Open Source TypeScript Code Review Software

Codeball is a code review AI that scores pull requests on a grade from 0 (needs careful review) to 1. Use Codeball to add labels to help you focus, auto-approve PRs, and more. The Codeball action is easy to use (sane defaults) and is highly customizable to fit your workflow when needed. Label PRs when you should review them with caution. Stay sharp, don't let the bugs pass through. Identifies and approves or labels safe PRs. Save time by fast-tracking PRs that are easy to review. Fully customizable and programmable with GitHub Actions. Codeball Actions are built on multiple smaller building blocks, that are heavily configurable through GitHub Actions. Codeball uses a deep learning model that has been trained on over 1 million Pull Requests. For each contribution, it considers hundreds of inputs. Codeball is optimized for precision, which means it only approves contributions that it's really confident in.

A command-line tool aims to improve front-end engineer workflow and standards, powered by Node.js. Feflow (pronounced /ˈfefləʊ/) is a front-end flow and rule tool to improve engineering efficiency., and is hosted on Github: feflow. At present, it has been used in many applications, such as Now, Huayang Live, Huayang Friends, Mobile QQ Near Hand, Group Video, Group Gift, Huiyin, Tencent Myapp, Penguins and etc. With 80+ WEB/IOS/Andriod stable users, the cumulative production project reached 240+. Feflow refers to the thinking of Pipeline and divides work into five steps: init, develop, build, test, deploy. And corresponding to five basic commands: init, dev, build, test, and deploy. In addition to serving basic development workflows and specifications, Feflow provides an easy-to-expand plug-in mechanism for creating a team-wide toolchain ecosystem. Feflow only provides a CLI and kernel. The CLI is responsible for interacting with the command line terminal.

Kodus-AI is a framework for building, training, and deploying intelligent agents and models, especially focusing on practical AI workflows for businesses and automation. It provides a structured set of tools and abstractions that help teams design agent behaviors, orchestrate data pipelines, optimize inference, and integrate AI capabilities with applications or services. The platform often includes model management, scalable training workflows, and orchestration patterns that help teams move from research or prototypes to production-ready AI deployments. Through configurable pipelines and a focus on modularity, it supports experimentation while maintaining reproducibility and performance. Its tooling is typically designed to handle real-world imperatives like logging, monitoring, versioning, and hooking into operational infrastructure.

Matter AI is an AI-powered platform designed to enhance productivity through automated content generation, data analysis, and decision support. It leverages machine learning models to process text, analyze patterns, and generate insights, making it suitable for businesses looking to optimize data-driven decision-making. Matter AI integrates with various data sources and provides customizable AI workflows tailored to different industries.

This SonarSource project is a static code analyzer for JavaScript, TypeScript and CSS languages. In order to analyze JavaScript, TypeScript or CSS code, you need to have a supported version of Node.js installed on the machine running the scan. Recommended versions are the previous LTS version v14 and the latest version - v16. We recommend using the latest available LTS version (v16 as of today) for optimal stability and performance. v12 is still supported, but it already reached end-of-life and is deprecated. If node is not available in the PATH, you can use property sonar.nodejs.executable to set an absolute path to Node.js executable. If you have a community plugin for CSS analysis installed on your SonarQube instance it will conflict with the analysis of CSS, so it should be removed.

Manually adding types to your codebase can be a daunting task, especially given how much room there is for errors. It’s true that in some cases, the types will be obvious by just reading the code. But when I was adding types to a big project I inherited recently, I found myself actually running the code and setting a breakpoint inside a function to figure out the types that were being passed to it. This gave me an idea: build a tool that does this automatically and much faster, and then call it TypeWiz! TypeWiz is a tool that helps you enrich your TypeScript code while saving your precious time by automating the task of adding types to your code. TypeScript helps you ensure code quality (and also helps you explore your code), but it can only go so far on it’s own: you must provide it with type information to make the most of it.

Lint the browser compatibility of your code. Browser targets are configured using a browser list. You can configure browser targets in your package.json. If no configuration is found, browser list defaults to "> 0.5%, last 2 versions, Firefox ESR, not dead". Add polyfills to the settings section of your eslint config. Append the name of the object and the property if one exists. Toolchains for native platforms, like iOS and Android, have had API linting from the start. It's about time that the web had similar tooling.

This extension allows you to review and manage GitHub pull requests and issues in Visual Studio Code. The support includes authenticating and connecting VS Code to GitHub. GitHub Enterprise is supported by the community, please see this PR for how to set it up. Listing and browsing PRs from within VS Code. Reviewing PRs from within VS Code with in-editor commenting. Validating PRs from within VS Code with easy checkouts. Terminal integration that enables UI and CLIs to co-exist. Listing and browsing issues from within VS Code. Hover cards for "@" mentioned users and for issues. Completion suggestions for users and issues. A "Start working on issue" action which can create a branch for you. Code actions to create issues from "todo" comments.