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Fetch current docs and code examples for third-party libraries, SDKs, APIs, and CLI tools via Context7. Use before writing or editing non-stdlib library calls — your prior knowledge may be stale. Prefer over web search for library docs.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/archibate/dotfiles-claude --skill context7명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Create or edit agent-facing/LLM prompts using modern prompt-engineering practices. Use this skill before editing agent-facing docs, rule files, references, skills, memory, or any form of LLM prompt. Also use it before writing LLM tests or evaluations. This is mandatory: NEVER skip this skill before writing agent-facing text; MUST use it before editing a file that will be fed to AI agents.
High-quality C++ OOP coding style (archibate / parallel101 lineage) that overrides sloppy AI-default C++. Use this skill WHENEVER writing, editing, refactoring, or reviewing C++ code (.cpp / .h / .hpp / .cc / .cxx), designing C++ classes, interfaces, APIs, or libraries, or when the user mentions C++ design, OOP, design patterns, dependency injection, RAII, or "clean / modern C++". Apply it even when the user does not explicitly ask for a style: the default way models write C++ leans on free functions, public mutable state, raw new/delete, sentinel return codes, and long loose parameter lists — this skill replaces all of that with abstract-class-or-data-class design, dependency injection, type-rich APIs, value-based error handling, and RAII ownership.
Evidence-driven C++ high-performance computing design, profiling, and optimization across algorithmic time/space complexity, data layout, cache and memory behavior, numerics, SIMD, multicore scheduling, and CPU/accelerator pipelines. Use before designing or changing computation-intensive kernels, high-throughput data structures, performance-critical loops, SIMD/OpenMP/TBB/CUDA code, mixed-precision or sparse representations, or when investigating throughput, latency, scaling, cache, bandwidth, compiler-vectorization, or profiling problems.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | context7 |
| description | Fetch current docs and code examples for third-party libraries, SDKs, APIs, and CLI tools via Context7. Use before writing or editing non-stdlib library calls — your prior knowledge may be stale. Prefer over web search for library docs. |
| allowed-tools | ["Bash(*mcpcall.py*:*)"] |
Fetch up-to-date library documentation and code examples. Requires CONTEXT7_API_KEY environment variable.
Skip Context7 for internal/private libraries, stdlib code, raw HTTP/filesystem, shell built-ins, or stable primitives whose signatures haven't changed in years (e.g. json.dumps, os.path).
Resolve a package/product name to a Context7 library ID. Call this before query-docs unless the user provides an ID in /org/project format.
libraryName (required): Official library name (e.g., "Next.js", "Three.js")query (required): What the user needs help with — used to rank results by relevancescripts/mcpcall.py resolve-library-id libraryName:"Next.js" query:"app router setup"
Retrieve documentation and code examples for a resolved library.
libraryId (required): Context7 library ID from resolve-library-id (e.g., "/vercel/next.js")query (required): Specific question — be detailed for better resultsscripts/mcpcall.py query-docs libraryId:"/vercel/next.js" query:"how to set up authentication with JWT"