Best AI Code Review Tools for Teams Using Codex and Cursor in 2026

When a team's agents write most of the code, the review step decides how soon the team merges. Codex code review and Cursor Bugbot now review the output of the tools that wrote it, so a team running both agents ends up with two reviewers and two rule files.

OpenAI rebuilt its own Git backend, Pando, after Codex-driven pushes, merges and fetches pushed monorepo reliability at times below 90%. One engineer designed the architecture of Pando, and teams of agents implemented it, taking Pando from kick-off to production in 10 weeks, according to OpenAI's Nov 2, 2026 post on scaling Git at OpenAI.

At that volume, review becomes the next bottleneck. 25.8% of developers name reviewing and validating AI-generated code as their primary delivery constraint, according to the Qodo State of AI Code Quality 2026 (Censuswide, 500 US developers and 300 US leaders, August 2026, self-reported).

What This Guide Covers

Teams that run Codex and Cursor side by side see pull requests from both land in the same repos every day. Here is what this guide covers, in order:

1. How Codex code review works, locally and on GitHub
2. How Cursor code review works, before push and on the PR
3. A side-by-side table of four reviewers
4. The rule-file split between AGENTS.md and BUGBOT.md
5. What an outside reviewer adds for a mixed-agent team
6. How to test reviewers on your own PRs

High-velocity teams feel the split first, because the Codex half and the Cursor half each get a different reviewer. Engineering orgs with both agents across many teams and repos feel it later and harder, because every repo grows its own copy of the review standards.

TL;DR: Which AI Code Review Tool Fits a Team Using Codex and Cursor

Each bundled reviewer is strongest for the developers inside its own tool. An outside reviewer is the one that reads every PR from the whole team the same way. For the basics, see how AI code review works.

Codex code review runs /review in your checkout and @codex review on GitHub pull requests, with rules in AGENTS.md and a P0 and P1 focus on GitHub.

Cursor code review splits into Agent Review and /review-bugbot before you push, then Bugbot on every PR update, with rules in BUGBOT.md.

GitHub Copilot code review reviews in GitHub and in the major editors, with rules in Copilot's instruction files and AGENTS.md.

Qodo, the AI code review platform, is the independent review layer on every PR in your Git, whichever agent wrote the change, and Qodo's Agentic Toolbox runs the same review inside Codex before the PR exists. At OpenAI's volume, one standard across both agents matters more than a second opinion from the same tool.

How Codex Code Review Works

Codex reviews in two places with the same reviewer, in the terminal and on the PR, so the Codex half of a team gets one standard throughout.

Local Review With /review

Codex's built-in /review command reviews the changes in your Git checkout. In the CLI, you can review against a base branch, review uncommitted changes (staged, unstaged and untracked files), review a commit, or give custom review instructions.

The app and IDE extension support the base-branch and uncommitted scopes. Codex reports prioritized findings without changing your working tree.

The command appears only when the project sits inside a Git repository. Findings show up as inline comments in the review pane, and if you ask Codex to apply the fixes, your normal sandbox and approval settings apply.

PR Review With @codex review

On GitHub, a developer mentions @codex review in a PR comment, or the team turns on automatic reviews per repository. Codex posts a standard GitHub review, and on GitHub it flags only P0 and P1 issues, so comments stay on high-priority risks. GitLab merge request support is in preview.

# In your Codex session, inside a Git repo /review > Review against a base branch: main # On a GitHub pull request @codex review @codex review for issues in the database migration 

A tight P0 and P1 focus keeps noise down on the PR. One reviewer in the terminal and on the PR keeps the Codex half of the team on one standard.

After a review, a developer comments @codex fix the P1 issue, and Codex starts a cloud chat with the PR as context and can push a fix back to the branch when it has permission. Finding and fix both stay inside Codex.

Writing Code Review Rules in AGENTS.md

Codex searches the repo for AGENTS.md files and follows the code review rules in a ## Code Review Rules section. Root rules apply everywhere, and a nested AGENTS.md adds rules for the service below it, so each changed file carries only the guidance that covers it.

