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 simonw · Agent Tool · ★ 1.9k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is tools safe to install? View the security audit →
tools.simonwillison.net Miscellaneous HTML+JavaScript tools built mostly with the help of LLMs. See also /python/ for tools written using Python. This collection is an experiment in prompt-driven development with very low stakes. The colophon lists commit messages and transcripts for every tool. The code lives in simonw/tools and many tools used the Claude custom instructions described here.
| Stars | 1,903 |
| Forks | 192 |
| Language | HTML |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 44.1120768268302/100 |
| Open Issues | 56 |
| Last Updated | 2026-10-01 |
| Created | 2024-03-29 |
| Est. Tokens | ~15k |
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tools is Assorted useful tools, almost entirely generated using LLMs. It is categorized as a Agent Tool with 1.9k GitHub stars.
tools is primarily written in HTML.
You can find installation instructions and usage details in the tools GitHub repository at github.com/simonw/tools. The project has 1.9k stars and 192 forks, indicating an active community.
tools is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to tools on Agent Skills Hub include notebooklm-skill, agent-skills, excalidraw-diagram-skill. 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: