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oabdelmaksoud
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langgraph-collab

Coordinate multi-agent graph execution with LangGraph routing and transcript logging.

4|Updated Feb 26, 2026
Search Tags:#workflow#routing#multi-agent#orchestration#langgraph#topology
One-click install
npx skills add https://github.com/oabdelmaksoud/Openclaw-skills-Compilations --skill langgraph-collab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langgraph-collab
Source: https://github.com/oabdelmaksoud/Openclaw-skills-Compilations/tree/main/langgraph-collab
Command: npx skills add https://github.com/oabdelmaksoud/Openclaw-skills-Compilations --skill langgraph-collab

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill orchestrates multi-agent graph workflows using LangGraph to route tasks across specialized agents with different topologies (linear, supervisor, parallel, and conditional).

Core Features & Use Cases

  • Supports linear pipelines, supervisor-driven delegation, parallel synthesis, and conditional branching.
  • Manages task context, agent responses, metadata routing, and result assembly with transcript logging for auditing.
  • Easy setup with OpenClaw provider configuration and reusable agent configurations.

Quick Start

Launch the runner with a chosen topology, select the agents, provide a task, and specify an output directory to capture status and transcript.

Frequently Asked Questions about langgraph-collab

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I route tasks between multiple agents in a LangGraph workflow?▼

Multi-agent graph execution routes tasks between agents using LangGraph topologies like linear pipelines, supervisor-driven delegation, parallel synthesis, or conditional branching to coordinate specialized processing.

What is the best way to orchestrate conditional branching across specialized agents?▼

Conditional branching across specialized agents is orchestrated by applying metadata-driven routing within a multi-agent graph, dynamically directing task context to specific agents based on defined conditions.

Can I use supervisor-driven delegation to manage task context in multi-agent graphs?▼

Supervisor-driven delegation manages task context by routing assignments to specialized agents within the graph, assembling their responses and logging a complete transcript for auditing.

Does LangGraph multi-agent orchestration support limits for max steps and timeouts?▼

Multi-agent orchestration implements guards for max steps and timeouts to control graph execution, ensuring workflows terminate safely and output structured results.

How do I get an auditing transcript from a parallel synthesis workflow?▼

Parallel synthesis workflows output a structured result and a complete execution transcript to a specified output directory, capturing agent responses and routing metadata for auditing.

When do I need conditional routing instead of a linear pipeline for multi-agent execution?▼

Conditional routing is needed when task execution paths must adapt dynamically based on metadata, whereas linear pipelines apply to fixed, sequential processing across specialized agents.

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