book-sft-pipeline
Pass
Audited by Gen Agent Trust Hub on Sep 14, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONEXTERNAL_DOWNLOADS
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill is designed to ingest and process external literary works (ePub files) to generate fine-tuning datasets.
- Ingestion points: Text extraction logic in
SKILL.mdusing BeautifulSoup and paragraph-level segmentation inscripts/pipeline_example.py. - Boundary markers: The pipeline produces structured JSONL files with explicit role-based message formatting (system, user, assistant).
- Capability inventory: Includes file system access for reading ePubs/JSONL files and network operations for model training via the Tinker API.
- Sanitization: The extraction process includes paragraph-level filtering and removal of metadata to prevent noise in the training data.
- [EXTERNAL_DOWNLOADS]: The skill references external datasets and research materials.
- Evidence: Downloads a sample style-transfer dataset from Hugging Face (
huggingface.co/datasets/MuratcanKoylan/gertrude-stein-style-sft) and references a research paper on ArXiv (arxiv.org/pdf/2510.13939). Both sources are well-known and consistent with the skill's stated purpose.
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