deep-research
Pass
Audited by Gen Agent Trust Hub on May 13, 2026
Risk Level: SAFE
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill is designed to ingest and analyze untrusted content from the internet via the
web_fetchtool. This creates a surface for indirect prompt injection where malicious content in a fetched article could attempt to influence the agent's logic. However, the skill includes a multi-layered synthesis process, structured data formats for inter-agent communication, and rigorous verification gates that effectively mitigate this risk. \n - Ingestion points: External content retrieved by subagents using
web_fetch(referenced inreference/subagent-prompt.md). \n - Boundary markers: Absent for raw fetched data, though output findings are highly structured. \n
- Capability inventory: Filesystem operations for research note management and CLI script execution for data processing. \n
- Sanitization: No explicit content sanitization is described, but the multi-agent synthesis and verification pipeline acts as a logical filter. \n- [COMMAND_EXECUTION]: The skill utilizes local utility scripts (
scripts/source_evaluator.pyandscripts/verify_citations.py) and coordinates subagents via CLI commands (e.g.,claude -p). These operations are consistent with the skill's primary purpose of automated research and do not involve suspicious network activity or unauthorized file access.
Audit Metadata