Implements dynamic workflow routing, retry loops, and semantic branching for LangGraph-based AI agents.
This skill provides production-ready implementation patterns for LangGraph routing, enabling Claude to architect complex, non-linear workflows. It covers essential patterns such as state-based conditional edges, quality gates for output validation, and sophisticated retry loops to handle transient failures. Additionally, it integrates modern best practices like using the Command object for simultaneous state updates and routing, alongside semantic routing techniques using embeddings to direct queries based on intent.
Características Principales
0169 GitHub stars
02Command-based routing for simultaneous state updates
03Quality gate patterns for output validation and review
04Automated retry loop patterns with max-attempt logic
05State-based conditional edge implementation
06Semantic routing via text embeddings and similarity scores
Casos de Uso
01Implementing self-correction loops for LLM-generated code or content
02Building multi-agent systems that route tasks based on specialized intent
03Creating complex decision trees for customer support or technical troubleshooting agents