Keep the rules short. Start with two or three rules, state the safe path for each, and leave mechanical checks in CI, as OpenAI's Codex docs advise. Review rules don't replace tests, branch protections or required approvals, the same docs add.

The rules question gets harder once Cursor joins the repo.

How Cursor Code Review Works: Agent Review Before Push, Bugbot on the PR

Cursor splits review into a local layer and a PR layer that share one rules file, so the Cursor half of the team works from BUGBOT.md.

Agent Review and /review-bugbot Before You Push

Cursor Agent Review reviews local changes inside Cursor, at Quick or Deep depth. The /review-bugbot skill runs Bugbot from the agent before you push, and by default reviews every change on the branch against the base branch, committed and uncommitted. /review-bugbot runs in Cursor 3.7 or later, at cursor.com/agents, and in the Cursor CLI.

Local Bugbot reviews stay in sync with the PR. Cursor stores the patch ID of the reviewed diff, and when Bugbot on GitHub, GitLab or Bitbucket sees the same diff in a PR, Bugbot skips the repeat review and says so in a comment.

Bugbot on Every PR Update

Bugbot reviews automatically on every PR update, or on demand when someone comments cursor review or bugbot run. Bugbot reads existing top-level and inline PR comments to avoid repeating feedback, and each finding comes with Fix in Cursor and Fix in Web links. By default, follow-up runs review only the changes since the previous review.

Bugbot connects to GitHub (including Enterprise Server), GitLab (including self-hosted), Bitbucket (including Data Center), Azure DevOps Services and Cursor's own Origin. The Bugbot check concludes neutral by default when findings exist, and fails only when a team configures fail-on-unresolved.

Cursor Bugbot Rules in BUGBOT.md

Cursor Bugbot rules come from four places, merged in order: Team Rules from the dashboard, project .cursor/BUGBOT.md files (nested files apply to the folders below them), learned rules and manual rules. Bugbot learns from merged or closed PRs, and @cursor remember adds a learned rule inline.

Project rules in .cursor/rules/*.mdc don't apply to Bugbot runs, as Cursor's Bugbot docs state. A rule a developer wrote for Cursor's coding agent doesn't reach Cursor's reviewer unless someone copies it into BUGBOT.md.

Codex Code Review vs Cursor Bugbot vs Copilot: Side by Side

For a team, the three bundled reviewers differ most on where rules live and which Git platforms they cover. Here is each on the same rows, with Qodo as the fourth column.

Two vendor caveats support layering. Copilot won't spot every problem and its feedback should be supplemented with human review, as GitHub's Copilot docs note, and Codex review rules don't replace tests or required approvals, according to OpenAI's docs. For more on Copilot's reviewer, see this glossary entry on GitHub Copilot code review.

One Rulebook for a Team on Both Agents: AGENTS.md, BUGBOT.md and a Shared Review Layer

The rule file one half of the team wrote for its reviewer is invisible to the other half's reviewer.

Where Each Reviewer Reads Its Rules

Codex reads review rules from the ## Code Review Rules section of AGENTS.md. Bugbot reads BUGBOT.md and skips .cursor/rules by default. Copilot reads copilot-instructions.md, *.instructions.md and AGENTS.md. A team with both agents ends up with two or three rule files per repo, and the copies drift apart.

Take one illustrative rule, "money values never use floats". The Codex half writes the rule into AGENTS.md, the Cursor half writes the rule into BUGBOT.md, and three months later only one copy covers the new refunds service. Both reviewers pass their own PRs, and the team's standard now depends on which agent opened the PR.

How Qodo Reads the Same Rule Files

Qodo imports rules from repo files such as AGENTS.md, CLAUDE.md, copilot-instructions.md and the .cursor/rules files that Bugbot skips by default.

Since Qodo 3.2, teams choose which files and folders count as rule sources. Qodo's rules detection agent adds rules learned from review comments the team accepted and acted on, so the standards grow from your own decisions.

