Introducing Lean Collab: A Multi-Agent Orchestrator for Long-Running LLM Tasks

✍️ OpenClawRadar📅 Published: February 13, 2026🔗 Source
Introducing Lean Collab: A Multi-Agent Orchestrator for Long-Running LLM Tasks
Ad

Lean Collab is an open-source orchestrator developed by Mutable State Inc., designed to handle complex, long-running tasks typically unsuitable for single-agent large language models (LLMs). The orchestrator breaks tasks down into manageable components, delegating them to sub-agents that work in parallel and share discoveries in real-time.

Key Features

  • Task Decomposition: The orchestrator agent breaks down lengthy and intricate tasks into smaller assignments for sub-agents to handle.
  • Parallel Sub-Agents: Sub-agents execute their tasks concurrently, speeding up processing times.
  • Task State and Progress Subscription: Track the task's progress with real-time updates, allowing for dynamic adjustments as needed.
  • Real-Time Intermediate Sharing: Intermediate discoveries among agents are shared in real-time to improve overall task efficiency and accuracy.

This setup has been tested on complex math problems at the Putnam level but also applies to software refactoring, app building, and comprehensive research tasks.

Ad

Installation and Setup

Prerequisites include Lean 4 and Mathlib installation. Configure your environment by installing tools like Rust and setting up the Lean project with appropriate dependencies. For authentication, you'll need an API key from ensue.dev. Sample configuration files and environment setup details are provided in the source documentation.

For a detailed setup walkthrough and source code, it's recommended to clone the repository and review the README for instructions on configuring and deploying your own instance of Lean Collab.

📖 Read the full source: HN AI Agents

Ad

👀 See Also

Claude-First Analytics MCP Server: Giving AI Agents Direct Access to Web Analytics Context
Tools

Claude-First Analytics MCP Server: Giving AI Agents Direct Access to Web Analytics Context

A developer rebuilt their web analytics tool as an MCP server, exposing simple web analytics, trackable links, and product insight tools directly to Claude, enabling AI agents to leverage site data alongside code and database context.

OpenClawRadar
Building an Agentic RAG for Obsidian with Claude and an Eval Harness to Detect Hallucinations
Tools

Building an Agentic RAG for Obsidian with Claude and an Eval Harness to Detect Hallucinations

A developer built an agentic RAG system over an Obsidian vault to let Claude answer questions from engineering books, then created an eval harness using Claude Sonnet as a judge to detect when the agent was confidently wrong. Rubric iterations improved judge-human agreement from 39% to 94%.

OpenClawRadar
Skill Seekers v3.2.0 adds YouTube tutorial extraction for Claude skills
Tools

Skill Seekers v3.2.0 adds YouTube tutorial extraction for Claude skills

Skill Seekers v3.2.0 now extracts content from YouTube tutorials to create structured SKILL.md files for Claude. The tool uses a two-pass AI enhancement workflow to clean OCR output and generate usable documentation from video content.

OpenClawRadar
quorum: AI Code Governance Tool Enforces Independent Model Review
Tools

quorum: AI Code Governance Tool Enforces Independent Model Review

quorum is a governance layer for AI-assisted development that enforces a consensus protocol requiring code to be independently reviewed by a different model before committing. It includes three structural gates that block progress: audit, retro, and quality gates.

OpenClawRadar