LangGraph development for stateful multi-agent applications, cyclic workflows, conditional routing, human-in-the-loop patterns, and persistent state management.
SkillScore100Maintained
Automatic
◆AI Engineer pack
Last verified 8/18/2026
What it changes
Passed 22 of 22 test cases with the skill, and 19 of 22 without it.
Without skill86%
With skill100%
Checks it passed that the model alone missed
Sets LANGSMITH_API_KEY environment variable.
States langchain-core>=0.3.0 as the compatibility requirement.
Notes that returning keys not declared in the state schema raises an InvalidUpdateError.
3 fixed19 passed either way0 still failing0 broke
Pass-rate lift
+14 pp
Tokens
+187%
Agent turns
0%
Response time
-32%
Model gemini-3.6-flashMeasured 8/18/2026v122 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 3
Prompt
We are installing langgraph version 0.2.x in our Python backend repository. What minimum version of langchain-core is required for compatibility?
What was checked, without and with the skill
Checked
Without skill
With skill
States langchain-core>=0.3.0 as the compatibility requirement.
Missed
Passed
case-13 · gemini-3.6-flash · 8/18/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md366 linessingle file
LangGraph Development Skill
Quick Reference
LangGraph is LangChain's framework for building stateful, multi-actor applications with LLMs. It enables cyclic graphs, conditional branching, persistent state management, and human-in-the-loop workflows.
Key capabilities: StateGraph for workflow orchestration, checkpointers for persistence, prebuilt ReAct agents, streaming at multiple granularities, and LangGraph Platform for managed deployment.