hugging-face-jobs
This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.
61
77%
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Low
Low-risk findings worth noting
Fix and improve this skill with Tessl
tessl review fix ./backend/cli/skills/other/hugging-face-jobs/SKILL.mdW011: 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 allows ingesting outsider-authored datasets from the Hugging Face Hub (e.g. seed datasets or input prompt datasets via `load_dataset`) into scripts that execute on Hugging Face Jobs or local environments, presenting a low indirect prompt injection risk as the agent actively fetches specific datasets.
- Repository
synthetic-sciences/openscience
- Revision
6a85742
- Audited
- Security analysis
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