Query the LLM Wiki — reads index.md first, drills into 3-10 relevant pages, synthesizes an answer with inline [[wikilink]] citations, and offers to file the ans
复制下面这句话,粘贴给 Claude Code、Codex、Cursor 等 AI 编程工具,它会读取安装说明并在你确认后完成安装。
请阅读 https://ai.atlankj.com/install/asset/gh-claude-skills-2bb1ff1e5656 ,按照其中的说明把「wiki-query」安装到你(当前 AI 工具)中。执行前先告诉我将运行的命令和写入的位置,等我确认。
查看 AI 将读取的安装说明正在读取 GitHub 原文…
内容来自 GitHub 原始文件,由原作者维护。在 GitHub 查看
Ask the wiki a question. The librarian reads index.md first, picks relevant pages across categories, synthesizes an answer with citations, and offers to file the answer back into the wiki so your explorations compound.
/wiki-query "<your question>"
/wiki-query "what does the wiki say about sparse autoencoders?"
/wiki-query "compare monosemanticity and polysemanticity across my sources"
/wiki-query "which sources disagree on scaling laws?"
/wiki-query "give me a comparison table of SAE vs linear probing"
wiki/index.md to find relevant pagesengineering/llm-wiki/skills/llm-wiki/scripts/wiki_search.py (BM25)[[sources/xxx]] citations + "Related pages" sectioncomparisons/ or synthesis/)The answer's format follows the question:
| Question shape | Output |
|---|---|
| "What is X?" | Markdown explanation with citations |
| "A vs B" | Comparison table |
| "Give me a slide deck on X" | Markdown synthesis → /wiki-marp to render |
| "Chart the trend in X" | Python script + saved chart in wiki/assets/charts/ |
This command dispatches the wiki-librarian sub-agent. See agents/wiki-librarian.md.
engineering/llm-wiki/skills/llm-wiki/scripts/wiki_search.py — BM25 fallback searchengineering/llm-wiki/skills/llm-wiki/scripts/append_log.py — log filed answers[[wikilink]].→ engineering/llm-wiki/skills/llm-wiki/SKILL.md
→ engineering/llm-wiki/skills/llm-wiki/references/query-workflow.md