9건(Benkapner의 저장소) · 인기순
Use when starting work in a repository under repositories/ that may lack CI configuration. Detects missing CI workflows (GitHub Actions, GitLab CI, CircleCI) and alerts the user to add one. Skips repos marked as research-only.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when the user asks to measure command execution time or optimize a feedback loop. Records explicit measurements and recommends faster alternatives such as unit tests versus integration tests. It is opt-in; it does not run on every command.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Team conventions for Python development — credentials, API clients, LLM response parsing, testing patterns, and data pipeline structure. Covers dotenv loading, retry logic, secret validation, and pipeline anti-patterns.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when implementing features, fixing bugs, or refactoring code that may invalidate existing docs. Detects stale documentation by matching the code diff against in-repo doc files and applies targeted updates. Relevant when code changes rename, remove, or add APIs, fields, config keys, or CLI flags. Also applies when the user says "update docs", "check docs", or "are the docs stale", or when reviewing a branch for documentation accuracy.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Unified verification engine for Python data science projects. Covers environment checks, type checking, linting, tests, security scans, code review with DS anti-patterns, and notebook checks. Commands (/verify, /quality-gate) invoke different subsets of this skill.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
User asks for design, planning, or approach exploration before implementation. Covers new features, components, refactors, or architecture decisions. Creates design docs and proposes approaches with trade-offs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Measurement-driven code refactoring — profile before changing, measure after, keep only if metrics improve. Covers complexity reduction, extraction patterns, and bulk refactoring for mechanical changes across many files.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Scan projects for credential leaks, secrets in code, insecure patterns, LLM API key exposure, PII leakage to external AI services, and .env/.gitignore misconfigurations. Especially useful for data and API integrations, regardless of implementation language.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when committing or pushing changes and the repository needs a version bump. Analyzes commits using conventional commit prefixes to determine whether the next release is a major, minor, or patch increment. Also use when the user asks about versioning, release planning, or changelog generation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.