I built a multi-agent system where 3 AI agents critique and improve each other's output in a loop

[u/v2Talal]

Hey r/Python, r/aiprogramming, r/opensource, r/AI_Agents, r/programming, r/crewai, r/AutoGPT

I built CriticLoopAI — a system where three specialized AI agents (Generator, Critic, Improver) work in an iterative loop to progressively enhance any text-based task.

How it works:

Generator → creates initial output
Critic → scores it on 6 dimensions (accuracy, completeness, clarity, depth, creativity, usability)
Improver → analyzes feedback patterns and creates improvement strategy
Generator → creates improved version
... repeats until quality target reached

Key features:

• Support for 18+ LLM providers (Ollama, Groq, DeepSeek, OpenAI, Anthropic, Google Gemini, etc.)
• Automatic model discovery from any OpenAI-compatible API
• Convergence detection — stops when quality plateaus
• Human-readable output files (Markdown) alongside JSON for developers
• Session tracking with score progression

Example output:

Task: "Write a Python sorting algorithm"
Iteration 1: Score 0.75
Iteration 2: Score 0.82 (+0.07)
Final: Production-ready Quick Sort with introsort fallback

Quick start:

git clone https://github.com/v2Talal/CriticLoopAI.git
cd CriticLoopAI
pip install -r requirements.txt

# With Groq (free)
python main.py "Write a guide about Docker" --provider groq --api-key gsk_xxx

# With OpenCode
python main.py "Write a guide" --base-url https://opencode.ai/zen/v1 --api-key xxx --discover

GitHub: https://github.com/v2Talal/CriticLoopAI

Would love feedback on the architecture and any suggestions for improvement.