by oxbshw · MCP Server · ★ 484
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
/plugin marketplace add oxbshw/watch-skill
/plugin install watch-skill@watch-skillTaken 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 | 484 |
| Forks | 68 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65/100 |
| Open Issues | 6 |
| Last Updated | 2026-10-14 |
| Created | 2026-07-05 |
| Platforms | browser, cli, mcp, python |
| Est. Tokens | ~17k |
Watch Skill Give every AI agent eyes for video—and a way to inspect its own work. Watch Skill is a local-first video intelligence layer for agents. It turns videos, live streams, meetings, and screen recordings into searchable, timestamped evidence. Agents can understand what happened, retain it across sessions, and cite the exact moment behind an answer.
These tools work well together with watch-skill for enhanced workflows:
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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: