by jallum · Agent Tool · ★ 78
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 | 78 |
| Forks | 9 |
| Language | Go |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 73/100 |
| Open Issues | 9 |
| Last Updated | 2026-09-14 |
| Created | 2026-02-19 |
| Platforms | go |
| Est. Tokens | ~16k |
Beadwork Git-native work management for AI coding agents. Why AI coding agents lose context constantly — compaction, session boundaries, crashes. Plans they build in-context die silently. The agent picks up where it left off with no memory of what it decided or why. Beadwork gives agents durable state in git. Plans, progress, and decisions persist as files on a git branch.
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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: