924건 · 관련도순
Autonomous iterative refactoring workflow. Scans for tactical code quality improvements (DRY, dead code, naming, complexity), implements through SMEs, verifies with QA, commits atomically, and loops until no improvements remain.
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Autonomous technical lead. Takes commander's intent and drives a project to completion through an OODA loop over implementation, refactoring, review, and bug-hunting skills. Has broad authority — creates tickets, commits, invokes any skill — and only escalates via andon cord for irreversible actions, public releases, or genuinely blocking decisions. User acts as product owner; skill acts as tech lead.
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C++ coding standards based on the C++ Core Guidelines (isocpp.github.io). Use when writing, reviewing, or refactoring C++ code to enforce modern, safe, and idiomatic practices.
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React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.
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React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
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Complete Claude Code productivity system — project setup, prompting patterns, sub-agent orchestration, context management, debugging, refactoring, TDD, and shipping 10X faster. Zero scripts needed.
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Enforce the no-useEffect rule when writing or reviewing React code. Activate when writing React components, refactoring existing useEffect calls, reviewing PRs that introduce useEffect, or when an agent adds useEffect "just in case." Provides five replacement patterns and the useMountEffect escape hatch.
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Guide for writing idiomatic Rust code based on Apollo GraphQL's best practices handbook. Use this skill when: (1) writing new Rust code or functions, (2) reviewing or refactoring existing Rust code, (3) deciding between borrowing vs cloning or ownership patterns, (4) implementing error handling with Result types, (5) optimizing Rust code for performance, (6) writing tests or documentation for Rust projects.
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Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or when debugging dependency cycles between application layers.
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Uses the local pruner indexer to gather relevant code context before making changes, debugging, refactoring, or answering questions about this repository.
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Generate code context for coding tasks. Run before code changes, bug fixes, or refactoring to get execution paths, key files, symbols, tests, and snippets.
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Generate synthetic code context for LLM coding tasks. Automatically use this before making code changes, fixing bugs, refactoring, or answering questions about the codebase. Provides execution paths, relevant files, symbols, tests, and code snippets.
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Improve or review ordinary dygo code changes for simplicity, focused scope, canonical ownership, clear boundaries, and verifiable behavior. Use for normal implementation and refactoring quality; use dygo-thermonuclear-review only for an explicitly severe audit.
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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.
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Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.
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Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing. Uses GPT-5.2 by default for state-of-the-art software engineering.
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Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.
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Create modern Angular standalone components following v20+ best practices. Use for building UI components with signal-based inputs/outputs, OnPush change detection, host bindings, content projection, and lifecycle hooks. Triggers on component creation, refactoring class-based inputs to signals, adding host bindings, or implementing accessible interactive components.
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Systematic framework for resurrecting and modernizing legacy codebases through archaeology, resurrection, and rejuvenation phases. Activate on "legacy code", "inherited codebase", "no documentation", "technical debt", "resurrect", "modernize". NOT for greenfield projects or well-documented active codebases.
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Load when creating, auditing, refactoring, or repairing an Agent Skill for reuse, governance, and runtime efficiency.
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Codebase audit + refactoring workflow. Dead code detection, God Object splitting, duplicate function removal, design flaw identification, frontier comparison verification. Triggered by "audit" ("감사"), "dead code" ("데드코드"), "refactor" ("리팩토링"), "god object", "duplication" ("중복"), "design flaw" ("설계 결함") keywords.
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Code review from the Kent Beck Simple Design 4 Rules perspective. God Object splitting, SRP, duplication removal, naming, cyclomatic complexity. Triggered by "kent beck", "simple design", "simplify", "refactoring" ("리팩토링"), "refactor", "god object", "SRP" keywords.
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Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.
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Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.