multi-agent-systems
Pass
Audited by Gen Agent Trust Hub on Feb 26, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: No malicious patterns, obfuscation, or persistence mechanisms were detected. The skill consists of educational markdown files and a standard Python framework for managing LLM agents via the Anthropic API.
- [SAFE]: The Python script in
scripts/agent_framework.pyfollows best practices for API interaction and does not include hardcoded credentials or unauthorized network operations. - [SAFE]: The documentation promotes security through the 'Verification Subagent Pattern,' which uses independent agents to validate outcomes, thereby reducing the risk of autonomous agent errors.
- [PROMPT_INJECTION]: The skill provides a framework for processing natural language, which creates a surface for indirect prompt injection if untrusted data is handled.
- Ingestion points: User messages enter the system via the
run,run_with_context, andrun_asyncmethods inscripts/agent_framework.py. - Boundary markers: The framework does not provide default delimiters; developers must define them in their prompts.
- Capability inventory: While the framework is passive, documentation examples suggest integration with tools such as
execute_code,run_tests, andwrite_file. - Sanitization: No automated sanitization of user input or tool outputs is performed by the base classes.
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