LangGraph Routing Skill
SkillDev toolsConditional edge routing and state-based transitions for LangGraph workflows
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the LangGraph Routing Skill skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/ai-agents-conversational/skills/langgraph-routing/SKILL.md and read by ahel’s review.
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
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
langgraph-routing- Source
- github.com/a5c-ai/babysitter