shelvick

shelvick / quoracle

Public

Recursive agent orchestration with multi-LLM consensus

github.comshelvickquoracle agentic-ai agentic-framework agents ai ai-agent
22
3
100% credibility
Found Feb 08, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Elixir
AI Summary

Quoracle is a browser-based dashboard for creating and overseeing teams of AI agents that collaborate hierarchically, making decisions only through agreement among multiple language models.

How It Works

1
🔍 Discover Quoracle

You hear about a smart tool that lets AI teams work together like a hierarchy of experts, making decisions only when they all agree.

2
🚀 Launch the dashboard

With one simple command, you start the web app and open your browser to see a clean control panel ready for action.

3
🔑 Connect your AI helpers

You add login details for a few AI services, like different smart thinkers, so they can join your team securely.

4
👥 Build agent personalities

You create profiles mixing your AI thinkers with specific abilities, like reading files or running safe commands, tailoring teams for different jobs.

5
✨ Start your first mission

You describe a tough task, pick a team leader personality, set a spending limit, and hit go – watching agents spawn helpers and collaborate in real-time.

6
📊 Watch the magic unfold

The dashboard shows your agent family tree growing, decisions forming by agreement, messages flying, and progress updating live.

🎉 Mission accomplished

Your agents deliver clear results from complex work, with full logs and costs tracked, ready for your next challenge.

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AI-Generated Review

What is quoracle?

Quoracle runs recursive AI agents in Elixir using Phoenix LiveView, where every decision requires consensus from multiple LLMs like GPT, Claude, and Gemini. Define oracles as these multi-model agreement mechanisms that spawn hierarchical child agents for complex tasks, persisting everything to PostgreSQL with a real-time browser dashboard. It solves unreliable single-model agents by only executing what a majority agrees on, via Docker or release tarballs.

Why is it gaining traction?

Multi-LLM quoracles meaning reliable recursive agents without hallucinations, beating langchain recursive agent volatility through diverse provider consensus. Real-time tree visualization and actions like shell commands, file edits, or API calls make debugging recursive agentic AI intuitive. Easy setup hooks Elixir devs cloning github recursive language model ideas into production-like experiments.

Who should use this?

AI researchers building recursive open meta agents for code analysis or deployments. DevOps engineers automating via quoracles digital gospel—safe, consensus-driven shell and file ops. Elixir fans prototyping recursive AI agent hierarchies beyond basic chains.

Verdict

Promising beta for quoracles digital gospel review seekers, with strong docs and Docker, but 13 stars and 1.0% credibility mean test thoroughly. Worth a spin for recursive agents tinkering; hold for maturity.

(178 words)

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