AI 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 AI 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 edges
```
get-agent-graph
```
-- inspect a graph's structure and edges
```
list-agent-graphs
```
-- browse existing graphs in the project

Optional MCP tools:

```
update-agent-graph
```
-- modify edges, root config, or description
```
delete-agent-graph
```
-- permanently remove a graph
```
get-ai-config
```
-- inspect individual AI Configs that serve as nodes
```
create-ai-config
```
-- create new AI Configs to use as graph nodes

Core Concepts

What Are Agent Graphs?

An agent graph is a directed graph where:

Nodes are AI 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 edge
```
sourceConfig
```
-- the AI Config key that routes FROM
```
targetConfig
```
-- the AI Config key that routes TO
```
handoff
```
(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 (AI 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-graphs
```
to avoid duplicates
Check existing AI Configs with
```
get-ai-config
```
to see what nodes already exist

Step 2: Ensure Nodes Exist

Each node in the graph must be an existing AI Config. If configs don't exist yet:

Use
```
create-ai-config
```
to 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 AI Configs
```
key
```
-- unique identifier for the graph
```
name
```
-- human-readable display name
```
description
```
(optional) -- explain the graph's purpose
```
rootConfigKey
```
-- the entry-point AI Config key
```
edges
```
-- array of connections between configs

json

{
  "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-graph
```
to 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 AI 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

aiconfig-agent-graphs

NPX Install

Tags

SKILL.md Content