hugging-face-model-trainer
Train language models using TRL (Transformer Reinforcement Learning) on fully managed Hugging Face infrastructure. No local GPU setup required—models train on cloud GPUs and results are automatically saved to the Hugging Face Hub.
52
58%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Low
Low-risk findings worth noting
Fix and improve this skill with Tessl
tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/hugging-face-model-trainer/SKILL.mdThe canonical home for this skill is hugging-face-model-trainer in administrakt0r/AI-Agents-Safe-Coding-Skills
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The workflow reads documentation via `hf_doc_fetch` and `hf_doc_search` and downloads external code/datasets via `hf_jobs` from URLs and repositories, which is considered low-risk user-selected or community content.
- Commit
57c135b
- Audited
- Security analysis
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.