by TarsLab · Agent Tool · ★ 329
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 | 329 |
| Forks | 30 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 67/100 |
| Open Issues | 2 |
| Last Updated | 2026-08-28 |
| Created | 2024-06-11 |
| Platforms | claude-code, gemini, node |
| Est. Tokens | ~16k |
English | 中文 Tars Tars is an Obsidian plugin that supports text generation based on tag suggestions, using services like Claude, OpenAI, Gemini, 🔥DeepSeek, 🔥SiliconFlow, 🔥OpenRouter, 🔥MiniMax, 🔥LongCat, Ollama, Kimi, Doubao, Qwen, Zhipu, QianFan & more. The name Tars comes from the robot Tars in the movie "Interstellar". The plugin supports both desktop and mobile devices.
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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: