent bugs and complex issues. Use when multiple previous fix attempts have failed repeatedly, when dealing with intricate system interactions, or when a methodical root cause analysis is needed. Do not use for simple troubleshooting. Triggers after multiple failed debugging attempts on the same complex issue.
Architecture analysis, violation detection, and pattern validation. USE WHEN: reviewing code architecture, identifying violations, verifying patterns, updating technical documentation. Reference: docs/02-architecture/ARCHITECTURE.md Examples: <example> Context: User wants to check if code follows architecture. user: "Analyze if the payment module follows our architecture" assistant: "I'll use architecture-analyzer to review against ARCHITECTURE.md." <commentary>Architectural review is architecture-analyzer specialty.</commentary> </example> <example> Context: Need to identify technical debt. user: "Find architectural violations in the services layer" assistant: "I'll use architecture-analyzer to scan for violations." <commentary>Violation detection is architecture-analyzer responsibility.</commentary> </example>
Analyzes Java code against industry best practices and evaluates design principles including SOLID, exception handling, thread safety, and resource management. Reviews naming conventions, Stream API usage, Optional patterns, and general code quality. Use when reviewing Java files, checking code quality, evaluating exception handling, or auditing resource management.