llm-application-dev-langchain-agent

Pass

Audited by Gen Agent Trust Hub on Aug 19, 2026

Risk Level: SAFEPROMPT_INJECTION
Full Analysis
  • [PROMPT_INJECTION]: The skill defines a surface for indirect prompt injection by interpolating untrusted input into the execution context.
  • Ingestion points: The $ARGUMENTS placeholder in the Context section of SKILL.md is an entry point for untrusted data.
  • Boundary markers: Absent. The instructions do not specify delimiters or instructions to the agent to treat the interpolated content as potentially untrusted data.
  • Capability inventory: The skill facilitates high-capability actions including code generation, tool usage, file access (e.g., reading resources/implementation-playbook.md), and network operations via LangSmith and FastAPI.
  • Sanitization: Absent. There is no evidence of filtering or validation logic for the provided arguments.
  • [DATA_EXFILTRATION]: The skill encourages the integration of LangSmith for observability. This involves transmitting application traces to a third-party service. As LangSmith is a well-known service for LLM monitoring, this is documented as standard operational behavior for production-grade agent development.
Audit Metadata
Risk Level
SAFE
Analyzed
Aug 19, 2026, 01:27 AM
Security Audit — agent-trust-hub — llm-application-dev-langchain-agent