メニュー
Query AI-generated overview of GitHub repositories via DeepWiki MCP. Use when needing a fast high-level understanding of a repository's architecture and design decisions without fetching full repository.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/archibate/dotfiles-claude --skill deepwikiコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
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 職業分類に基づく
SKILL.md を表示中
| name | deepwiki |
| description | Query AI-generated overview of GitHub repositories via DeepWiki MCP. Use when needing a fast high-level understanding of a repository's architecture and design decisions without fetching full repository. |
| allowed-tools | ["Bash(*mcpcall.py*:*)"] |
| disable-model-invocation | true |
AI-powered documentation for GitHub repositories. Browse auto-generated docs, explore topic structures, and ask questions about any public repo. Powered by DeepWiki MCP. No API key required.
Get a list of documentation topics for a repository. Use this first to discover what's documented.
repoName (required): GitHub repo in owner/repo formatscripts/mcpcall.py read_wiki_structure repoName:"facebook/react"
scripts/mcpcall.py read_wiki_structure repoName:"anthropics/claude-code"
View full documentation about a repository.
repoName (required): GitHub repo in owner/repo formatscripts/mcpcall.py read_wiki_contents repoName:"facebook/react"
scripts/mcpcall.py read_wiki_contents repoName:"pallets/flask"
Ask any question about a repository and get an AI-powered, context-grounded response.
repoName (required): GitHub repo (owner/repo string) or array of up to 10 reposquestion (required): the question to askscripts/mcpcall.py ask_question repoName:"facebook/react" question:"How does the reconciliation algorithm work?"
scripts/mcpcall.py ask_question repoName:"pallets/flask" question:"How are blueprints registered?"
scripts/mcpcall.py ask_question --args '{"repoName": ["pallets/flask", "django/django"], "question": "How do these frameworks handle middleware?"}'
| Scenario | Tool |
|---|---|
| Discover what topics are documented | read_wiki_structure |
| Read full repo documentation | read_wiki_contents |
| Ask a specific question about a repo | ask_question |
| Compare multiple repos | ask_question with array of repos |
read_wiki_structure to see available topics before diving into full contents.ask_question supports up to 10 repos at once for cross-project comparisons.ask_question for targeted queries — it's faster than reading full wiki contents./repo-cache to clone and read).