by 10xChengTu · LLM Plugin · ★ 302
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
brew install --cask input0Taken from the project's README on GitHub.
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 | 302 |
| Forks | 13 |
| Language | Rust |
| Category | LLM Plugin |
| Quality Score | 66/100 |
| Open Issues | 3 |
| Last Updated | 2026-05-28 |
| Created | 2026-04-06 |
| Platforms | rust |
| Est. Tokens | ~1089k |
English | 简体中文 Input 0 🏗️ This project's AI agent harness is built with Harness Engineering. A macOS voice input tool — hold a hotkey to record, release to get polished text auto-pasted into any input field. Local AI transcription → LLM text optimization → auto-paste. Private, fast, effortless. Features Press & Speak — Hold (customizable) to record, release to transcribe + optimize + paste.
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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: