embedding-strategies
Pass
Audited by Gen Agent Trust Hub on Sep 25, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTION
Full Analysis
- [SAFE]: The skill contains standard Python code templates for text processing, embedding generation, and retrieval evaluation using well-known libraries such as
openai,sentence-transformers,numpy,scipy,nltk, andtiktoken. All code follows industry-standard patterns for building RAG (Retrieval-Augmented Generation) applications. - [INDIRECT_PROMPT_INJECTION]: The skill facilitates the ingestion and processing of external data through embedding and chunking pipelines, which is a common attack surface for indirect prompt injection.
- Ingestion points: External text data is ingested via parameters in
get_embeddings,chunk_by_tokens, and theDomainEmbeddingPipelineclass. - Boundary markers: The templates do not implement specific boundary markers or "ignore" instructions for the ingested content, which is typical for embedding-only tasks.
- Capability inventory: The skill includes text processing, chunking, local model inference via sentence-transformers, and network calls to the OpenAI API.
- Sanitization: The skill includes a
_default_preprocessfunction that performs basic sanitization by normalizing whitespace and removing non-standard special characters.
Audit Metadata