Feature
AI Debugger - Reproduce, Fix, and Prove It With a Test
Describe the bug and Agentcode reproduces it, traces it to the root cause, and fixes it. The pull request includes a new test that fails before the fix and passes after, so you can trust the fix is real.
In short
An AI debugger is a tool that locates and fixes defects in code automatically. Agentcode takes a bug description, reproduces the failure, finds the underlying cause rather than patching the symptom, and applies a fix. It then adds a regression test that fails on the old code and passes on the new code, and delivers the whole thing as a reviewable pull request. You review and merge, and the agent never merges on its own.
Reproduce first
The agent recreates the failing behavior before changing anything, so it fixes the bug you actually reported instead of guessing.
Find the root cause
Agentcode traces the problem to its source and fixes that, rather than masking the symptom and leaving the real issue in place.
Proven by a test
Every fix ships with a regression test that fails before and passes after, so the bug stays fixed and the proof lives in the PR.
See it in action
Watch the agent run a task
Pick a task
Plan
- planning
Files changed
Test run
Pull request
You review and merge. Agentcode never merges on its own.
More of what the agent does
See the whole loop on the how it works page, or compare Agentcode to GitHub Copilot.
Put the agent to work
Describe a task and get a pull request you review and merge.