advanced-evaluation
Pass
Audited by Gen Agent Trust Hub on Feb 17, 2026
Risk Level: SAFE
Full Analysis
- SAFE (SAFE): The content is purely educational and reference-based documentation regarding LLM-as-a-judge evaluation frameworks.
- EXTERNAL_DOWNLOADS (SAFE): The code snippets reference standard, trustworthy Python libraries including scipy, numpy, and scikit-learn for statistical calculations. No unauthorized external downloads or remote script execution (curl|bash) were found.
- COMMAND_EXECUTION (SAFE): No instances of arbitrary command execution, shell spawning, or dangerous system-level calls were detected.
- DATA_EXFILTRATION (SAFE): No hardcoded credentials, sensitive file path access, or network calls to untrusted domains were identified.
- PROMPT_INJECTION (SAFE): While the documents discuss prompts used for evaluation rubrics, there are no attempts to override or bypass the agent's instructions or safety filters.
- INDIRECT_PROMPT_INJECTION (SAFE): The skill describes systems that ingest model outputs for evaluation, but as a documentation-only skill, it does not execute these patterns on untrusted data during analysis and provides mitigation strategies like anonymization and consistency checks.
Audit Metadata