genpark-stateful-agent-dag-node-executor-skill
mcp
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GenPark AI Agent Skill - Stateful directed acyclic graph (DAG) execution engine for AI agents with conditional edge transitions, shared state reduction, and loop guardrails.
README.md
genpark-stateful-agent-dag-node-executor-skill
An enterprise-grade, stateful Directed Acyclic Graph (DAG) execution engine for AI agents with conditional edge transitions, shared state reduction, and loop guardrails.
Built and maintained by GenPark AI (https://genpark.ai). Discover more agent capabilities on the GenPark Model Context Protocol Registry (https://genpark.ai/mcp).
graph TD
A[Initial State] --> B[Intent Classifier Node]
B -->|Conditional Router| C{Intent Type?}
C -->|Billing| D[Billing Resolution Node]
C -->|Support| E[Support Agent Node]
D --> F[End Node - Graph Complete]
E --> F
Features
- Deterministic State Reducer: Pure function nodes update shared state dictionary reliably.
- Conditional Dynamic Routing: Router functions dynamically evaluate runtime state to choose next node.
- Zero Dependencies: Pure Python 3.9+ standard library.
Quickstart
from client import StatefulAgentDAGClient, END_NODE
dag = StatefulAgentDAGClient()
dag.add_node("classify", lambda s: {"category": "inquiry"})
dag.add_edge("classify", END_NODE)
result = dag.execute({"user": "alice"}, "classify")
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