by LegalQuants · Agent Tool · ★ 65
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git clone https://github.com/LegalQuants/lq-skills.gitTaken 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 | 65 |
| Forks | 25 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 60/100 |
| Open Issues | 11 |
| Last Updated | 2026-06-28 |
| Created | 2026-05-07 |
| Platforms | python |
| Est. Tokens | ~16k |
LQ Skills Legal Quants — agent skills for legal work. A curated collection of skills built by the Legal Quants community (100 lawyer-builders across 17+ jurisdictions). These skills are harness-agnostic: install once, use across Claude Code, Codex CLI, Gemini CLI, OpenCode, Cursor, and OpenClaw. Why Most legal AI tools are black boxes.
These tools work well together with lq-skills for enhanced workflows:
Explore other popular agent tool tools:
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: