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Description
Codeball is an AI designed for code reviews, providing a scoring system for pull requests that ranges from 0 (indicating a need for thorough examination) to 1. By leveraging Codeball, you can apply labels to prioritize your focus, automate approvals for straightforward PRs, and enhance your review process. Its user-friendly action comes with sensible defaults while offering extensive customization options to fit your specific workflow requirements. You'll be able to label pull requests that require careful scrutiny, ensuring that you remain vigilant and prevent bugs from sneaking through unnoticed. Codeball efficiently identifies, approves, or labels PRs deemed safe, allowing you to save valuable time by expediting the review of simpler contributions. Built to be fully customizable and programmable through GitHub Actions, Codeball Actions consist of various modular components that can be tailored to meet your needs. Utilizing a deep learning model, Codeball analyzes over one million pull requests, taking into account numerous factors for each submission. Its optimization for precision ensures that it only approves those contributions that it has a high level of confidence in, making it a trustworthy assistant in your development workflow. With Codeball in your toolkit, you can streamline your code review process while maintaining high standards of quality in your projects.
Description
Enable engineering teams to optimize their time and concentrate on their core competency, which is product development. Establish personalized patterns and outline your expectations for the review process, as Trag will handle it prior to your involvement. Formulate rules specific to your team’s use cases, allowing for as many as needed and as detailed as desired. Keep track of progress, knowing that any rules that fail can be restored by our AI. Direct commits are not allowed; instead, you will receive pull requests with the necessary fixes. Manage multiple repositories effortlessly, all within your reach. Invite your colleagues to collaborate seamlessly. Trag will conduct automatic reviews of pull requests based on the established patterns. Analyze pull request metrics to facilitate quicker and more informed decisions. Create your own patterns using everyday language, while Trag aligns rules with the changes in pull requests and implements automatic corrections. All data is encrypted and secure; we never make direct commits, utilizing only pull requests, and your code is not repurposed for development activities. Additionally, the system encourages continuous improvement through regular feedback cycles, ensuring that your engineering practices evolve alongside your team's needs.
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Has API
Pricing Details
Free
Free Trial
Free Version
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Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Codeball AI
Country
United States
Website
github.com/sturdy-dev/codeball-action
Vendor Details
Company Name
Trag
Website
usetrag.com