open-code-review vs e2e
Two of the top projects in Code review and testing, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
open-code-review
CLI that reviews Git diffs with an LLM agent and line-level comments
e2e
AI-driven end-to-end testing framework for web and mobile apps
Verdict
open-code-review ranks higher, 79 to 67. Of the 5 score parts we measure for both, open-code-review leads on 3, e2e on 1 and 1 is even.
- Adoptionopen-code-review leads by 28 points, 88 to 60: a wide gap.
- FreshnessEven at 100.
- Maintenancee2e leads by 3 points, 94 to 91: close to even.
- Easy to runopen-code-review leads by 17 points, 50 to 33: a wide gap.
- Agent-readyopen-code-review leads by 25 points, 70 to 45: a wide gap.
Pick open-code-review if you are
Teams adding LLM code review to local workflows or CI pipelines
- Deterministic file selection and bundling; each bundle runs as an isolated sub-agent
- Reviews workspace changes, branch ranges, single commits, or full files via `ocr scan`
Pick e2e if you are
Teams writing end-to-end tests for web and mobile apps in TypeScript
- Recorded agent actions replay with no model calls until the app changes
- Tests without agent steps need no model at all
| What we compare | open-code-review | e2e |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 88, widely used | 60, popular |
| Freshness | 100, active | 100, active |
| Maintenance | 91, healthy | 94, healthy |
| Easy to run | 50, easy | 33, some setup |
| Agent-ready | 70, partly | 45, minimal |
| Facts from GitHub and the README | ||
| Stars | 47.3k | 10.7k |
| License | Apache-2.0 (permissive) | Apache-2.0 (permissive) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | Go | TypeScript |
| Docker | No | No |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Mentioned | Not stated |
open-code-review
Open Code Review is a Go CLI (`ocr`) that reads a Git diff, groups related files into bundles, and runs each bundle through a tool-using LLM agent that produces structured review comments. File selection, rule matching, comment positioning and reflection are done by deterministic code rather than prompts. `ocr scan` reviews whole files when there is no diff, and delegation mode lets an existing coding agent do the review with its own model.
Who it is for: Teams adding LLM code review to local workflows or CI pipelines
Strengths
- Deterministic file selection and bundling; each bundle runs as an isolated sub-agent
- Reviews workspace changes, branch ranges, single commits, or full files via `ocr scan`
- Sessions can be resumed and browsed in a viewer; JSON output for automation
- Plugins for Claude Code, Codex, Cursor, Kimi Code, OpenCode; CI docs for GitHub, GitLab, Gerrit
Weaknesses
- Requires Git >= 2.41 and a configured LLM endpoint, unless delegation mode is used
- Recall is lower than general-purpose agents by the README's own benchmark
- Benchmark figures are published by the project itself, not independently verified
- No Docker or Compose files detected
- no GPU
- Needs Git >= 2.41, LLM provider API
- Models: configurable LLM providers, custom providers
e2e
TypeScript test runner where an agent carries out natural-language goals in the app, and ordinary locators and assertions verify the result in the same test. Agent steps that a later assertion checks are recorded and replayed on the next run without model calls until the app changes. Web runs use Playwright (Chromium, Firefox, WebKit); mobile runs use iOS simulators and Android emulators.
Who it is for: Teams writing end-to-end tests for web and mobile apps in TypeScript
Strengths
- Recorded agent actions replay with no model calls until the app changes
- Tests without agent steps need no model at all
- Web via Playwright; iOS and Android via simulators and emulators
- Examples for Next.js, Vite, Astro, Expo, SwiftUI, Compose, Flutter
Weaknesses
- APIs and config can still change between minor releases before 1.0
- CLI sends anonymous telemetry by default; opt-out required
- Agent steps need a model subscription, API key, or local model
- Hosted browser and simulator options depend on third-party services
- no GPU
- Needs Node.js, Playwright, agent-device, iOS simulator or Android emulator (mobile)
- Models: Bring your own subscription, API key, or local model
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