Heal · comparison · October 2026
Heal vs CodeRabbit: CodeRabbit reads the diff, Heal runs the product
CodeRabbit was the fastest bot in our benchmark. It named almost none of the defects users would hit.
CodeRabbitCode reviewTL;DR
- CodeRabbit is an AI code reviewer: it summarises and comments on a pull request minutes after the push. Heal builds a production-like sandbox of the product and drives it as its users do, then proves every defect with a failing test.
- CodeRabbit was the fastest to comment, with a median of 4 minutes, and reviewed every one of the 236 PRs.2,3
- On top of cubic and Greptile it named one more Heal defect. On the three open-source products it named none of the 74.4
- 70 % of the user-facing defects Heal proved were found by no review bot. Keep CodeRabbit for the diff; add Heal for what users hit.5
1. Heal and CodeRabbit, side by side
Both aim to catch defects before they reach users. CodeRabbit reads what a developer changed; Heal runs what users will meet.1
| CodeRabbit | Heal | |
|---|---|---|
| What it is | A PR review bot: it reads the diff and comments on it | A runtime bug hunter: it runs the product and proves the defects it finds |
| Input | A diff, with the codebase as context | The whole codebase, and a diff |
| The question it answers | What would a developer reading this change fix? | What will a user hit when they use the product? |
| When | Minutes after the push: a median of 4 minutes in the benchmark, the fastest of the three | Minutes to hours: a full run over the product |
| Does it run code? | No: it reads the code and its context | The whole product, in the Heal application sandbox, through every entry point: UI, API, CLI, webhooks, jobs |
| Its proof | An argument in a comment, with a proposed fix | A test that fails on the running product |
| Best at | Style, consistency, internal guidelines, and files no user reaches: CI, migrations, scripts, tests | Behaviour, security and performance defects a user reaches, across files, PRs and repositories |
2. What the benchmark measured
CodeRabbit is quick and thorough on the diff: it reviewed all 236 PRs and posted 329 comments on the open-source products, most of them summaries of the change. 70 raised a defect.2,3
Of the 74 Heal defects on the open-source PRs all three bots reviewed, it named none. On Product A, it named one that cubic and Greptile had both missed.4
The defects it missed are the ones the diff could not show: a bug that takes two repositories, three PRs, or the frontend and the backend disagreeing about a route.5
3. What CodeRabbit catches that Heal doesn't
Much of what CodeRabbit writes is the change summarised for the reviewer, and its flags mostly sit where Heal does not look, by design: CI configuration, migration history, analytics, upgrade scripts, the product's own tests. No user reaches those files, so Heal never maps them.3,6
Some flags sit on code Heal tests but did not report, mostly race conditions, which one pass through a feature does not always trigger. The benchmark did not check whether those are real.6,8
4. Use both
CodeRabbit is on the diff within minutes and proposes a fix for nearly every claim. Heal runs later and longer, and hands back defects a user would meet, each with the test that proves it.7
Adding CodeRabbit to another review bot changed almost nothing in the benchmark: one Heal defect over cubic and Greptile together. The runtime adds what the review cannot see.4
Read the full benchmark, or run Heal on your repository.
5. Notes
Every number on this page comes from our benchmark of Heal against CodeRabbit, cubic and Greptile on 236 pull requests of five products (October 2026), or from its raw data.
- 236 pull requests of five products (two private, anonymised as Product A and Product B, and Formbricks, Sim and Infisical) replayed PR by PR into fresh private repositories, with CodeRabbit, cubic and Greptile installed on their default settings, Greptile with TREX on, and Heal's full run before and after the sequence of PRs tested. A language-model judge, calibrated on a manually curated sample, decides whether a bot's claim and a Heal defect on the same lines name the same problem. Benchmark, section 3: The benchmark.
- CodeRabbit reviewed all 60 of Product A's PRs and every PR of the four other products, on its default settings; on Formbricks the repository's own CodeRabbit config file applied. Benchmark, section 3: Benchmark stats.
- The per-bot counts on this page (comments posted, comments raising a defect, median delay before a comment) are computed from the appendix's raw data: every comment the three bots posted on the 146 replayed PRs of Formbricks (56), Sim (44) and Infisical (46), as CSV. A comment raising a defect is one the appendix tags functional, security, data, performance or concurrency; summaries, docs, tests and style are left out. Benchmark appendix: the raw data.
- Figure 4, every Heal defect on the PRs all three bots reviewed (247 across the five products): cubic alone named 46 (29 of 120 on Product A, 13 of 53 on B, 3 of 31 on Formbricks, 1 of 21 on Sim, 0 of 22 on Infisical); adding Greptile brings it to 52, all six on Product A; adding CodeRabbit to 53, the one on Product A. Benchmark, section 6: the truth about stacking.
- 70 % of the user-facing defects Heal proved on the code of the PRs tested (141 of 202, across the five products) had never been found by any of the three review bots. Benchmark, section 4: what code review bots don't see.
- The three bots' 1,003 distinct flags: 654 in files Heal does not read by design (CI configuration, migration history, dependency versions, analytics, upgrade scripts, the product's own tests); 202 on code Heal tests but did not report, mostly race conditions, not checked for whether they are real; 100 on code a later PR rewrote before Heal ran; 47 also found by Heal. Benchmark, section 5: what code review bots find and Heal doesn't.
- 98 to 99 % of the bots' claims come with a proposed fix. Heal's defects come with 1,085 regression tests across the five products, each one failing on the running product. Benchmark, section 7: Heal and code review find complementary issues.
- The bots' claims were not checked for relevance, while every Heal defect is proven by a test: a bias in the bots' favour. Whether the authors acted on a comment could not be checked, since the replays were isolated from the real history. A relatively small dataset: a useful signal, not a ranking. Benchmark, section 3: Limitations.