by genai-craft · AI Tool · ★ 13
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. 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 | 13 |
| Forks | 0 |
| Language | Python |
| Category | AI Tool |
| Quality Score | 61/100 |
| Last Updated | 2026-10-18 |
| Created | 2026-09-17 |
| Platforms | python |
| Est. Tokens | ~16k |
openvons (open-Jev): 有限選択肢に確率で答える判断層 — テキスト / 画像 / 日本語音声コマンド
Looking for a openvons alternative? If you're comparing openvons 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.
ZeusHammer - AI Super Agent with Local Brain, Voice Interaction & Three-Tier Memory
MCP server that turns any video — YouTube, Instagram, TikTok, Loom, X, Vimeo, direct URLs, local files — into
Kesha listens and talks back: local speech to text and text to speech for agents and scripts, fastest on Apple
Ask your house a question, get a number back. Home Assistant integration for TypeSafe Jev: typed answers as se
A Telegram bot that proves you don't need a body to have a personality. Works with any OpenAI-compatible LLM;
Official Supadata MCP Server - Adds powerful video & web scraping to Cursor, Claude and any other LLM clients.
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: