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 cuzfrog · Claude Skill · ★ 53
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is lissom-skills safe to install? View the security audit →
Lissom Skills English · 简体中文 · 日本語 Why? What's the difference from GSD, SuperPower? Zero Dependency — just plain files. Thin Skill Dispatchers — relentless context protection. Idempotency — hussle-free resume with minimal state. Hammered Specs — no surprise dev experience. /gsd-autonomous /lissom-auto (Context after a 10m task on a small loc
| Stars | 53 |
| Forks | 6 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 73.0671143538895/100 |
| Last Updated | 2026-08-24 |
| Created | 2026-04-26 |
| Platforms | claude-code, cli, gemini, python |
| Est. Tokens | ~14k |
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lissom-skills is Light weight Claude Skills and Agents for every day tasks.. It is categorized as a Claude Skill with 53 GitHub stars.
lissom-skills is primarily written in Python. It covers topics such as agent, ai, automation.
You can find installation instructions and usage details in the lissom-skills GitHub repository at github.com/cuzfrog/lissom-skills. The project has 53 stars and 6 forks, indicating an active community.
lissom-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to lissom-skills on Agent Skills Hub include squeez, antigravity-workflows, Dream-Creator. 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: