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Agent Skill · 研究检索

llm-obsidian-wiki(LLM Obsidian wiki 搜索)

llm-obsidian-wiki 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

llm-obsidian-wiki 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 59,464。

总安装 388周安装 16GitHub Stars 13下载 127核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:llm-obsidian-wiki(LLM Obsidian wiki 搜索)
来源仓库:https://github.com/ignromanov/llm-obsidian-wiki
仓库路径:skills/llm-obsidian-wiki
安装命令:
npx skills add https://github.com/ignromanov/llm-obsidian-wiki --skill llm-obsidian-wiki
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ignromanov/llm-obsidian-wiki --skill llm-obsidian-wiki

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

llm-obsidian-wiki 用于查找、检索和筛选相关信息。适合根据关键词、任务场景或来源线索快速定位候选结果。可在 Codex、Claude、Cursor、Gemini CLI 中用于信息调研场景。安装前建议确认权限范围、维护状态及是否触发联网或文件操作。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/llm-obsidian-wiki

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/ignromanov/llm-obsidian-wiki --skill llm-obsid…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

llm-obsidian-wiki 怎么安装?

在终端执行 npx skills add https://github.com/ignromanov/llm-obsidian-wiki --skill llm-obsidian-wiki。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

llm-obsidian-wiki 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

llm-obsidian-wiki 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

llm-obsidian-wiki 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

llm-obsidian-wiki 用的人多吗?

公开数据是累计安装 388 次,近一周安装 16 次,下载 127 次,GitHub 13 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

llm-obsidian-wiki 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
llm-obsidian-wiki

LLM Obsidian wiki 搜索 · 本页

38813操作浏览器未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

LLM Obsidian Wiki

Karpathy's LLM Wiki pattern — as a Claude Code plugin. Turn Claude into a researcher that remembers, backed by an Obsidian vault that grows smarter every session.

In his original gist, Andrej Karpathy sketched a simple but powerful idea: an LLM-maintained personal wiki where knowledge is compiled once, cross-linked, and kept current — so the LLM never re-derives what it's already learned. This plugin is a faithful implementation of that pattern, weaponized for Claude Code and built on top of Obsidian.

Every conversation with an LLM normally starts from zero. You paste the same context. You re-explain the same decisions. Your research dies in closed browser tabs. llm-obsidian-wiki fixes this by giving Claude a persistent, file-based memory that survives across sessions — structured as a plain-text Obsidian vault you can read, edit, git-version, and grep yourself. It's a second brain Claude actively maintains — a zettelkasten where the LLM does the filing, cross-linking, and drift detection for you.

Live Example

You:     Research auth options for my Next.js app and write it up.

Claude:  [wiki-capture-agent]  → pulls 5 blog posts, 2 GitHub READMEs,
                                 1 YouTube talk into raw/external/
         [wiki-ingest-agent]   → synthesizes typed wiki pages:
                                 wiki/concepts/nextjs-auth-patterns.md
                                 wiki/comparisons/nextauth-vs-clerk-vs-supabase.md
                                 wiki/entity/better-auth.md
                                 wiki/open-questions/session-cost-past-10k-mau.md
         [regenerate]          → updates index.md + domain hub pages

         Done. 4 pages created, cross-linked with [[wikilinks]] and citations
         to raw sources. Confidence: medium (2+ corroborating sources).

─── A week later, new side project ───

You:     Which auth library should I use for this new Next.js app?

Claude:  [wiki-query] → reads wiki/comparisons/nextauth-vs-clerk-vs-supabase.md
                      → reads wiki/decisions/clerk-for-side-projects.md

         Clerk, if you want zero config and $0/month under 10k MAU — it ships
         social login, magic links, and organizations out of the box. Use
         NextAuth if you need full control of the DB schema. Avoid Supabase Auth
         unless you're already on Supabase for data. See [[clerk-for-side-projects]]
         for the full rationale. The open question [[session-cost-past-10k-mau]]
         still applies to this project too.

Notice what happened: Claude didn't re-research. It read its own structured notes in the Obsidian vault and answered with citations. That's the Karpathy compounding loop — knowledge compiled once and kept current, not re-derived on every query.

What You Get

Skills (8)Autonomous Agents (5)
/wiki:init — scaffold a new Obsidian vaultwiki-capture-agent — batch source capture
/wiki:capture — collect URL/PDF/GitHub/YT/git-logwiki-ingest-agent — autonomous page synthesis
/wiki:ingest — compile raw into typed wiki pageswiki-query-agent — deep research + file-back
/wiki:query — ask with citations + synthesiswiki-lint-agent — health + source drift detection
/wiki:browse — load domain contextwiki-migrate-agent — schema version upgrades
/wiki:lint — orphans, staleness, contradictions
/wiki:status — metrics + unprocessed queue
/wiki:migrate — apply schema migrations

Plus 17 portable bash utilities, a shared scripts/lib/ helper library, 10 page-type templates (concept / entity / decision / strategy / comparison / synthesis / open-question / architecture / org / source-summary), and a versioned schema with migrations.

How It Works

Three layers with strict data flow and clear ownership inside the Obsidian vault:

raw/                 →    wiki/                  →    query
(immutable sources)       (structured knowledge)       (cited synthesis)

• URLs + HTML             • concepts                   • "What did we decide?"
• PDFs                    • decisions (ADR-style)      • "What contradicts X?"
• GitHub PRs + issues     • comparisons                • Cross-page research
• YouTube transcripts     • synthesis pages            • Citation-backed answers
• Git logs                • open questions
• Clipboards              • organizations

Raw is append-only source material with SHA-256 provenance tracking. Wiki holds LLM-maintained pages with YAML frontmatter, tags, [[wikilinks]], confidence scores, and typed relations (contradicts, supports, evolved_into, depends_on). Query reads the wiki — never raw sources directly — and answers with [[wikilink]] citations you can click through in Obsidian.

Contradictions surface as > [!warning] callouts with explicit relations.type: contradicts entries. Drift between raw and wiki is detected automatically by wiki:lint via hash comparison. Schema migrations travel with the plugin version, so upgrading the plugin upgrades your vault.

Why This Exists

Other tools give Claude retrieval. The Karpathy LLM Wiki pattern gives Claude memory with structure:

  • vs raw RAG — you get typed pages (concept / decision / comparison / open-question) instead of opaque chunks. LLM-navigable, human-auditable.
  • vs Notion AI — files live in your Obsidian vault as markdown. Edit in Obsidian, git-version them, grep them, take them offline.
  • vs plain Obsidian — the LLM maintains the structure for you: creates wikilinks, reuses tags, tracks confidence, detects contradictions, migrates schemas.
  • vs other Obsidian plugins — ships both interactive skills AND autonomous agents for batch research and long-running synthesis.

This is personal knowledge management (PKM) for the LLM era — Karpathy's llm-wiki concept meeting the zettelkasten method, with Claude as the patient filer and Obsidian as the durable substrate.

Install

# Via Claude Code marketplace
/plugin marketplace add ignromanov/llm-obsidian-wiki
/plugin install llm-obsidian-wiki@ignromanov

# Or local install
claude --plugin-dir /path/to/llm-obsidian-wiki

Then:

/wiki:init                              # scaffold a new Obsidian vault
/wiki:capture https://example.com/post  # capture a source
/wiki:ingest                            # compile raw into wiki pages
/wiki:query "what did we decide?"       # ask with citations

What's New in v0.3.0

  • Security hardening — capture-url.sh rejects non-https schemes and private/loopback IPs; shell injection fixed in capture and create scripts; prompt-injection defense added to the ingest agent
  • Vault contract — wiki.config.md now requires both vault_name (for the Obsidian CLI) and vault_path (for scripts)
  • New /wiki:migrate skill — upgrades existing vaults between plugin versions
  • Shared bash library — scripts/lib/ with portable helpers for YAML reading, SHA-256 hashing, and dependency checks
  • Linux portability — migration scripts now work on both macOS and Linux

Ideal For

Engineering decision tracking (ADRs), competitive landscape research, long-running projects that span months, founders tracking market intelligence, researchers building annotated bibliographies, teams who want every Slack discussion to settle into a durable note, and anyone tired of re-explaining the same context to Claude every Monday morning.

Philosophy

  • Privacy > features — everything lives on your disk, nothing leaves your machine
  • Files > databases — plain markdown, editable in any tool, greppable forever
  • Compound > retrieve — compile knowledge once, keep it current, never re-derive
  • Typed > chunked — concept / decision / comparison beats opaque embeddings

Learn More


*Keywords: karpathy llm wiki, llm-wiki, obsidian plugin, claude code plugin, knowledge base, compounding knowledge, second brain, zettelkasten, pkm, personal knowledge management, long-term memory for llm, llm memory, research assistant, obsidian vault, structured notes, markdown knowledge base, rag alternative, typed pages, note-taking with ai.*

平台分布

Codex

37.37%
按下载量换算47

Claude

31.3%
按下载量换算40

Cursor

16.41%
按下载量换算21

Gemini CLI

9.71%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

可疑

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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