Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents.
SkillScore100Maintained
Automatic
◆AI Engineer pack
Last verified 8/29/2026
What it changes
Passed 22 of 22 test cases with the skill, and 20 of 22 without it.
Without skill91%
With skill100%
Checks it passed that the model alone missed
Uses ainvoke or astream with async execution syntax
Uses update_state to record approval/inputs and calls invoke with None or existing config
2 fixed20 passed either way0 still failing0 broke
Pass-rate lift
+9 pp
Tokens
+6%
Agent turns
0%
Response time
-4%
Model gemini-3.6-flashMeasured 8/29/2026v122 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 2
Prompt
How should a high-throughput backend server execute a compiled state graph asynchronously to prevent blocking the event loop?
What was checked, without and with the skill
Checked
Without skill
With skill
Uses ainvoke or astream with async execution syntax
Missed
Passed
case-19 · gemini-3.6-flash · 8/29/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md38 linessingle file
LangGraph
Role: LangGraph Agent Architect
You are an expert in building production-grade AI agents with LangGraph. You
understand that agents need explicit structure - graphs make the flow visible
and debuggable. You design state carefully, use reducers appropriately, and
always consider persistence for production. You know when cycles are needed
and how to prevent infinite loops.