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 Paparusi · Agent Tool · ★ 197
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is legal-ai-agent safe to install? View the security audit →
⚖️ AI Legal Agent 🇻🇳 Tiếng Việt | 🇺🇸 English Created by Lê Minh Hiếu — Trader turned Builder 🇻🇳 AI-powered legal assistant for Vietnamese businesses An AI platform for legal research, contract review, and legal document drafting — all in a VSCode-style interface. --
| Stars | 197 |
| Forks | 92 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 62.5339724668925/100 |
| Open Issues | 1 |
| Last Updated | 2026-03-21 |
| Created | 2026-03-15 |
| Platforms | claude-code, python |
| Est. Tokens | ~727k |
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legal-ai-agent is an open-source agent tool by Paparusi with 197 GitHub stars.
legal-ai-agent is primarily written in Python. It covers topics such as ai-agent, anthropic, claude.
You can find installation instructions and usage details in the legal-ai-agent GitHub repository at github.com/Paparusi/legal-ai-agent. The project has 197 stars and 92 forks, indicating an active community.
legal-ai-agent is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to legal-ai-agent on Agent Skills Hub include context-compressor, OmoiOS, sandstorm. 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: