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 pithings · Agent Tool · ★ 85
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is advocaat safe to install? View the security audit →
❓Advocaat A small, type-safe client for asking AI questions about your data, powered by TypeSafe Jev. Get probabilities, choices, and scores in one request. Agent skill teaches coding agents how to design questions and build with . Quick start Install the package: Set your TypeSafe API key: Using Vercel instead? See Vercel AI Gateway. Ask several questions about the same data in one request: Question types Answers use the same keys as your questions. Mix any of these forms in one call:
| Stars | 85 |
| Forks | 1 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 64.1349370497915/100 |
| Last Updated | 2026-09-18 |
| Created | 2026-09-16 |
| Platforms | cli, node |
| Est. Tokens | ~17k |
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advocaat is A small, type-safe client for asking AI questions about your data, powered by TypeSafe Jev.. It is categorized as a Agent Tool with 85 GitHub stars.
advocaat is primarily written in TypeScript.
You can find installation instructions and usage details in the advocaat GitHub repository at github.com/pithings/advocaat. The project has 85 stars and 1 forks, indicating an active community.
advocaat is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to advocaat on Agent Skills Hub include tutor-skills, repren. 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: