multi-agent-architect
Design and optimize production-grade multi-agent systems with LangGraph, LangChain, and DeepAgents for complex AI workflows.
Profile →npx skills add sickn33/agentic-awesome-skills --skill multi-agent-architect --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Multi-Agent Architect & Updater Skill ## Overview This skill turns Claude into a Senior AI Multi-Agent Architect specialized in LangGraph, LangChain, and DeepAgents. It provides structured workflows for creating and updating production-grade multi-agent systems — including supervisor agents, planners, researchers, coders, and memory-backed autonomous pipelines. Use it whenever you need to design, build, debug, or scale any multi-agent AI system. If this skill adapts material from an external GitHub repository, declare both: - `source_repo: owner/repo` - `source_type: official` or `source_type: community` ## When to Use This Skill - Use when you need to create a new agent or multi-agent workflow from scratch - Use when working with LangGraph state graphs, nodes, edges, or conditional routing - Use when the user asks about agent communication, memory systems, or tool-calling pipelines - Use when debugging or optimizing an existing LangChain/LangGraph agent system - Use when architecting supervisor, planner, research, coding, or validation agent roles - Use when integrating DeepAgents with hierarchical planning and delegation ## How It Works ### Step 1: Understand the Goal Before wr
- Overview
- When to Use This Skill
- How It Works
- Step 1: Understand the Goal
- Step 2: Define the State Schema
- Step 3: Define Agent Nodes
- Step 4: Build the LangGraph
- Step 5: Add Memory
- Step 6: Run the Graph
- Step 7: Expose via FastAPI (optional)
- Updating an Existing Agent
- Standard Folder Structure
- Examples
- Example 1: Research + Coding Multi-Agent Workflow
What does the multi-agent-architect skill do?
Design and optimize production-grade multi-agent systems with LangGraph, LangChain, and DeepAgents for complex AI workflows.
How do I install it?
Run `npx skills add sickn33/agentic-awesome-skills --skill multi-agent-architect --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From sickn33/agentic-awesome-skills, a repository with 44,414 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.