Total 54,018 skills, Code Quality has 2434 skills
Showing 12 of 2434 skills
Python coding standards with automatic version detection. Use when writing, reviewing, or refactoring Python to ensure adherence to LBYL exception handling patterns, modern type syntax (list[str], str | None), pathlib operations, ABC-based interfaces, absolute imports, and explicit error boundaries at CLI level. Also provides production-tested code smell patterns from Dagster Labs for API design, parameter complexity, and code organization. Essential for maintaining erk's dignified Python standards.
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.
Retrieve code review results from DeepSource — issues, vulnerabilities, report cards, and analysis runs. Use when asked about code quality, security findings, dependency CVEs, coverage metrics, or analysis status.
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".
Coding conventions enforcement agent. Auto-invoked when writing new code, reviewing code quality, adding headers, or checking documentation compliance across Python, TypeScript/JavaScript, and C#/.NET.
This skill should be used when the user asks to "analyze skill quality", "evaluate this skill", "review skill quality", "check my skill", or "generate quality report". Evaluates local skills across description quality, content organization, writing style, and structural integrity.
Review protocol code for chain halt risks, non-determinism, and onchain behavior bugs
Guidelines for using modern Dart features (v3.0 - v3.10) such as Records, Pattern Matching, Switch Expressions, Extension Types, Class Modifiers, Wildcards, Null-Aware Elements, and Dot Shorthands.
Fix findings from the active review session — reads reviewer findings files, applies fixes by priority, and updates the resolution log. Use after pasting reviewer output into findings files.
Opinionated guide to software design principles and architectural patterns. Use when reviewing code design, planning feature architecture, asking "is this the right design?", "how should I structure this?", or requesting design philosophy guidance. Triggers on questions about SOLID, DRY, KISS, YAGNI, Clean Architecture, DDD, hexagonal architecture, composition vs inheritance, coupling, cohesion, or any software design trade-off discussion.
Find dead code using parallel subagent analysis and optional CLI tools, treating code only referenced from tests as dead. Use when the user asks to "find dead code", "find unused code", "find unused exports", "find unreferenced functions", "clean up dead code", or "what code is unused". Analysis-only — does not modify or delete code.
Use this skill to review pull requests against coding standards and best practices. Invoke when reviewing code changes before merge.