rag-implementation
Pass
Audited by Gen Agent Trust Hub on Sep 14, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: No security issues were detected in the analyzed content. The skill follows development best practices by utilizing environment variables for API keys and referencing official documentation for well-known services.
- [INDIRECT_PROMPT_INJECTION]: The skill provides architectural templates for RAG systems which, by design, process external data (retrieved documents) and user inputs within a prompt. This represents a standard attack surface for indirect prompt injection common to all RAG implementations.
- Ingestion points: User questions and retrieved context are interpolated into prompt templates in
SKILL.md. - Boundary markers: The implementation uses clear structural labels (e.g., "Context:", "Question:") to provide delimiters within the LLM prompt.
- Capability inventory: The code examples demonstrate network operations (calling Anthropic and Voyage AI APIs) and local file system access (Chroma database persistence).
- Sanitization: The examples use standard string formatting; implementers should follow best practices for sanitizing data when moving beyond these templates to production environments.
Audit Metadata