Gito: AI Code Reviewer
An AI-powered GitHub code review tool that uses LLMs to detect high-confidence, high-impact issues
About
Gito is an open-source AI code reviewer that works with any language model provider. It detects issues in GitHub pull requests or local codebase changes—instantly, reliably, and without vendor lock-in. Get consistent, thorough code reviews in seconds—no waiting for human availability.
Key Features
Parallelized LLM Analysis
Runs multiple model inferences in parallel to produce detailed code reviews in seconds, accelerating feedback on PRs and local changes.
Vendor-Agnostic Model Support
Works with any LLM provider (OpenAI, Anthropic, Google, local models, etc.), allowing teams to choose their inference provider or use on-prem/local models for privacy.
CI/CD & Git Integration
Integrates with GitHub Actions (and other platforms like GitLab) to automatically analyze pull requests, post review comments, and enforce quality gates in pipelines.
Configurable Rules & Severity
Customize review focus areas, severity levels, and rules to match project standards—filtering results for security, performance, maintainability, best practices, and more.
Local Analysis & Privacy Controls
Support for running analysis locally or routing code directly to a chosen model endpoint so code never passes through intermediary servers, improving security and compliance.
How to Use Gito: AI Code Reviewer
1) Install and configure: Add Gito to your repository (via README/installer) and set the desired LLM provider credentials or local model endpoint in configuration. 2) Integrate with CI or run locally: Enable the provided GitHub Actions workflow (or GitLab CI) to automatically analyze pull requests, or run Gito's CLI to scan local changes. 3) Review results: Gito posts findings as PR comments and summary reports—inspect high-confidence issues and suggested fixes. 4) Tune & enforce: Adjust config (rules, severity, focus areas) to reduce noise and optionally fail CI on critical findings to enforce quality gates.