Run a two-pass bug check before opening a PR
Use an agent to flag possible bugs first, then have it verify each one before any pull request is opened.
- What they did
- They used a tool-using loop called roast on code or prose before a PR was created. The agent made one pass to surface possible bugs in a structured list, then a second pass to challenge each item by checking the code and, when useful, running tests or small scripts. Only after that did it send the results to a person or a harness.
- How it went
- The post was just an announcement, so it did not report any bugs found or any counts. It also gave no false-positive rate or other measured outcome.
- Tips
- A setup like this works best when the verifier is stricter than the finder and every claim needs evidence. Keep the agent in read-only mode until you approve any fix, submission, or other irreversible step.
Try it yourself with Claude Code
In [repo or path], review [branch, commit, or PR] before I open a pull request. Do this in two stages: first, scan for every plausible bug or flaw and list them with a short reason; second, examine each item like a skeptic and try to confirm or rule it out using the code, tests, or small scripts. Return only issues that you can support with evidence, and for each one include the file, line, proof, and a fix suggestion. Pause and ask for my approval before making any change, submitting anything, or opening a PR.
Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.
Get 3 agent uses like this every morning
With the day's top AI news. Free, and one click to unsubscribe.
Related agent uses
Run bug fixes through a staged agent team
Use separate agent roles to reproduce, diagnose, review, and audit bugs before any irreversible step.
Turn a docs site into Markdown files with an agent
They used a custom crawler so Claude could save a 60-page docs site as Markdown without crowding the chat.
Convert a spoken brief into a working task tree
A developer fed a spoken project brief into LLM agents, which turned it into a spec, plan, scaffold, module tickets, and PRs.
Set up a GitHub bot that triages and patches bugs
They built a GitHub bot that sorts issues, reviews pull requests, answers with citations, and opens patch PRs for humans to check.
Use parallel agents to build a database engine
They split a SQLite implementation across several coding agents working in separate branches, then merged the pieces after repeated test-and-fix loops.
Check upgrade risks before you ship
A ReAct agent reviewed dependency data for a planned cloud upgrade and blocked it when it found an incompatible SDK version.