mirror of
https://github.com/magnus919/agent-skills.git
synced 2026-09-15 13:36:35 +03:00
37 lines
1.6 KiB
Markdown
37 lines
1.6 KiB
Markdown
# LangGraph — Stateful Multi-Agent Orchestration
|
|
|
|
Build multi-agent AI systems with LangGraph — the low-level orchestration framework for stateful, graph-based agent workflows. The foundation for agents in the LangChain ecosystem.
|
|
|
|
## Why Install This Skill
|
|
|
|
When your agent loads this skill, it becomes a **LangGraph architect** who can:
|
|
|
|
- **Design graph topologies** — nodes, edges, state schemas, reducers
|
|
- **Implement multi-agent patterns** — supervisor, swarm, and hierarchical orchestration
|
|
- **Add persistence** — checkpointers and stores for long-running agents
|
|
- **Handle production complexity** — branching, cycles, parallel execution, human-in-the-loop
|
|
- **Evaluate agent performance** — systematic eval methodology
|
|
- **Debug production failures** — common failure modes and how to trace them
|
|
|
|
## What You Get
|
|
|
|
| Directory | Purpose |
|
|
|-----------|---------|
|
|
| `SKILL.md` | Quick start, design principles, pattern selection guide |
|
|
| `scripts/` | Supervisor scaffold, swarm scaffold, eval generator |
|
|
| `templates/` | 3 runnable template implementations |
|
|
| `references/` | 8 reference files: architecture, each pattern in depth, evals, production failures, troubleshooting |
|
|
|
|
## Triggers
|
|
|
|
Load this when designing agent architectures that need cycles, conditional branching, parallel execution, or human-in-the-loop patterns.
|
|
|
|
## Requirements
|
|
|
|
Python 3.8+ with `langgraph`, `langchain`, and `langchain-openai` packages.
|
|
|
|
|
|
## Quick Start
|
|
|
|
Start with the setup and first workflow in SKILL.md, then use the linked resources for the specific task you need to complete.
|