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Runbook Rover

A self-improving agent team for researching a market and producing a cited decision brief.

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Project description

Runbook Rover 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 Replay.io for the core agent loop and Pioneer 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

Technical architecture

A CrewAI flow coordinates a researcher, source checker, analyst, and editor. Every claim must retain its source before the editor can publish the brief.

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. Replay.io handled orchestration while Pioneer made the result easier to inspect and improve.

Additional screenshots or links

https://docs.crewai.com/
https://github.com/crewAIInc/crewAI

Tools used

Replay.io

Pioneer

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