by bkuan001 · MCP Server · ★ 83
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
uvx --from halo-record halo demo --serve
pip install halo-recordTaken from the project's README on GitHub. Check the security audit before running it.
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. Full audit →
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 | 83 |
| Forks | 10 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 66/100 |
| Last Updated | 2026-10-03 |
| Created | 2026-06-11 |
| Platforms | mcp, python |
| Est. Tokens | ~15k |
halo-record Tamper-evident runtime records for AI agents: the audit trail the vendor runs but cannot edit. Every action your agent takes (tool calls, model calls, data access, approvals) becomes one record in an append-only, hash-chained log. Any party can verify the log was never altered, without trusting whoever produced 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: