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Found 707 Skills
Reduce cyclomatic complexity with targeted refactoring strategies
Apply systematic code refactoring with small steps, clear boundaries, and proven techniques. Use when improving existing code, reducing technical debt, cleaning up legacy code, or when user mentions refactoring, code cleanup, or code improvement.
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.
Generate a persistent .nexus-map/ knowledge base that lets any AI session instantly understand a codebase's architecture, systems, dependencies, and change hotspots. Use when starting work on an unfamiliar repository, onboarding with AI-assisted context, preparing for a major refactoring initiative, or enabling reliable cold-start AI sessions across a team. Produces INDEX.md, systems.md, concept_model.json, git_forensics.md and more. Requires shell execution and Python 3.10+. For ad-hoc file queries or instant impact analysis during active development, use nexus-query instead.
Analyze code for patterns, complexity, dependencies, and quality. Use when: code review, refactoring, understanding codebases.
Systematic refactoring of codebase components through a structured 3-phase process. Use when asked to refactor, restructure, or improve specific components, modules, or areas of code. Produces research documentation, change proposals with code samples, and test plans. Triggers on requests like "refactor the authentication module", "restructure the data layer", "improve the API handlers", or "clean up the payment service".
Systematic codebase quality scan for identifying duplication, redundancy, and improvement opportunities. Use when reviewing a repo's architecture, finding refactoring targets, or assessing code health. Triggers: "scan the repo", "find code duplication", "suggest improvements", "code quality review", "is there redundant code", "refactoring plan", "architecture review".
Deep code simplification, refactoring, and quality refinement. Analyzes structural complexity, anti-patterns, and readability debt, then applies targeted refactoring preserving exact behavior. Language-agnostic: Python, Go, TypeScript/JavaScript, Rust. Use this skill when the goal is simplification and clarity rather than bug-finding. Triggers on: "simplify this code", "clean up my code", "refactor for clarity", "reduce complexity", "make this more readable", "code quality pass", "tech debt cleanup", "run the code refiner", "simplify recent changes", "this code is messy", "too much nesting", "this function is too long", "clean this up before I PR it", "tidy up my code", cyclomatic complexity, cognitive complexity, code smells.
Aggressively clean up a codebase by removing AI slop, dead code, weak types, defensive over-engineering, duplication, and legacy cruft. Orchestrates 8 specialized subagents in parallel to deduplicate code, consolidate types, kill unused code, untangle circular dependencies, strengthen weak types, remove unnecessary try/catch, delete deprecated/legacy paths, and strip unhelpful comments. Use when the user asks to 'clean up the codebase', 'remove slop', 'improve code quality', 'remove dead code', 'kill AI slop', 'tighten types', 'remove legacy code', 'deduplicate code', 'DRY this up', 'untangle dependencies', or wants a thorough code quality pass. Also use when the user mentions code smells, technical debt cleanup, or refactoring for clarity — even if they don't use the word 'slop'.
Principle-engineering posture for production-grade code: reads the repo first, plans before code, matches conventions, pulls latest docs over training recall, and ships the simplest correct change that holds the bar — proper algorithms and data structures, idempotent writes, schema+queries+indexes as one artefact, typed errors, tests in the same diff. Substrate-agnostic; defers to peer skills on their lanes. Use for non-trivial planning, design, implementation, review, or refactoring; RCA and debugging; performance and optimization work; changes touching a database schema, security, infrastructure, or a public API; hardening inherited, vibe-coded, or LLM-generated code (dependency/CVE and migration audits); and over-engineering cleanup ("simplest solution," "YAGNI," "what can we delete").
Code graph navigation skill. Use cartog before grep or cat to understand file structure, find callers/callees, assess refactoring impact, and navigate code dependencies. Supports Python, TypeScript/JavaScript, Rust, Go.
Apply the "How I Made Your Machine" coding style guide to implementation, refactoring, and code review tasks across TypeScript, Rust, and Python. Use when a request asks for this style guide, when improving maintainability and type safety, when modeling domain concepts with explicit variants/types, or when enforcing behavior-first testing.