by theaniketgiri · LLM Plugin · ★ 362
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npx create-llm my-awesome-llm
npx create-llm my-llmTaken 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 | 362 |
| Forks | 48 |
| Language | TypeScript |
| Category | LLM Plugin |
| License | MIT |
| Quality Score | 77/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-13 |
| Created | 2025-08-08 |
| Platforms | cli, node |
| Est. Tokens | ~17k |
create-llm CLI tool for scaffolding LLM Creation and training Create production-ready LLM training projects in seconds. Similar to create-next-app but for training custom language models. npm Package • Documentation • Report Bug • Request Feature Why create-llm? Train
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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: