autogen-collab

Automate multi-agent debates to reach consensus with configurable rounds and logging.

4|Updated Feb 26, 2026

Search Tags:#logging #multi-agent #orchestration #consensus #debate #autogen

Ready to run

npx skills add https://github.com/oabdelmaksoud/Openclaw-skills-Compilations --skill autogen-collab

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: autogen-collab
Source: https://github.com/oabdelmaksoud/Openclaw-skills-Compilations/tree/main/autogen-collab
Command: npx skills add https://github.com/oabdelmaksoud/Openclaw-skills-Compilations --skill autogen-collab

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates AutoGen-style debates to reach consensus among specialist agents, reducing manual coordination and accelerating high-stakes decision-making.

Core Features & Use Cases

Orchestrates multi-agent debates with configurable agent sets, rounds, and timeouts to surface consensus decisions.
Detects consensus using explicit signals and outputs a final result with provenance and audit logs.
Logs conversation transcripts and run metadata for auditing, QA, and knowledge capture.
Use cases include architectural design reviews, root cause analysis, and research tasks requiring diverse expert input.

Quick Start

Run the autogen_runner.py with mode debate, specifying a task and the agents to start a consensus-driven discussion.

Frequently Asked Questions about autogen-collab

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

FAQPage Schema

How do I automate multi-agent debates to reach a consensus on architecture decisions?▼

Multi-agent debates for architecture decisions are automated by orchestrating specialist agents through configurable rounds to surface consensus decisions. This AutoGen-style coordination applies explicit signals to detect agreement and generate final results with audit logs.

When do I need multi-agent orchestration for root cause analysis?▼

Multi-agent orchestration is needed for root cause analysis when diverse expert perspectives improve outcomes. Orchestrating specialist agents through structured debate rounds surfaces consensus decisions and logs conversation transcripts for knowledge capture.

How do I coordinate multiple agent turns and log conversation transcripts for design reviews?▼

Coordinate multiple agent turns by running the debate runner with configurable agent sets and timeouts. The system logs conversation transcripts and run metadata alongside the final consensus result, providing provenance for design reviews.

Can I configure agent sets, rounds, and timeouts for consensus-driven research tasks?▼

Consensus-driven research tasks support configurable agent sets, rounds, and timeouts. The orchestration detects consensus using explicit signals, enabling diverse expert input to converge on a final result with provenance and audit logs.

Does multi-agent consensus orchestration require external dependencies to run?▼

Multi-agent consensus orchestration runs without external dependencies, using OpenClaw's gateway to automate AutoGen-style debates. It handles coordination of multiple agent turns, logging, consensus signaling, and final result generation natively.