Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/domleca/llm-wikiTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. 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.
| Stars | 176 |
| Forks | 13 |
| Language | TypeScript |
| Category | AI Tool |
| License | MIT |
| Quality Score | 58/100 |
| Open Issues | 5 |
| Last Updated | 2026-06-15 |
| Created | 2026-04-08 |
| Platforms | node |
| Est. Tokens | ~16k |
LM Wiki This project was inspired by Andrej Karpathy's post on LLM knowledge bases — using LLMs to compile personal notes into a structured, queryable wiki. LM Wiki is an attempt to package that workflow into something anyone can use, privately, right inside Obsidian. Your notes already contain a wealth of knowledge — scattered across files, half-connected, hard to query.
Looking for a llm-wiki alternative? If you're comparing llm-wiki with other ai tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
A tool to make socks connections through HTTP agents
Open-source AI research assistant for biomedicine — chat to run RNA-seq, drug discovery, clinical analysis, an
SciToolAgent: A Knowledge Graph-Driven Scientific Agent for Multi-Tool Integration
Skip to content github / docs Code Issues 80 Pull requests 35 Discussions Actions Projects 2 Security Insights
Skill to talk to Claude about your projects over the phone
.NET MAUI skills for GitHub Copilot and Claude Code
Explore other popular ai tool tools:
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: