AI Tool

Open Code Review Review

Open Code Review is an AI-powered command-line interface (CLI) tool developed by Alibaba for automated code review, integrating LLM agents while maintaining data privacy.

shipped Sep 1, 2026free

Why it matters

1Developed and open-sourced by Alibaba, serving tens of thousands of developers internally for two years.

2Offers a free tier with usage-based pricing at $0.291 per 1,000 tokens.

3Utilizes a hybrid architecture combining deterministic engineering with LLM agents for precise, line-level feedback.

4Supports integration with multiple LLM providers including Anthropic Messages API and OpenAI Chat Completions API.

About Open Code Review

Business Model

Usage-Based (Pay Per Use)

Usage Pricing

$0.291/1,000 tokens per token

Headquarters

Hangzhou, China

Platforms

Web, CLI (Terminal)

Target Audience

Developers and Teams looking for AI-assisted code reviews

Cost Examples

• Review 1,000 PRs: ~$291

GitHubOpen Source

overview

What is Open Code Review?

Open Code Review is a AI-powered command-line interface (CLI) tool developed by Alibaba that enables developers and teams to perform automated code reviews using integrated LLM agents. It provides actionable review comments with line-level precision, designed to identify bugs, security vulnerabilities, and performance issues while keeping data private.

features

Key Features of Open Code Review

Open Code Review incorporates a sophisticated architecture to deliver precise and customizable code review capabilities. Its design emphasizes control over LLM integration and data privacy, making it suitable for various development workflows.

Hybrid Architecture: Combines deterministic engineering for precise file selection and rule resolution with LLM agents for language generation and judgment.
Precise Comment Positioning: Generates structured review comments with line-level accuracy on Git diffs.
Multi-Model Protocol Support: Allows integration with various LLM providers, including Anthropic, OpenAI, and DeepSeek, via their respective APIs.
Effort-Driven Progressive Review: Supports reviewing specific commits, staged changes, or entire pull requests.
Smart Memory Compression: Optimizes token usage for cost-effective and efficient reviews.
Terminal-Native Interface: Provides a polished Text User Interface (TUI) for developers who prefer command-line workflows.

use cases

Who Should Use Open Code Review?

Open Code Review is designed for a range of technical professionals and teams seeking to enhance code quality and streamline development processes through automated AI assistance.

Individual Developers: For local AI-assisted development, providing instant feedback on staged changes or specific commits.
Software Engineers: To integrate automated code review into pull-request workflows, identifying security vulnerabilities and correctness issues before code merges.
Platform Teams: For seamless integration into internal systems, offering full control over data flow and review policies.
ML Researchers: To serve as a code quality verifier in reinforcement learning (RL) training pipelines, providing reliable reward signals for code generation models.
System Administrators: For auditing unfamiliar codebases or directories by reviewing entire files without a diff.

how to use

How to Use Open Code Review

Open Code Review functions as a command-line interface (CLI) tool, requiring initial setup for LLM API keys and configuration. It processes Git diffs or specified files to generate review comments.

1Install the Open Code Review CLI tool via npm or a similar package manager.
2Configure API keys for your preferred Large Language Model (LLM) provider (e.g., OpenAI, Anthropic) in the tool's configuration files.
3Run ocr review commands to analyze Git diffs (e.g., pull requests, staged changes) or specific files/directories.
4Review the generated comments directly in the terminal or integrate them into CI/CD pipelines.
5Adjust configuration settings (e.g., rules, LLM parameters) using JSONC files to customize review policies.

pricing

Open Code Review Pricing & Plans

Open Code Review operates on a freemium and usage-based model, allowing users to utilize a free tier and pay for additional LLM token usage. An optional subscription plan, OpenCode Go, provides curated model access.

Free Tier: Basic functionality with usage-based pricing for LLM tokens.
Usage-based: $0.291 per 1,000 tokens for LLM interactions. For example, reviewing 1,000 pull requests could cost approximately $291.
OpenCode Go: An optional subscription plan at $10 per month, offering stable access to a curated set of open coding models with included usage roughly six times the subscription price.

Pros

+Offers extensive control and optionality, allowing users to bring their own API keys and choose from various LLM providers (Anthropic, OpenAI, DeepSeek).
+Utilizes a hybrid architecture that combines deterministic engineering with LLM agents, ensuring precise, line-level comments and effective bug detection (e.g., NPE, XSS, SQL injection).
+Battle-tested and scalable, originating as an internal Alibaba tool used by over 40,000 developers and credited with detecting over 1 million code defects.
+Cost-effective, especially when using user-provided API keys (BYOK) or the OpenCode Go plan, potentially cheaper than some SaaS alternatives.
+Provides a polished, fast, and terminal-native Text User Interface (TUI) for developers who prefer CLI workflows.

Cons

−Configuration can be complex, particularly with JSONC files, requiring more setup compared to fully hosted agents.
−Requires users to make decisions regarding LLM models and providers, which can add initial overhead.
−Documentation is still evolving and may not fully cover all features and configurations due to the project's active development.
−The core CLI tool lacks direct IDE integration, which some developers might prefer for a more integrated workflow.
−Predicting pay-as-you-go costs with user-provided API keys (BYOK) can be challenging without usage limits.

Similar Tools

Open Code Review vs Competitors

Open Code Review distinguishes itself in the AI code review landscape through its open-source nature, hybrid architecture, and emphasis on user control over LLM integration and data privacy, contrasting with more closed or SaaS-based alternatives.

CodeRabbitOn Stork

Provides AI-powered code reviews directly on pull requests, focusing on identifying issues, suggesting improvements, and generating summaries.

CodeRabbit offers a very similar core functionality of AI-driven comments on pull requests as Open Code Review, potentially differing in the specific AI models used or the depth of analysis.

Trunk↗

Offers AI-powered code review, auto-fixes, and integrates with various linters and formatters to maintain code quality.

While both provide AI code review, Trunk offers a broader suite of code quality tools including linting and auto-fixing, whereas Open Code Review is more singularly focused on the AI review agent.

ReviewpadOn Stork

Automates pull request workflows using AI to generate summaries, suggest changes, and enforce repository policies.

Reviewpad extends beyond just AI code comments to offer comprehensive pull request automation, which might include more workflow management features than Open Code Review's primary focus on AI review comments.

Reviewdog↗

A flexible linter runner that integrates with code hosting services to post feedback from various tools and custom scripts on pull requests.

Reviewdog is a framework for running linters and tools, not an AI agent itself. Achieving AI code review similar to Open Code Review would require integrating a separate AI-powered linter or custom script, demanding more setup.

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