by momotech · MCP Server · ★ 116
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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 | 116 |
| Forks | 14 |
| Language | Dockerfile |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 63/100 |
| Open Issues | 4 |
| Last Updated | 2026-03-31 |
| Created | 2026-03-16 |
| Platforms | k8s, mcp |
| Est. Tokens | ~1008k |
LinkWork (灵工) 🤖 Make AI Work Like Your Team Open-source enterprise AI workforce platform — Roles · Skills · Tools · Security · Scheduling, all in one place English | 中文 Introduction LinkWork is an open-source enterprise AI Agent platform. It does not just make AI "answer", it makes AI "deliver".
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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: