ReddRadar
Agent skill
langgraph-routing
Conditional edge routing and state-based transitions for LangGraph workflows
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/ai-agents-conversational/skills/langgraph-routing
SKILL.md
LangGraph Routing Skill
Capabilities
- Design conditional edge routing in LangGraph
- Implement state-based transition logic
- Create dynamic routing functions
- Handle multi-path workflow branches
- Implement router nodes for complex decisions
- Design fallback and error routing paths
Target Processes
- langgraph-workflow-design
- plan-and-execute-agent
Implementation Details
Routing Patterns
- Conditional Edges: add_conditional_edges with routing functions
- Router Nodes: Dedicated nodes for routing decisions
- State-Based Routing: Routing based on state values
- LLM-Based Routing: Using LLM to determine next node
Configuration Options
- Routing function definitions
- Path mapping configurations
- Default/fallback routes
- Cycle detection settings
- Max iteration limits
Best Practices
- Clear routing logic documentation
- Handle all possible states
- Implement fallback paths
- Avoid infinite cycles
- Use descriptive edge names
Dependencies
- langgraph
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