Question 1

Which should I use to review a GitHub pull request?

Accepted Answer

Try GitHub Copilot when you want to request a review from the pull request's reviewer panel and read its comments in GitHub. Try Codex when you want a separate Code Review workspace to inspect the diff, findings, comments, checks, and conflicts, then ask questions about a finding or request a scoped fix. These are documented workflow differences, not evidence that either reviewer finds more bugs. Sources: GitHub's code review guide and OpenAI's Codex pull request review guide.

Question 2

How do their review and follow-up workflows differ?

Accepted Answer

GitHub documents Copilot review comments on a pull request, suggested changes that can be applied, and an option to ask Copilot cloud agent to implement a suggestion when enabled. OpenAI documents discussing a pull request with Codex, investigating a finding, and asking Codex to prepare a bounded fix; it says to inspect the resulting diff and test results before submitting or merging. Check both linked official guides for the current steps.

Question 3

Can I give each reviewer repository-specific guidance?

Accepted Answer

Yes, the documented approaches differ. Codex Code Review can use concise, scoped review rules in AGENTS.md and cite relevant guidance in a finding. GitHub Copilot documents repository-wide and path-specific custom instructions, and also supports AGENTS.md for repository context. Start with a durable rule, then check it against a real violation, a safe counterexample, and an unrelated change; inspect every finding yourself. Sources: OpenAI's custom review rules guide and GitHub's code review guide.

Question 4

Can these reviews satisfy a required human approval?

Accepted Answer

Do not assume they do. GitHub says Copilot reviews are comments by default and do not count toward required approvals; an administrator can configure Copilot approvals. OpenAI describes Codex Code Review as an additional reviewer and says tests, branch protections, and required approvals continue to provide enforcement. Check your repository's current policy before relying on any automated review.

Question 5

How can I compare them on my own pull request?

Accepted Answer

Use a small, non-sensitive test pull request with a known issue, a safe change that should not be flagged, and an unrelated edit. Request each review on the same revision, record settings and setup, and compare findings against the code and tests. If trying custom instructions, keep the same rules for both where supported and note differences in how each tool reads them. This is a workflow trial, not a benchmark of general review accuracy.

Question 6

Does this comparison show which reviewer is more accurate or cheaper?

Accepted Answer

No. The cited official documentation describes interfaces, configuration, and follow-up workflows, not an independent head-to-head accuracy study or comparable total cost. Verify current eligibility, settings, and usage terms for your account before choosing.