agent-graphs
launchdarkly/ai-tooling
Create and manage directed graphs of agent configs with handoff logic for multi-agent workflows.
What is agent-graphs?
Agent graphs let you design multi-agent systems as directed graphs where nodes are configs and edges define routing with handoff data. Use this when building workflows where multiple specialized agents need to coordinate and pass context to each other.
- Design and create directed graphs with configs as nodes and routing edges
- Define handoff data to control context passing between agents
- Set a root config as the entry point for user input
- List and inspect existing graphs in your project
- Update graph topology and edges without recreating
- Delete graphs when no longer needed
How to install agent-graphs
npx skills add https://github.com/launchdarkly/ai-tooling --skill agent-graphs- LaunchDarkly MCP server configured in your environment
- Existing AI configs to use as graph nodes (or ability to create them)
How to use agent-graphs
- 1.Design your graph topology on paper: identify agents, routing paths, and handoff data
- 2.Verify all config nodes exist using get-ai-config; create missing configs with create-ai-config
- 3.Call create-agent-graph with projectKey, graph key, name, rootConfigKey, and edges array
- 4.Use get-agent-graph to verify the graph structure and edge connections
- 5.Update edges with update-agent-graph if topology changes are needed
- 6.Test end-to-end routing to confirm agents hand off correctly
Use cases
- Build customer support triage systems that route queries to specialist agents
- Create multi-step processing pipelines (extract → transform → validate → store)
- Implement escalation chains (L1 support → L2 support → human handoff)
- Design intent-based routers that dispatch to different specialized agents
- Orchestrate complex workflows where agents hand off work based on context
- AI engineers building multi-agent systems
- Product teams designing agent-based workflows
- DevOps/platform engineers managing agent infrastructure
- Teams using LaunchDarkly for agent configuration
agent-graphs FAQ
Nodes are configs (agents with models, prompts, and tools). Edges are connections between configs that define routing and carry handoff data from source to target.
Yes, circular routing is allowed, but you must ensure agents have termination conditions to avoid infinite loops.
Create it first with create-ai-config before referencing it in the graph. All nodes must exist before the graph can be created.
Define handoff data on edges — this data is passed from the source config to the target config during the transition.
Yes, use update-agent-graph to modify edges, root config, or description without deleting and recreating.
Full instructions (SKILL.md)
Source of truth, from launchdarkly/ai-tooling.
name: agent-graphs description: "Create and manage agent graphs — directed graphs of configs connected by edges with handoff logic. Use when building multi-agent workflows where configs route to each other." license: Apache-2.0 compatibility: Requires the remotely hosted LaunchDarkly MCP server metadata: author: launchdarkly version: "0.1.0"
Config Agent Graphs
You're using a skill that will guide you through creating and managing agent graphs in LaunchDarkly. Your job is to design the graph topology, create it with the right edges and handoffs, and verify the routing between config nodes.
Prerequisites
This skill requires the remotely hosted LaunchDarkly MCP server to be configured in your environment.
Required MCP tools:
create-agent-graph-- create a new graph with nodes and edgesget-agent-graph-- inspect a graph's structure and edgeslist-agent-graphs-- browse existing graphs in the project
Optional MCP tools:
update-agent-graph-- modify edges, root config, or descriptiondelete-agent-graph-- permanently remove a graphget-ai-config-- inspect individual configs that serve as nodescreate-ai-config-- create new configs to use as graph nodes
Core Concepts
What Are Agent Graphs?
An agent graph is a directed graph where:
- Nodes are configs (each config is an agent with its own model, prompt, and tools)
- Edges define routing between configs (source -> target)
- Handoff data on edges controls how context is passed between agents
- Root config is the entry point — the first agent that receives user input
When to Use Agent Graphs
| Scenario | Example |
|---|---|
| Multi-step workflows | Triage agent -> Specialist agent -> Summary agent |
| Routing by intent | Router agent decides which specialist handles the request |
| Escalation chains | L1 support -> L2 support -> Human handoff |
| Pipeline processing | Extract -> Transform -> Validate -> Store |
Graph Structure
[Root Config] --edge--> [Config A] --edge--> [Config C]
\--edge--> [Config B]
Each edge has:
key-- unique identifier for the edgesourceConfig-- the config key that routes FROMtargetConfig-- the config key that routes TOhandoff(optional) -- data/instructions passed during the transition
Core Principles
- Design Before Building: Map out nodes and edges on paper/whiteboard first
- One Agent, One Job: Each node should have a clear, focused responsibility
- Root Config Is the Router: The entry point should understand how to dispatch
- Handoff Data Matters: Define what context flows between agents
- Verify the Full Path: Test that routing works end-to-end
Workflow
Step 1: Design the Graph
Before creating anything:
- Identify the agents (configs) needed — each is a graph node
- Map the routing: which agent hands off to which?
- Define handoff data: what context does each edge carry?
- Identify the root config: which agent receives initial input?
- Check existing graphs with
list-agent-graphsto avoid duplicates - Check existing configs with
get-ai-configto see what nodes already exist
Step 2: Ensure Nodes Exist
Each node in the graph must be an existing config. If configs don't exist yet:
- Use
create-ai-configto create each agent config - Set up variations with appropriate models and prompts for each agent's role
- Verify each config exists with
get-ai-config
Step 3: Create the Graph
Use create-agent-graph with:
projectKey-- the project containing the configskey-- unique identifier for the graphname-- human-readable display namedescription(optional) -- explain the graph's purposerootConfigKey-- the entry-point config keyedges-- array of connections between configs
{
"projectKey": "my-project",
"key": "support-triage-graph",
"name": "Customer Support Triage",
"description": "Routes customer queries to the appropriate specialist agent",
"rootConfigKey": "triage-agent",
"edges": [
{
"key": "triage-to-billing",
"sourceConfig": "triage-agent",
"targetConfig": "billing-specialist",
"handoff": {"category": "billing", "priority": "normal"}
},
{
"key": "triage-to-technical",
"sourceConfig": "triage-agent",
"targetConfig": "technical-specialist",
"handoff": {"category": "technical", "priority": "normal"}
}
]
}
Step 4: Verify
- Use
get-agent-graphto confirm the graph was created with the correct structure - Verify edges connect the right source and target configs
- Check that the root config key matches the intended entry point
- Confirm handoff data is present on edges that need it
Report results:
- Graph created with N nodes and M edges
- Root config set correctly
- All edges verified
Edge Cases
| Situation | Action |
|---|---|
| Config doesn't exist yet | Create it first with create-ai-config before referencing in a graph |
| Circular routing | Allowed but warn user — ensure there's a termination condition in the agent logic |
| Single-node graph | Valid but unusual — consider if a graph is actually needed |
| Updating edges | Use update-agent-graph — provide the complete new edge list |
What NOT to Do
- Don't create a graph before the config nodes exist
- Don't forget handoff data when agents need context from predecessors
- Don't create overly complex graphs — start simple and add nodes as needed
- Don't delete a graph without understanding if it's actively used in agent workflows
Other Resources
To learn more, read Agent graphs.
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