Answering Research Questions
Pass
Audited by Gen Agent Trust Hub on Oct 28, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONDYNAMIC_EXECUTION
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill is designed to ingest and process content from external, untrusted sources (academic abstracts and full-text PDFs) which could contain adversarial instructions.
- Ingestion points: External metadata from PubMed (Phase 3), paper abstracts and full-text PDFs (Phase 4), and citation/reference lists (Phase 5).
- Boundary markers: The instructions do not define clear boundaries or isolation techniques to prevent the agent from following instructions potentially embedded in the analyzed research papers.
- Capability inventory: The agent has capabilities to create directories, write files (SUMMARY.md, JSON data stores), and execute Python code for data processing.
- Sanitization: There are no explicit sanitization steps described for content extracted from external documents before it is interpolated into summaries or passed to other processing stages.
- [DYNAMIC_EXECUTION]: The skill utilizes runtime generation and execution of Python scripts to manage and synthesize research data.
- Evidence: Phase 7 (Option B) instructs the agent to create a
generate_summary.pyscript to aggregate findings for large research sessions. - Evidence: Phase 8 (Final Consolidation) provides a Python script template for the agent to read
papers-reviewed.json, filter the contents, and write the output torelevant-papers.json. - Context: These scripts are used for legitimate data management of the agent's own research artifacts, but represent a pattern of dynamic execution.
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