openwiki: CLI that writes and maintains agent documentation for your codebase

by langchain-ai · Agent Tool · ★ 17.8k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Featured in: Knowledge Base & RAG

How to install openwiki

npm install -g openwiki

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 62/100

Flagged: opens a tunnel service. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars17,798
Forks1,315
LanguageTypeScript
CategoryAgent Tool
LicenseMIT
Quality Score62/100
Open Issues180
Last Updated2026-11-07
Created2026-06-22
Platformscli, node
Est. Tokens~20k

About openwiki

The self-maintaining wiki. Built for agents, explored by humans. OpenWiki is a CLI that writes and maintains a wiki for your codebase or your personal knowledge. An agent reads your sources, synthesizes a linked Markdown wiki you own, and keeps it current on every change. It is built for agents to read as memory, and it ships an interact

Compatible Skills

These tools work well together with openwiki for enhanced workflows:

  • oh-my-mermaid — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (57%)
  • gemini-mcp-tool — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (56%)
  • sourcey — semantic(0.28)+complementary+same_lang+shared_platform (50%)
  • codealmanac — semantic(0.27)+complementary+same_lang+shared_platform (50%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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