code-review

Automate a fresh-eyes code review by submitting your code snippets or diffs to be analyzed for correctness, security, and maintainability. This process identifies potential issues across multiple dimensions and generates structured findings before changes reach production.

A fresh-eyes code review evaluates code without prior context, analyzing correctness, security, architecture, performance, and maintainability. It generates structured findings with severity prefixes like Blocking, Consider, and Nit to highlight design and maintainability issues.

Yes, you can generate AI-specific prompts for Claude, Gemini, and Codex from a code diff. The analysis creates tailored prompts designed to leverage the specific strengths of each AI assistant for further code review and refinement.

Identify security and correctness issues in staged git changes by running a disconnected review analysis. This evaluates the code against strict security and correctness criteria, generating a detailed report with clear explanations and severity-based findings.

Yes, this approach works for analyzing code snippets without full project context because it performs a disconnected review. It assesses the provided code directly against correctness, security, and performance criteria to produce structured findings independently.

A limitation is that the AI performs a disconnected review without full project context, focusing strictly on the provided snippet or diff. It generates findings based on code quality and security criteria but may lack broader architectural awareness.