by Curated-Awesome-Lists · Agent Tool · ★ 525
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 | 525 |
| Forks | 79 |
| Category | Agent Tool |
| Quality Score | 54/100 |
| Open Issues | 9 |
| Last Updated | 2026-09-04 |
| Created | 2023-10-30 |
| Est. Tokens | ~22k |
Awesome LLMs Fine-Tuning Welcome to the curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their numerous variants! In this era of artificial intelligence, the ability to adapt pre-trained models to specific tasks and domains has become an indispensable skill for researchers, data scientists, and machine learning practitioners.
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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: