by QWED-AI · Agent Tool · ★ 64
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
docker pull qwedai/qwed-verification
git clone https://github.com/QWED-AI/qwed-verification.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 | 64 |
| Forks | 14 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 64/100 |
| Open Issues | 49 |
| Last Updated | 2026-11-03 |
| Created | 2025-12-13 |
| Platforms | python |
| Est. Tokens | ~23k |
QWED Verification Reference implementation of the QWED Verification protocol and Verification Context v1.0 QWED applies deterministic verification to AI outputs before production execution. Every verification returns a DiagnosticResult: VERIFIED — proof established, evidence attached UNVERIFIABLE — proof could not be established BLOCKED — policy or rule rejected the action Admission: ADMIT |...
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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: