by ddalcu · Agent Tool · ★ 2.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
brew install mlx-serve # CLI server onlyTaken from the project's README on GitHub. Check the security audit before running it.
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 | 2,391 |
| Forks | 252 |
| Language | Zig |
| Category | Agent Tool |
| Quality Score | 71/100 |
| Open Issues | 87 |
| Last Updated | 2026-11-07 |
| Created | 2026-02-17 |
| Platforms | claude-code |
| Est. Tokens | ~23k |
mlx-serve — run any LLM on your Mac OpenAI- and Anthropic-compatible local inference for Apple Silicon — MLX and GGUF — faster than LM Studio on the same file. No Python. No cloud. No Electron. ddalcu.github.io/mlx-serve · Download MLX Core.app · Changelog ★ If mlx-serve saves you from spinning up another Electron app, star the repo — it genuinely helps people fin
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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: