embedding-strategies
Pass
Audited by Gen Agent Trust Hub on Sep 14, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTION
Full Analysis
- [SAFE]: The skill uses standard Python libraries for natural language processing and interacts with official embedding provider APIs without employing dangerous execution patterns.
- [SAFE]: Secret management is handled securely via environment variables (
os.environ.get) rather than hardcoding credentials. - [INDIRECT_PROMPT_INJECTION]: The skill accepts external text data for embedding and chunking, creating a theoretical ingestion surface. However, the risk is negligible as the skill performs only text processing and lacks dangerous sinks like arbitrary shell execution or local file writes. Mandatory evaluation:
- Ingestion points:
get_embeddings,process_documents, andchunk_by_tokensinSKILL.mdaccept external strings. - Boundary markers: The templates do not include explicit instructions to the agent to ignore instructions embedded in data.
- Capability inventory: Operations are limited to text manipulation, mathematical computations via
numpy, and network API calls to trusted embedding providers. - Sanitization: Basic regex-based sanitization is implemented in the
_default_preprocessfunction.
Audit Metadata