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Quick 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.
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。
SOC 職業分類に基づく
Use the `bilibili-api-python` async library (400+ endpoints) for any Bilibili programmatic operation — videos, users, favorites, danmaku, live rooms, comments, search, uploads. This skill should be used whenever user asked for any Bilibili operation.
Fetch authoritative, current, version-specific documentation for libraries, SDKs, APIs, and CLI tools via Context7. MUST TRIGGER before writing or editing any non-stdlib library call — including well-known libraries you think you know, since your prior knowledge may be stale. SKIP 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`). Prefer this over web search for library docs.
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.
Periodic distillation: scan the last 5 days of high-quality Claude transcripts in the current project, dedup facts seen across sessions and against existing docs, and propose surgical edits to the right reference docs. Wider-than-daily window avoids 00:00 boundary loss. This skill should be used when the user says "distill recent", "distill session", "distill last week", or asks "what should we learn from recent work".
Extract atomic flashcards from documents/conversations and write them into local Anki via AnkiConnect, using a React-rendered paper-note card template with markdown, collapsible code, KaTeX, and mermaid. Triggers on "flashcards", "flash", "抽认卡", "anki".
This skill should be used when the user sends an image and asks to "analyze this image", "describe this picture", "what's in this image", or any request requiring visual understanding of images. Provides image analysis using Zhipu GLM-4.6V multimodal model.
| name | deepwiki |
| description | Quick 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*:*)"] |
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).