LangGraph Execution Control
Pass
Audited by Gen Agent Trust Hub on Mar 2, 2026
Risk Level: SAFE
Full Analysis
- Architectural Surface for Untrusted Input: The skill demonstrates how to build agents that ingest data such as message history or task descriptions. This is an inherent property of agentic workflows. Ingestion points: Input variables like messages in AgentState and tasks in OrchestratorState (found in SKILL.md) receive external data. Boundary markers: The technical snippets focus on graph orchestration logic and do not implement specific text-based delimiters for model prompts. Capability inventory: The patterns include calling language models and executing tools, which is the primary function of the orchestration logic. Sanitization: The examples provide a structural foundation; developers can implement additional input validation logic within the node functions as needed.
- Infinite Loop Prevention: The skill includes best-practice recommendations for limiting agent iterations, which helps manage resource usage and prevents unintended recursive behavior.
- Secure State Persistence: The examples utilize standard memory-based savers for state checkpointing, which is a local mechanism for maintaining execution context without external dependencies.
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