No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by doum1004 · Agent Tool · ★ 101
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is llmwiki-cli safe to install? View the security audit →
llmwiki-cli A CLI tool for LLM agents to build and maintain personal knowledge bases. Inspired by Andrej Karpathy's LLM Wiki. Live Demo — interactive d3-force graph built from the example wiki in . Overview The CLI is the hands -- it reads, writes, searches, and manages wiki files. The LLM is the brain -- it decides what to create, update, and connect. LLM Agent (Claude Code / Codex) | | shells out to: | $ wiki init my-wiki --name "Notes" --domain "machine learning" | $ wiki write wiki/concepts/
| Stars | 101 |
| Forks | 14 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 76.0681010558366/100 |
| Last Updated | 2026-05-01 |
| Created | 2026-04-10 |
| Platforms | cli, node |
| Est. Tokens | ~30k |
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llmwiki-cli is CLI tool for LLM agents to build and maintain personal knowledge bases. It is categorized as a Agent Tool with 101 GitHub stars.
llmwiki-cli is primarily written in TypeScript. It covers topics such as ai-tools, cli, knowledge-base.
You can find installation instructions and usage details in the llmwiki-cli GitHub repository at github.com/doum1004/llmwiki-cli. The project has 101 stars and 14 forks, indicating an active community.
llmwiki-cli is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to llmwiki-cli on Agent Skills Hub include llm-wiki, mcp-server-atlassian-confluence, LLM-Wiki. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: