Prompt Lab

Project description

Prompt Lab coordinates focused agents, scores the quality of each completed run, and uses reviewer feedback to improve the next attempt. The team built the full workflow during the hackathon, using Pioneer for the core agent loop and Guild.ai for evaluation, communication, or runtime support. The demo includes a visible activity trace so judges can inspect what each agent did and where human approval was required.

Project links

• GitHub repository
• Project website
• Demo video

Technical architecture

AG2 agents independently inspect risk, commercial terms, and implementation requirements before a synthesis agent resolves disagreements with citations.

Setup instructions

Clone the public repository, install dependencies, copy .env.example to .env.local, add the documented API keys, and run the development command in the README.

Lessons learned

The team found that clear handoffs and fast evaluation loops mattered more than adding more agents. Pioneer handled orchestration while Guild.ai made the result easier to inspect and improve.

Additional screenshots or links

• https://docs.ag2.ai/latest/
• https://github.com/ag2ai/ag2