메뉴
Run linting and formatting checks on the codebase. Use this skill when code changes are made and need static analysis validation. Runs ruff (Python) and eslint+prettier (TypeScript/React) depending on the project type. Invoke after implementation and before code review.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | linter |
| description | Run linting and formatting checks on the codebase. Use this skill when code changes are made and need static analysis validation. Runs ruff (Python) and eslint+prettier (TypeScript/React) depending on the project type. Invoke after implementation and before code review. |
You are a code quality engineer. Run all relevant linters on the project and fix any issues found.
Examine the project directory to determine the stack:
pyproject.toml, *.py files → use ruffpackage.json, eslint.config.*, *.tsx files → use eslint + prettier# Check for issues
uv run ruff check . --fix
# Format
uv run ruff format .
If ruff is not in dependencies, configure it:
ruff to dev dependencies (uv add --dev ruff or add to pyproject.toml)[tool.ruff] section in pyproject.toml with sensible defaults:[tool.ruff]
target-version = "py312"
line-length = 100
[tool.ruff.lint]
select = [
"E", # pycodestyle errors
"W", # pycodestyle warnings
"F", # pyflakes
"I", # isort
"B", # flake8-bugbear
"C4", # flake8-comprehensions
"UP", # pyupgrade
"ARG", # flake8-unused-arguments
"SIM", # flake8-simplify
]
[tool.ruff.lint.isort]
known-first-party = ["domain", "application", "infrastructure"]
uv run ruff check . --fix and uv run ruff format .# ESLint
npx eslint . --fix
# Prettier
npx prettier --write "src/**/*.{ts,tsx}"
If the project has a lint script in package.json, prefer npm run lint or npx eslint ..
Provide a table:
| Linter | Issues found | Auto-fixed | Manual fixes | Remaining |
|----------|-------------|------------|-------------|-----------|
| ruff | X | Y | Z | 0 |
| eslint | X | Y | Z | 0 |
| prettier | X | Y | Z | 0 |
# noqa, // eslint-disable, or @ts-ignore unless the rule is genuinely a false positive, and explain whygit diff --name-only main to scope), unless the user asks for a full lint.eslintrc, ruff.toml, pyproject.toml linter sectionsComprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.
Agent-based development workflow for implementation tasks. Use this skill when the user asks to implement a feature, fix a bug, or make significant code changes. Orchestrates work through phases, requirements gathering, test-first development (TDD), clean architecture implementation, code review, and documentation.
SonarQube issue remediation workflow. Use this skill when the user asks to fix SonarQube issues, run a code quality sweep, or remediate static analysis findings for a project. Retrieves issues via MCP, groups them, presents a fix plan, and implements fixes in batches with test verification.
Deep performance audit for Python and React codebases. Use this skill ANY TIME the user shares code and mentions performance, slow queries, latency, re-renders, optimization, profiling, bottlenecks, or memory issues — even if they don't use the word "audit". Also trigger when the user pastes code and asks "is this efficient?", "why is this slow?", "how can I improve this?", or shares ORM/database code (Django, SQLAlchemy, Prisma, TypeORM) where N+1 query risks are high. Covers: N+1 queries, missing indexes, loop anti-patterns, React re-render storms, missing memoization, bundle bloat, async misuse, memory leaks, caching strategy opportunities (query caching, HTTP caching, client-side caching, cache invalidation triggers), and 20+ other patterns across both stacks.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Analyze a database schema by running SchemaCrawler lint and extracting the full schema via information_schema. Use this skill whenever the user wants to audit a database schema, check normalization, detect missing indexes, redundant indexes, nullable FK columns, inconsistent data types, design smells, or get improvement recommendations.