Qodo's rules detection agent learns only from accepted comments that led to code changes, on GitHub, GitLab and Azure DevOps. Admins choose whether mined rules wait for approval. Enterprise teams get one rulebook scoped by folder and applied across Git organizations, instead of one file per agent per repo.

A Practical Split for Mixed Teams

One practical split keeps shared standards in AGENTS.md and Bugbot-only notes in BUGBOT.md. Codex and Copilot both read AGENTS.md, so the shared file covers two of the three reviewers. For the wider idea, see this glossary entry on AGENTS.md files.

Writing the rules well matters as much as where they live. A rule that names the safe path and the reason holds up across reviewers, and this guide to custom review rules covers the patterns that work.

Why the Reviewer Should Sit Outside the Tool That Wrote the Code

A reviewer bundled into the writing tool shares its context, and sometimes its blind spots. An outside reviewer reads every PR from the team the same way, whichever agent wrote it.

Same Tool, Same Assumptions

A second agent called "reviewer" can share the first agent's wrong assumption about the ticket. The system that generates code shouldn't decide whether the code ships, and you shouldn't review code with the same tool that wrote it. For the longer argument, see the case for an independent verification layer.

For the Developers on Codex: Qodo's Agentic Toolbox Inside Codex

Qodo's Agentic Toolbox runs the same review locally, through the CLI, as a plugin for Codex and Claude Code, as a Kiro Power, or through MCP. Qodo retired its IDE plugin on Nov 1, so local review now runs through the Agentic Toolbox.

Inside Codex, the Reviewer skill in Qodo's Agentic Toolbox reviews the agent's local changes with the same engine that will review the PR in your Git.

Installing Qodo's Codex plugin takes four steps:

1. Open ChatGPT on Desktop and select Codex.
2. Click Plugins in the left navigation bar.
3. Type Qodo in the search field.
4. Click + next to Qodo to install the plugin.

After installing, add Qodo's default instructions template to AGENTS.md, so Codex knows when to call the review. Developers who prefer the terminal can install the Agentic Toolbox with curl -fsSL https://get.qodo.ai | sh (Node.js 20+) and run qodo review.

Qodo's local review works on uncommitted and untracked changes, and only the base commit has to be on your Git provider.

For the Developers on Cursor: Qodo in Your Git

Whatever editor or agent wrote the change, Qodo reviews the pull request in GitHub, GitLab, Bitbucket, Azure DevOps or Gerrit. The Cursor half of the team needs nothing new in the editor, because the review runs where the PR lives.

What Qodo's PR Review Reads

Qodo's PR review reads cross-repo context, so a change in one repo that breaks a consumer in another repo gets flagged at PR review. PR history shows how the team handled similar findings before. Since Qodo 3.2, follow-up reviews focus on your latest fixes, and the first review of a PR is never narrowed.

Context is where AI review still falls short for many teams. 38% of engineering leaders name keeping architecture consistent as one of their biggest quality and governance gaps, according to the same Qodo report. Qodo flags; your team decides what blocks the merge.

Choose Qodo When Your Team Runs Codex and Cursor Side by Side

A team with two agents often has two rule files, and its PRs look fine inside each tool. Qodo gives every PR one standard and one reviewer.

Signs Qodo Is the Right Pick

Choose Qodo when your team runs Codex and Cursor side by side and wants one independent reviewer on every PR.

Choose Qodo when you want your Codex developers' agents to check their changes with the same engine that will review the PR, before the PR exists.

Choose Qodo when a change in one repo can break another and you want that break flagged at PR review.

Choose Qodo when you want rules learned from your own team's accepted review comments, and fewer, higher-signal findings for everyone on the team.

What Each Kind of Team Gets

Both kinds of team get agent code merged sooner, with fewer rollbacks. High-velocity teams keep the rule files they already have, AGENTS.md for Codex and .cursor/rules for Cursor, and Qodo checks them on every PR, with setup measured in minutes and no new process.

