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Clawhub Skill

该 Skill 通过 npx 运行 create-opc-wiki 包,在指定目录生成个人 LLM wiki 知识库:同步 9 种 Agent 规则文件,提供 /wiki-ingest、/wiki-query、/wiki-lint 三个技能,内置三件 MCP 工具与隐私门控,并可选用 Astro 生成含 sitemap、llms.txt、RSS 的发布站点。

mackding
mackding
热度 33.69
最近更新 2026-05-11 17:45:54
分类:知识依赖:代码执行 / 读写文件 / MCP 服务 / 内部调用大模型应用场景:笔记整理 / 研究 / 工作流 / 模板 ...

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add create-opc-wiki
Metadata
name
create-opc-wiki
description
Scaffold a personal LLM wiki (Karpathy pattern) — multi-agent, MCP-ready, with SEO/GEO publish target. Compiles knowledge into a persistent wiki instead of re-deriving from raw docs on every query. One paste from any agent (OpenClaw, Claude Code, Codex, Cursor, Hermes) installs it.

create-opc-wiki

Scaffold a personal LLM wiki on the Karpathy pattern in 30 seconds. Multi-agent native, MCP server built-in, SEO/GEO-optimized publish target.

What this skill does

Run the scaffolder against any folder and you get a complete personal-knowledge-base vault:

  • agent-rules/main.md — single source of truth, synced to 9 agent file formats (CLAUDE.md, AGENTS.md, .cursor/rules/main.mdc, .cursorrules, .github/copilot-instructions.md, .trae/rules.md, .openclaw/rules.md, .hermes/agent.md)
  • Three reusable skills: /wiki-ingest, /wiki-query, /wiki-lint
  • Five source recipes: arXiv paper, X thread, YouTube transcript, RSS article, podcast transcript
  • Privacy-tagged frontmatter: public | private | secret
  • An MCP server with three tools (wiki_query, wiki_list, wiki_read) and a hard privacy gate (privacy: secret pages never leave the box)
  • Optional Astro static site target with sitemap.xml, llms.txt, robots.txt, RSS feed, OpenGraph + JSON-LD per page

How to invoke

The skill wraps the published npm package create-opc-wiki@latest. From any agent that can run a shell command:

npx -y create-opc-wiki@latest <path> --yes --agents=openclaw,claude,codex,cursor

Common one-liners:

Agent Command
OpenClaw npx -y create-opc-wiki@latest ~/wiki --yes --agents=openclaw,claude
Claude Code npx -y create-opc-wiki@latest ~/wiki --yes --agents=claude
Codex CLI npx -y create-opc-wiki@latest ~/wiki --yes --agents=codex
Cursor npx -y create-opc-wiki@latest ~/wiki --yes --agents=cursor
All of them npx -y create-opc-wiki@latest ~/wiki --yes --agents=openclaw,claude,codex,cursor,hermes,vscode,trae

Add --no-mcp, --no-site, --no-recipes, or --no-git to skip those layers. --json emits machine-readable result on stdout.

How to use the generated vault

  1. Open the folder in Obsidian (it's a valid Obsidian vault) — and/or
  2. Open the folder in your AI agent (it reads CLAUDE.md / AGENTS.md / .openclaw/rules.md / etc.)
  3. From inside the agent, use the three skills:
    • /wiki-ingest <url-or-file> — drop a new source, agent files it into raw/ and synthesizes wiki pages
    • /wiki-query <question> — natural-language query across compiled wiki
    • /wiki-lint — health-check (contradictions, stale speculative claims, orphan pages)

The MCP server in mcp/server.mjs exposes the wiki to any MCP client (Claude Desktop, Cursor, Codex). Run npm install && npm start from the mcp/ directory.

Why a wiki and not just RAG

Most LLM-on-files setups re-derive answers from raw docs at every query. There's no accumulation. Quoting Karpathy's gist:

The LLM incrementally builds and maintains a persistent wiki — a structured, interlinked collection of markdown files that sits between you and the raw sources. The wiki keeps getting richer with every source you add and every question you ask.

This skill operationalizes exactly that, with concrete choices for ontology, agent rules, MCP, and publishing.

Privacy & security

  • privacy: secret pages never returned by the MCP server (enforced at mcp/server.mjs:38)
  • privacy: public is the only level that publishes (enforced at site/build.mjs:53)
  • Default frontmatter privacy is private — nothing publishes by accident
  • The scaffolder runs once, locally, and exits — no telemetry, no network calls during scaffolding except the optional npm install you trigger yourself

Links

License

MIT. Inspired by Andrej Karpathy's "LLM Wiki" gist; implementation choices are this project's. Full attribution in INSPIRATION.md.