Surmado Code Review

Surmado Code Review is an automated code review tool specifically designed to optimize the workflow of small development teams, independent programmers, and coding founders. Its primary function is to act as the first layer of technical review for every GitHub Pull Request (PR), ensuring that code meets quality and security criteria before a human reviewer steps into the process.

The engine behind this application is Scout, an artificial intelligence agent that utilizes advanced models from Anthropic and OpenAI. Unlike traditional linters that are limited to detecting syntax errors, this tool analyzes the context, architecture, and intent of the code. The process integrates natively via GitHub OAuth, activating automatically with every push or through specific commands, processing diffs in real-time to provide a structured response in minutes.

One of the most standout capabilities of Surmado Code Review is its focus on custom standards. The AI uses a configuration file called STANDARDS.MD, where users define their own rules, naming conventions, and architectural patterns. Scout uses this document as a master guide, ensuring each review is consistent with the project's specific needs rather than just generic programming rules.

Key features and practical benefits:

• Detection of solid patterns: Identifies and highlights technical successes so the team can replicate them in future development.
• Actionable improvement suggestions: Points out errors or areas for optimization based on defined standards, providing concrete steps to resolve them.
• Human reviewer brief: Generates an executive summary that tells the team where to focus their attention (architecture, business logic, trade-offs), eliminating the need to manually search for minor typos.
• Data contract verification: Automatically alerts when a change affects schema paths or read/write patterns in the data layer.
• PII filtering: Detects and filters personally identifiable information in logs to protect user privacy.

Regarding code privacy and security, the tool follows a zero-retention policy. Code snippets (diffs) are sent to the language model's API solely to generate the review and are neither stored nor used to train external AI models. The final result exists exclusively within the comment posted on the user's repository.

This solution is ideal for those seeking a GitHub AI tool that offers deep analysis aligned with business rules, allowing for faster task completion through intelligent code reviews that don't replace humans, but rather enhance their judgment.