What is Deebo?
Deebo is an autonomous debugging agent designed to integrate into coding workflows using the Model Context Protocol (MCP). It autonomously investigates software bugs, runs experiments in isolated Git branches, and reports validated fixes without human intervention.
How to use Deebo?
To use Deebo, coding agents can call it when they encounter a bug they cannot confidently fix. It can be started with specific parameters, and it will manage debugging sessions through various commands like start, check, cancel, and add_observation.
Key features of Deebo?
- Spawns multiple subprocesses to test competing hypotheses.
- Runs each scenario in a dedicated Git branch for isolation.
- Validates or falsifies each approach and returns structured reports.
- Optionally logs session history to a memory bank for learning.
Use cases of Deebo?
- Offloading complex bug investigations from coding agents.
- Running real experiments in codebases to find validated fixes.
- Enhancing the debugging capabilities of coding agents like Claude and Cline.
FAQ from Deebo?
- Can Deebo handle all types of bugs?
Yes! Deebo is designed to investigate a wide range of software bugs autonomously.
- Is Deebo easy to integrate with existing coding agents?
Yes! Deebo is built to be compatible with any MCP-compatible agent, making integration straightforward.
- How does Deebo ensure the accuracy of its fixes?
Deebo runs multiple scenario agents in parallel, validating each hypothesis before reporting a solution.