Enterprise teams get one rulebook across many repos and both agents, reviews on GitHub, GitLab, Bitbucket, Azure DevOps and Gerrit, single-tenant, on-prem and air-gapped options, and every finding logged and exportable. For more options, see these enterprise code review tools.

Qodo fits teams that need one independent review layer across Codex, Cursor and the five Git providers Qodo supports, because Qodo reviews the code both agents write against one rulebook, before the PR and on the PR. For the GitHub and GitLab view, see this list of agentic AI code reviewers.

How Your Team Can Test AI Code Reviewers on Its Own PRs

A team should count fixed findings, not comments. A reviewer that leaves 40 comments and gets two fixed costs more attention than a reviewer that leaves five and gets four fixed.

A Five-Step Test

1. Pick 10 to 20 recent merged PRs from both Codex and Cursor developers, each with a known follow-up fix.
2. Run each reviewer on the same PRs at a comparable effort level.
3. Record findings a person would act on, findings the team would dismiss, and misses.
4. Compare noise per PR across the reviewers.
5. Check where each reviewer reads its rules, and whether one rule change reaches all of them.

Keep the Test Fair

Qodo's fix loop optimization narrows follow-up reviews to your latest fixes. If you benchmark for maximum recall, Qodo's docs suggest switching the optimization off. Benchmarks are easy to misread, and this breakdown of AI review benchmarks shows what false-positive numbers do and don't mean.

Edge cases deserve their own column in the test.

36.4% of developers say reviewing AI-generated code now takes more cognitive effort to spot hidden AI bugs, according to the same Qodo survey, so seed a few PRs where the follow-up fix was an edge case. For how a review loop should end, see my notes on an agentic review loop.

Summary

Codex reviews locally with /review and on GitHub with @codex review, reading rules from AGENTS.md. Cursor splits review into Agent Review before push and Bugbot on the PR, reading rules from BUGBOT.md.

Copilot reviews in GitHub and the editor. Rule files don't carry across a mixed-agent team, so an outside reviewer gives every PR from the team the same standards. One reviewer and one rulebook on every PR means agent code from both halves of the team merges sooner, with fewer rollbacks.

For the basics behind all four tools, start with what code review is.

For a wider shortlist beyond Codex and Cursor, see these code review tools for enterprise teams.

FAQ

What does Codex /review check?

In the CLI, Codex's /review checks the changes in your Git checkout against a base branch, your uncommitted changes, a single commit, or custom instructions. Codex reports prioritized findings without changing your working tree.

Is Cursor Bugbot free?

Bugbot bills by usage, under Cursor's May 2026 pricing update. Individual accounts draw first on included usage, then on prepaid credit, while teams bill from prepaid credit, and Cursor's pricing page lists current rates.

What's the difference between Bugbot and Agent Review?

Agent Review is a local review inside Cursor, at Quick or Deep depth. Bugbot reviews pull requests on every update and posts a CI status, and /review-bugbot runs the same Bugbot review from the agent before you push.

Can Codex review GitLab merge requests?

GitLab merge request support in Codex code review is in preview. GitHub pull request review is generally available.

Does Qodo work with Cursor?

Qodo reviews the pull request in GitHub, GitLab, Bitbucket, Azure DevOps or Gerrit, whatever editor or agent wrote the change. The Cursor half of a team gets Qodo's review on every PR with nothing new to install in the editor.

Can one team use Codex and Cursor with the same review rules?

Keep shared standards in AGENTS.md, which Codex and Copilot both read, and Bugbot-only notes in BUGBOT.md. Then add one outside reviewer on the PR that imports the repo's rule files, so every PR meets the same standard.

Is Qodo a test generation tool?

Qodo isn't focused on test generation, even though some authors still point to it as a key strength. In my experience, Qodo is best at AI code review and code governance for teams running Codex and Cursor side by side who want one independent reviewer on every pull request.