No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by lawve-ai · Agent Tool · ★ 678
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-legal-skills safe to install? View the security audit →
What are Agent Skills? Agent Skills are portable instructions that teach AI agents how to perform specific tasks your way. For legal professionals, this means encoding your expertise into reusable AI workflows. Draft GDPR-compliant privacy policies. Review NDAs using your firm's methodology. Create due diligence checklists that match your standards. Get Started [!IMPORTANT] Write once, use anywhere — Skills are an open standard for AI agents, with adoption growing across the industry. Use them with your favorite AI tool.
| Stars | 678 |
| Forks | 86 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 54.8546981242714/100 |
| Open Issues | 6 |
| Last Updated | 2026-09-04 |
| Created | 2025-12-18 |
| Platforms | python |
| Est. Tokens | ~25k |
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awesome-legal-skills is A curated list of awesome Agent Skills for automating legal work. It is categorized as a Agent Tool with 678 GitHub stars.
awesome-legal-skills is primarily written in Python. It covers topics such as agent-skills, automation, law.
You can find installation instructions and usage details in the awesome-legal-skills GitHub repository at github.com/lawve-ai/awesome-legal-skills. The project has 678 stars and 86 forks, indicating an active community.
The top alternatives to awesome-legal-skills on Agent Skills Hub include claude-code-plugins-plus-skills, commands, OwnPilot. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: