obsidian-wiki Agent工作流 是 AI Skill Hub 本期精选AI工具之一。已获得 1.3k 颗 GitHub Star,综合评分 8.2 分,整体质量较高。我们强烈推荐将其纳入你的 AI 工具库,帮助提升工作效率。
obsidian-wiki Agent工作流 是一款基于 Python 开发的开源工具,专注于 AI智能体、Obsidian、知识库 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
obsidian-wiki Agent工作流 是一款基于 Python 开发的开源工具,专注于 AI智能体、Obsidian、知识库 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
# 方式一:pip 安装(推荐)
pip install obsidian-wiki
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install obsidian-wiki
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/Ar9av/obsidian-wiki
cd obsidian-wiki
pip install -e .
# 验证安装
python -c "import obsidian_wiki; print('安装成功')"
# 命令行使用
obsidian-wiki --help
# 基本用法
obsidian-wiki input_file -o output_file
# Python 代码中调用
import obsidian_wiki
# 示例
result = obsidian_wiki.process("input")
print(result)
# obsidian-wiki 配置文件示例(config.yml) app: name: "obsidian-wiki" debug: false log_level: "INFO" # 运行时指定配置文件 obsidian-wiki --config config.yml # 或通过环境变量配置 export OBSIDIAN_WIKI_API_KEY="your-key" export OBSIDIAN_WIKI_OUTPUT_DIR="./output"
<p align="center"> <a href="https://deepwiki.com/Ar9av/obsidian-wiki"><img src="https://deepwiki.com/badge.svg" alt="Ask DeepWiki" /></a> <a href="https://github.com/ar9av/obsidian-wiki/pulls"><img src="https://img.shields.io/badge/PRs-welcome-brightgreen.svg" alt="PRs Welcome" /></a> <a href="https://x.com/_ar9av"><img src="https://img.shields.io/badge/@__ar9av-black?logo=x&logoColor=white" alt="X" /></a> </p>
<p align="center"> <img width="768" height="512" alt="obisidan-wiki" src="https://github.com/user-attachments/assets/b44cf63b-3197-4fb1-8e18-dbc9a39f27a7" /> </p>
A digital brain you grow with your AI agent. It remembers what you figure out, connects it to what you already know, and answers when you ask.
The pattern comes from Andrej Karpathy's LLM Wiki gist: compile knowledge once into interconnected markdown files and keep them current, instead of asking an LLM the same questions over and over (or running RAG every time). Obsidian is how you see the brain. Your AI agent is how you grow it.
We built a framework around that idea. Every skill is a markdown file that any AI coding agent (Claude Code, Cursor, Windsurf, Pi, and others) reads and runs. Point it at an Obsidian vault, tell it what to remember, and the vault becomes a second brain you own.
/wiki-query what do I know about rate limiting? ```
/wiki-update reads your project, figures out what's worth keeping, and writes it into the brain. Architecture decisions, patterns you discovered, key concepts, trade-offs you evaluated. It skips code and file listings and saves the stuff you'd forget in 3 months. Run it again from the same project and it checks what changed since last sync (via git log) and processes only the delta.
/wiki-query goes the other direction. You're mid-task and you want to know what the brain already holds on a topic. Maybe you solved the same problem 2 months ago in a different project and the answer is already there. The agent searches the vault, reads the relevant pages, and gives you a synthesized answer with citations.
Both skills follow the same Karpathy pattern as everything else. If a concept page already exists in the vault, it merges into it. Everything gets cross-linked with [[wikilinks]], tracked in .manifest.json, and logged.
pip install obsidian-wiki
obsidian-wiki setup --vault /path/to/your/digital/brain
obsidian-wiki setup writes the config to ~/.obsidian-wiki/config and installs every wiki skill into all your AI agents (Claude Code, Cursor, Codex, Gemini, Hermes, Pi, and more). Skills are symlinked to the installed package, so pip install -U obsidian-wiki upgrades them everywhere — just re-run obsidian-wiki setup to pick up new skills. Then open a project in your agent and say "set up my wiki".
obsidian-wiki list # list the bundled skills
obsidian-wiki info # show install paths, version, and config
obsidian-wiki doctor # health-check config, vault shape, and installed skills
obsidian-wiki query "rate limiting" # query the configured vault from the terminal
obsidian-wiki lint # lint the configured vault for broken links / metadata gaps
obsidian-wiki setup --project . # also drop project-local skills + AGENTS.md into the current repo
obsidian-wiki setup --copy # copy skill files instead of symlinking
OBSIDIAN_VAULT_PATH is just any directory where you want your digital brain to live, a new empty folder or an existing Obsidian vault. Omit --vault to be prompted (or set it later in ~/.obsidian-wiki/config).
npx skills add Ar9av/obsidian-wiki
This only installs the markdown skills into the current agent. It does not write ~/.obsidian-wiki/config, install ~/.obsidian-wiki/sync.sh, or wire the global multi-agent bootstrap that obsidian-wiki setup / setup.sh performs.
Use this path only if you intentionally want a partial, agent-local install and are prepared to manage config yourself. For a complete setup, use Install via pip or Install via git clone instead.
Browse the full skill list at skills.sh/ar9av/obsidian-wiki.
git clone https://github.com/Ar9av/obsidian-wiki.git
cd obsidian-wiki
bash setup.sh
setup.sh asks for your vault (path to your digital brain) path, writes the config to ~/.obsidian-wiki/config, symlinks skills into all your agents, and installs wiki-update globally so you can use it from any project.
Open the project in your agent and say "set up my wiki". That's it.
<details> <summary>Claude Code</summary>
Skills are auto-discovered from .claude/skills/. Either run setup.sh or copy .skills/* to .claude/skills/. The CLAUDE.md file at the repo root is automatically loaded as project context.
cd /path/to/obsidian-wiki && claude "set up my wiki" </details>
<details> <summary>Cursor</summary>
Skills are auto-discovered from .cursor/skills/. The .cursor/rules/obsidian-wiki.mdc file provides always-on context. Either run setup.sh or copy .skills/* to .cursor/skills/. Then type /wiki-setup in the chat. </details>
<details> <summary>Windsurf</summary>
Cascade reads rules from .windsurf/rules/ and skills from .windsurf/skills/. Either run setup.sh or copy .skills/* to .windsurf/skills/. Then tell Cascade: "set up my wiki". </details>
<details> <summary>Codex</summary>
Reads AGENTS.md for project context. setup.sh installs skills globally to ~/.codex/skills/. Either run setup.sh or manually symlink .skills/* to ~/.codex/skills/.
cd /path/to/obsidian-wiki && codex "set up my wiki" </details>
<details> <summary>Gemini CLI</summary>
Reads GEMINI.md and discovers global skills from ~/.gemini/skills/. Either run setup.sh or manually symlink .skills/* to ~/.gemini/skills/.
cd /path/to/obsidian-wiki && gemini "set up my wiki" </details>
<details> <summary>Google Antigravity</summary>
Always-on via .agent/rules/ + .agent/workflows/. setup.sh ships both files and symlinks skills into .agents/skills/. The legacy ~/.gemini/antigravity/skills/ path is also wired. </details>
<details> <summary>Kiro IDE/CLI</summary>
Always-on via .kiro/steering/*.md with inclusion: always. setup.sh symlinks .skills/* into both .kiro/skills/ and ~/.kiro/skills/. Invoke with /wiki-ingest, /wiki-query, etc. </details>
<details> <summary>OpenCode / Aider / Factory Droid / Trae</summary>
All read AGENTS.md at the repo root. setup.sh symlinks skills into ~/.agents/skills/ (shared discovery path). Trae also gets ~/.trae/skills/ and ~/.trae-cn/skills/. </details>
<details> <summary>Hermes</summary>
Reads .hermes.md first, then falls back to AGENTS.md. Skills discovered from ~/.hermes/skills/. Run setup.sh or manually symlink .skills/* there.
```bash cd /path/to/obsidian-wiki && hermes "set up my wiki"
**Hourly auto-sync via cron (can be enabled during setup):**
0 ~/.obsidian-wiki/sync.sh >> ~/.obsidian-wiki/sync.log 2>&1 ```
Keep the repo private if your vault contains personal notes. Nothing is sent to any third-party service — your vault lives on your machines and your GitHub account only.
---
By default, wiki-ingest and wiki-query use Grep/Glob for search — fully functional, no extra setup. If your vault grows large or you want concept-level matches across your sources, you can plug in QMD, either through MCP or by letting the agent call the local qmd CLI.
Setup:
1. Install QMD. If you want MCP mode, also add it to your MCP config (see the QMD repo for instructions). 2. Index your wiki and/or source documents:
qmd index --name wiki /path/to/your/vault
qmd index --name papers /path/to/your/sources
3. Set the collection names and transport in your .env: QMD_WIKI_COLLECTION=wiki # used by wiki-query
QMD_PAPERS_COLLECTION=papers # used by wiki-ingest (source discovery)
QMD_TRANSPORT=mcp # mcp | cli
QMD_CLI_SEARCH_MODE=quality # quality | balanced | fast
QMD_TRANSPORT=mcp preserves the original behavior and uses an agent-configured QMD MCP server. QMD_TRANSPORT=cli runs the local qmd command directly. CLI mode defaults to quality, which uses qmd query with reranking for the best relevance. If that is too slow on CPU, set QMD_CLI_SEARCH_MODE=balanced to use qmd query --no-rerank, or fast for a lighter semantic pass.
What changes with QMD enabled:
wiki-query runs a semantic pass (lex+vec) against your wiki collection before falling back to Grep. Finds conceptually related pages even when the exact terms don't match.wiki-ingest queries your papers collection before writing a new page — surfaces related sources, spots contradictions, and decides whether to create a new page or merge into an existing one.Both skills degrade gracefully: if QMD_WIKI_COLLECTION / QMD_PAPERS_COLLECTION are not set, they skip the QMD step silently and use Grep instead.
The Python package also ships a few local commands for inspection and maintenance:
obsidian-wiki doctor --json
obsidian-wiki query "what do I know about MCP security?"
obsidian-wiki lint --strict
obsidian-wiki graph-query /path/to/vault "transformer architecture"
obsidian-wiki graph-analyse /path/to/vault --pretty
Use doctor to catch broken setup, stale installs, or malformed vault state. Use query and lint when you want fast local answers without going through an agent prompt. The lower-level graph-query, graph-analyse, batch-plan, cache-*, and ast-extract commands are still available for automation and debugging.
This repo includes a zero-build Chrome extension at extensions/brain-capture/ for saving web pages and selected text into your vault's _raw/ folder.
To install it:
chrome://extensionsextensions/brain-captureTo find the configured _raw folder from this repo:
awk -F= '/^OBSIDIAN_VAULT_PATH=/{print $2 "/_raw"; exit}' "$(git rev-parse --show-toplevel)/.env"
After capturing pages into _raw/, ask your agent to process them:
/wiki-ingest promote my raw pages
wiki-ingest will read each _raw/ capture, distill it into the right wiki pages, update the manifest/index/log, and remove the promoted raw files so they are not processed twice.
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创新的AI智能体应用框架,结合Obsidian生态实现知识库自动化。代码质量好、社区活跃度高,但依赖外部LLM服务存在成本考量。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
经综合评估,obsidian-wiki Agent工作流 在AI工具赛道中表现稳健,质量优秀。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。
| 原始名称 | obsidian-wiki |
| 原始描述 | 开源AI工作流:Framework for AI agents to build and maintain an Obsidian wiki using Karpathy's 。⭐1.3k · Python |
| Topics | AI智能体Obsidian知识库工作流自动化 |
| GitHub | https://github.com/Ar9av/obsidian-wiki |
| License | MIT |
| 语言 | Python |
收录时间:2026-05-18 · 更新时间:2026-05-19 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。