How to Automate GitHub Issue Fixes with Sweep AI

Sweep AI is a GitHub bot that reads an issue, writes the code change and opens a pull request for you. You install it on a repo, label an issue, and a few minutes later a PR appears with a diff and a short explanation of what it changed.

The pitch is simple: small bugs and clear feature requests stop sitting in a backlog. The catch is that Sweep only performs well on issues a new contributor could finish in an hour with no questions.

How do you install Sweep AI on a repository?

You install it as a GitHub App, not a CLI. The flow:

1. Go to sweep.dev and sign in with GitHub.
2. Install the Sweep GitHub App and select the repos you want it on. Start with one.
3. In the repo, add a sweep.yaml at the root with a one-line project description and your test command.
4. Open an issue, add the sweep label, and wait.

Sweep comments on the issue when it starts, then links the PR when it opens. If it gets stuck it asks a question in the thread instead of guessing — worth watching for the first few runs.

What makes an issue Sweep can actually solve?

Specific, self-contained, and testable. The three that Sweep handles reliably:

• A failing test plus the expected behavior.
• A clear bug report with steps to reproduce and the bad output.
• A small feature with an obvious location, like adding a flag to an existing function.

What it struggles with: cross-cutting refactors, anything needing design decisions, and issues that depend on context living outside the repo. Give it a vague ticket and you get a plausible-looking PR that misses the point — which is worse than no PR, because someone still has to review it.

Is Sweep AI free?

It has a free tier aimed at individual developers and open source, and paid plans for private repos billed per seat. The free tier limits how many PRs it will generate per month, so a busy repo will hit the ceiling. Public open-source projects generally get the most generous terms.

Budget for review time, not just subscription cost. Even good Sweep PRs need a human pass, and a bad one costs more to clean up than writing the fix yourself.

How should you review a Sweep pull request?

Read the diff, not the summary. Sweep’s description is generated from its own changes, so it will confidently describe code that does something subtly different from the issue.

Check two things first: does the test suite pass in CI, and did it touch files outside the scope of the issue? Scope creep is the most common failure mode. If a Sweep PR edits eight files to fix a typo, close it and move on.

Quick Summary

• Sweep AI converts labelled GitHub issues into pull requests automatically.
• Install it as a GitHub App and add a sweep.yaml with your test command.
• It works on specific, testable issues and fails on vague or cross-cutting ones.
• Free tier for individuals and open source; private repos are per-seat with PR caps.
• Always review the diff, and check for scope creep in changed files.

If you want a bot that critiques code instead of writing it, CodeAnt AI covers that side.