by hiroki-abe-58 · AI Tool · ★ 6
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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.
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 | 6 |
| Forks | 1 |
| Language | Python |
| Category | AI Tool |
| License | Apache-2.0 |
| Quality Score | 58/100 |
| Last Updated | 2026-10-08 |
| Created | 2026-09-20 |
| Platforms | python |
| Est. Tokens | ~16k |
Japanese System One decision model (Jev-style): typed answers and probabilities in one forward pass, no text generation. Includes bench_ja/bench_en and a Laya position-bias repro.
Looking for a sokudan alternative? If you're comparing sokudan with other ai tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Ask your house a question, get a number back. Home Assistant integration for TypeSafe Jev: typed answers as se
Blazing fast, self-hosted structured decisions for open models with a TypeSafe AI compatible API, written in R
Intent compiler for AI agents — converges vague requests into typed IntentSpec contracts (probe, ask, or halt
AI-powered text compression library for RAG systems and API calls. Reduce token usage by up to 50-60% while pr
Roy: A lightweight, model-agnostic framework for crafting advanced multi-agent systems using large language mo
A unified client for AI providers with built-in agent support.
Explore other popular ai 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: