Introducing SWE-Kit, headless IDE and AI-native tools for agents

We know you have tried at least once to build an AI agent to automate coding tasks. We also know your AI agent didn’t work; even if it did, it gave up when the code base became large. This doesn’t mean your AI agent is terrible; the problem is, more often than not, your tools.

From our experience of building software engineering tools and integrations for agents, we’ve found that apart from capable LLMs, tools play a significant role in deciding the usefulness of an agent. Then we thought, why not build a comprehensive IDE for AI agents just as a human developer?

This is how we came to build SWE-kit, a headless IDE for AI agents with AI-native tools. Coding agents will have separate isolated IDE with all the code intelligence features via Language Server Protocols (LSP), such as code completions and development containers for secure code execution.

State-of-the-art Performance on SWE-bench

To showcase the capabilities of the tools and agents, we tested the agent on the SWE bench, one of the most reputed benchmarks for testing the performance of AI coding agents. It has 2,294 issues from Django, Scikit-learn, Flask, etc.

The benchmark has two tracks: Verified and Lite.

⏺ Verified

Is a human-validated subset of the original dataset, consisting of 500 samples reviewed by software engineers.

⏺ Lite

Is a subset of the original dataset with 300 samples.

We tested our SWE agent on both tracks. The agent Scored 48.60% and 41% on Verified and Lite, respectively.

Read our full report on it here.

Features of SWE-Kit

As developers, we know that flexibility and freedom are top priorities. That’s why we designed SWE-Kit with these principles, ensuring it adapts to your unique workflow and preferences.

SWE-Kit is

⏺ Framework Agnostic

It is compatible with all the major agentic frameworks, such as LangGraph, CrewAI, Autogen, LlamaIndex, etc.

⏺ Specialized Coding tools

Use CodeAnalysis, File management, and Git tools to work with large codebases seamlessly.

⏺ Application integration

You can add GitHub, Jira, Linear, and more with AI agents to automate workflows.

⏺ Flexible runtime

Run your agents in secure and isolated environments. Use Docker for a complete local experience or any cloud-hosted solution like E2B and FlyIo.

What you can build with SWE-kit

To help you get started quickly, we’ve created several example agents:

1. GitHub PR Agent

Using SweKit, we built an automated GitHub code review bot. The GitHub PR Agent automates pull request reviews, helping identify code quality issues and flagging potential bugs. You can also integrate Slack and get a summary of a PR right in your channel, making the code review process feel less like a job.

2. Q&A with Codebase

We also created a Q&A bot for codebases that lets anyone ask questions about any codebase from Slack. The agent can explain specific functions, clarify dependencies, and offer insights into architecture. Again, you can integrate Slack to get answers right where your tech team resides.

3. SWE Agent

This is the agent we used to top the SweBench rankings. It interacts with GitHub repositories through GitHub Integration, navigating and working with local codebases using CodeAnalysis, file management and shell tools.