by sarrazola · Agent Tool · ★ 79
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/sarrazola/openlivery.gitTaken from the project's README on GitHub.
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.
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 | 79 |
| Forks | 57 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 67/100 |
| Last Updated | 2026-11-04 |
| Created | 2026-08-14 |
| Platforms | cli, docker, python |
| Est. Tokens | ~15k |
OpenLivery The open-source, white-label platform for agencies to build, run and manage AI agents for their clients. Documentation · Documentación · Quick start · Self-hosting · Discussions One OpenLivery installation serves one agency. The agency creates AI agents for its clients, gives each client a branded portal, and talks to end users over WhatsApp or an embeddable web chat widget.
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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: