zeynepyorulmaz

zeynepyorulmaz / openclaw-orchestrator

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Adaptive multi-agent orchestration framework — break down complex goals into parallel tasks, route them to specialized LLM agents, and iterate with a real-time web dashboard. TypeScript, Zod-validated, SQLite-backed.

zeynepyorulmaz.github.ioopenclaw-orchestrator agent-framework ai-agents ai-orchestration autonomous-agents developer-tools
23
3
69% credibility
Found Feb 23, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
TypeScript
AI Summary

A dashboard and command tool that coordinates specialized AI agents to break down and complete complex goals through adaptive planning and execution.

How It Works

1
🔍 Discover the Orchestrator

You stumble upon this clever tool that teams up smart AI helpers to handle tough jobs without chaos.

2
💻 Get it ready on your machine

A simple setup gets everything installed and waiting for action in just a few minutes.

3
🔗 Link your AI specialists

Connect a bunch of focused AI assistants, each good at their own thing like researching or coding.

4
📱 Fire up the watching screen

Open a friendly web page that shows live updates as your team works together.

5
🎯 Share a big goal

Tell it something challenging, like comparing tech options or planning a project.

6
⚙️ See smart teamwork in action

Watch it slice the goal into bite-sized jobs, hand them to the right helpers, and build results step by step.

🎉 Celebrate spot-on results

Receive a polished final answer or creation, all safe and speedy thanks to the team's coordination.

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Star Growth

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AI-Generated Review

What is openclaw-orchestrator?

openclaw-orchestrator is a TypeScript framework for adaptive multi-agent orchestration, designed for OpenClaw gateways. It takes complex goals—like adaptive multi-agent reasoning for workflows or planning—and breaks them into parallel tasks routed to specialized LLM agents with isolated tools for security. Users get a CLI for quick runs (`openclaw-orchestrator run "Compare React vs Svelte"`), a real-time web dashboard, and Zod-validated, SQLite-backed persistence, all over WebSockets.

Why is it gaining traction?

Unlike rigid single-agent setups or predefined DAGs, it uses an LLM-driven adaptive loop that iterates based on results, dynamically discovering agents via metadata for plug-and-play scaling. The zero-dependency dashboard streams live execution, task outputs, and history, while adapters support OpenClaw, HTTP endpoints, or plain functions. Devs love the least-privilege security—coder agents get shells but no web access—making multi-agent systems safer and more efficient.

Who should use this?

AI engineers building adaptive multi-agent systems for tasks like traffic light control, healthcare interventions, or bitcoin trading bots. Teams orchestrating LLM specialists for research, coding, or analysis pipelines. OpenClaw users wanting a meta-layer to coordinate gateways without rebuilding from scratch.

Verdict

Grab it for early multi-agent experiments—solid CLI, API, and docs make prototyping fast, with Vitest coverage and TypeScript safety. At 12 stars and 0.7% credibility, it's pre-1.0 raw; test thoroughly before production, but the adaptive routing hook delivers immediate wins.

(198 words)

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