by xcjy8bao · MCP Server · ★ 54
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 | 54 |
| Forks | 3 |
| Language | TypeScript |
| Category | MCP Server |
| License | AGPL-3.0 |
| Quality Score | 59/100 |
| Last Updated | 2026-09-03 |
| Created | 2026-08-27 |
| Platforms | cli, mcp, node |
| Est. Tokens | ~13k |
sift-light English · 简体中文 sift-light — Evidence-first search for AI agents. A general-purpose local search plugin that helps agents find files, documents, notes, logs and other text material. Think of a patient librarian: describe what you need, and it helps locate the shelf, open the relevant page and follow the next lead. A small search brings the passages straight to you.
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I'm sad: such a great project, yet no one has starred it.
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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: