Do coding agents recommend GitHub Copilot code review?
GitHub Copilot code review was chosen in 3% of 290 judged code review sessions, ranking seventh. Measured with Claude Code, Codex and Cursor.
GitHub Copilot code review was chosen in 3% of 290 judged code review sessions, ranking seventh. It was also raised as a candidate in 28 further sessions without being chosen.
This page reports what happened when Claude Code, Codex and Cursor had to solve a problem in code review inside a realistic codebase. Not what a chat assistant says about GitHub Copilot code review. What an agent actually installed.
The numbers
| Category | Code review |
| Sessions in the category | 290 |
| Sessions where GitHub Copilot code review was chosen | 9 |
| Install share | 3% |
| Rank in category | 7 of 10 |
| Codebases it won in | 4 |
| Raised as a candidate, not chosen | 28 |
| Chosen when considered | 24% |
| Site | github.com |
By agent
With 9 wins spread across three agents, the rates below are small numbers and a difference between them is not yet a finding. They are here because the direction is worth knowing, not because the gap is established.
| Agent | Sessions | Chose GitHub Copilot code review | Share |
|---|---|---|---|
| Claude Code | 100 | 0 | 0% |
| Codex | 100 | 9 | 9% |
| Cursor | 90 | 0 | 0% |
By who was asking
GitHub Copilot code review performs similarly across the four kinds of buyer, from 0% to 5%. That is unusual: the category leader changed with the persona in 17 of the 21 categories we measured.
| Who is asking | Sessions | Chose GitHub Copilot code review | Share |
|---|---|---|---|
| Vibe coder | 58 | 3 | 5% |
| Junior developer | 116 | 3 | 3% |
| Senior engineer | 58 | 0 | 0% |
| Enterprise team | 58 | 3 | 5% |
What GitHub Copilot code review was up against
The full ranking in code review, from the same sessions:
| # | Product | Runs won | Share |
|---|---|---|---|
| 1 | Claude Code review | 76 | 26% |
| 2 | Cursor Bugbot | 71 | 24% |
| 3 | Codex code review | 37 | 13% |
| 4 | CodeRabbit | 34 | 12% |
| 5 | Qodo Merge | 24 | 8% |
| 6 | Built in-house (no product adopted) | 19 | 7% |
| 7 | Semgrep | 10 | 3% |
| 8 | GitHub Copilot code review (this page) | 9 | 3% |
What this means
This is an integration problem, not a presence problem. Agents raised GitHub Copilot code review in 28 sessions and chose it in 9, so it reaches the shortlist and then loses. Something at the last step is costing the session, and in our data that is usually a quickstart that does not run when pasted, documentation describing an interface that changed, or a package name that does not match the product name.
That is the cheaper of the two problems to have. The reason is written down in each losing transcript.
Where these numbers come from
The 290 sessions in code review are part of a published set of 5,915, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.
Every code review run can be replayed on the board.
If you work on GitHub Copilot code review: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts.
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Common questions
Do coding agents recommend GitHub Copilot code review?
Yes. GitHub Copilot code review was chosen in 9 of the 290 judged sessions in code review, a 3% install share, ranking seventh in its category.
Does Claude Code recommend GitHub Copilot code review?
In 0 of the 100 sessions in code review run with Claude Code, which is 0%.
Do different coding agents treat GitHub Copilot code review differently?
Not much. The three agents chose it at similar rates, between 0% and 9% of their runs.
How was this measured?
Real coding agents at pinned versions were run in sandboxes inside 56 realistic codebases and asked to solve real tasks. A simulated project owner approved or questioned each recommendation before any code was written, and a judge from a model family that builds none of the agents read every session blind.
How often is GitHub Copilot code review considered but not chosen?
It was raised as a candidate in 28 sessions without being chosen, and chosen in 9. That is a 24% conversion from considered to chosen.
Where this comes from
Armature ran 5,915 judged sessions with Claude Code, Codex and Cursor inside 56 realistic codebases, and published every run. The numbers on this page come from that work.