---
title: "SWE-agent"
type: "tool"
slug: "swe-agent-swe-agent"
canonical_url: "https://www.graphcanon.com/tools/swe-agent-swe-agent"
github_url: "https://github.com/SWE-agent/SWE-agent"
homepage_url: "https://swe-agent.com"
stars: 19724
forks: 2155
primary_language: "Python"
license: "MIT"
categories: ["evaluation-observability", "ai-agents"]
tags: ["agent-based-model", "llm", "cybersecurity", "developer-tools"]
updated_at: "2026-07-07T18:27:02.920666+00:00"
---

# SWE-agent

> Automatically fixes GitHub issues and performs cybersecurity tasks using your preferred language model.

SWE-agent utilizes a chosen large language model to autonomously address issues in real GitHub repositories, identify cybersecurity vulnerabilities, or perform customized tasks. It is developed at Princeton University and Stanford University with configurations managed through a single YAML file.

## Facts

- Repository: https://github.com/SWE-agent/SWE-agent
- Homepage: https://swe-agent.com
- Stars: 19,724 · Forks: 2,155 · Open issues: 26 · Watchers: 111
- Primary language: Python
- License: MIT
- Last pushed: 2026-07-07T15:57:40+00:00

## Categories

- [Evaluation & Observability](/categories/evaluation-observability.md)
- [AI Agents](/categories/ai-agents.md)

## Tags

agent-based-model, llm, cybersecurity, developer-tools

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## README (excerpt)

```text
<p align="center">
  <a href="https://swe-agent.com/latest/">
    <img src="assets/swe-agent-banner.png" alt="swe-agent.com" style="height: 7em" />
  </a>
</p>

<p align="center">
<a href="https://swe-agent.com/latest/"><img src="https://img.shields.io/badge/Docs-green?style=for-the-badge&logo=materialformkdocs&logoColor=white" alt="Docs"></a>
<a href="https://swe-bench.slack.com"><img src="https://img.shields.io/badge/Slack-4A154B?style=for-the-badge&logo=slack&logoColor=white" alt="Slack"></a>
<a href="https://arxiv.org/abs/2405.15793"><img src="https://img.shields.io/badge/arxiv-2405.15793-red?style=for-the-badge&logo=arxiv&logoColor=white&labelColor=black" alt="arxiv 2405.15793"></a>
</p>

<p align="center">
  <a href="https://github.com/SWE-agent/mini-swe-agent/">
    <img src="assets/warning.png" alt="mini-swe-agent.com" style="height: 7em" />
  </a>
</p>

> [!warning]
> Most of our current development effort is on [mini-swe-agent](https://github.com/SWE-agent/mini-swe-agent/),
> which has superseded SWE-agent. It matches the performance performance of SWE-agent, while being
> much simpler.
> See the [FAQ](https://mini-swe-agent.com/latest/faq/) for more details about the differences.
> Our general recommendation is to use mini-SWE-agent instead of SWE-agent going forward.


SWE-agent enables your language model of choice (e.g. GPT-4o or Claude Sonnet 4) to autonomously use tools to
[fix issues in real GitHub repositories](https://swe-agent.com/latest/usage/hello_world),
[find cybersecurity vulnerabilities](https://enigma-agent.com/), or
[perform any custom task](https://swe-agent.com/latest/usage/coding_challenges).

* ✅ **State of the art** on SWE-bench among open-source projects
* ✅ **Free-flowing & generalizable**: Leaves maximal agency to the LM
* ✅ **Configurable & fully documented**: Governed by a single `yaml` file
* ✅ **Made for research**: Simple & hackable by design

SWE-agent is built and maintained by researchers from Princeton University and Stanford University.

## 📣 News

* July 24: [Mini-SWE-Agent](https://github.com/SWE-agent/mini-SWE-agent) achieves 65% on SWE-bench verified in 100 lines of python!
* May 2: [SWE-agent-LM-32b](https://github.com/SWE-bench/SWE-smith) achieves open-weights SOTA on SWE-bench
* Feb 28: [SWE-agent 1.0 + Claude 3.7 is SoTA on SWE-Bench full](https://x.com/KLieret/status/1895487966409298067)
* Feb 25: [SWE-agent 1.0 + Claude 3.7 is SoTA on SWE-bench verified](https://x.com/KLieret/status/1894408819670733158)
* Feb 13: [Releasing SWE-agent 1.0: SoTA on SWE-bench light & tons of new features](https://x.com/KLieret/status/1890048205448220849)
* Dec 7: [An interview with the SWE-agent & SWE-bench team](https://www.youtube.com/watch?v=fcr8WzeEXyk)

## 🚀 Get started!

👉 Try SWE-agent in your browser:  ([more information](https://swe-agent.com/latest/installation/codespaces/))

Read our [documentation][docs] to learn more:

* [Installation](https://swe-agent.com/latest/installation/source/)
* [Hello world from the command line](https://swe-agent.com/latest/usage/hello_world/)
* [Benchmarking on SWE-bench](https://swe-agent.com/latest/usage/batch_mode/)
* [Frequently Asked Questions](https://swe-agent.com/latest/faq/)

[docs]: https://swe-agent.com

## SWE-agent for offensive cybersecurity (EnIGMA) <a name="enigma"></a>

<img src="https://github.com/user-attachments/assets/84599168-11a7-4776-8a49-33dbf0758bb2" height="80px"></img>

[SWE-agent: EnIGMA][enigma] is a mode for solving offensive cybersecurity (capture the flag) challenges.
EnIGMA achieves state-of-the-art results on multiple cybersecurity benchmarks (see [leaderboard](https://enigma-agent.com/#results)).
Please use [SWE-agent 0.7](https://github.com/SWE-agent/SWE-agent/tree/v0.7) while we update EnIGMA for 1.0.

[enigma]: https://enigma-agent.com
[SWE-bench]: https://github.com/SWE-bench/SWE-bench
[nyu-ctf]: https://arxiv.org/abs/2406.05590

In addition, you might be interested in our other projects:


<div align="cente
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/swe-agent-swe-agent`](/api/graphcanon/tools/swe-agent-swe-agent)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_