SWE-agent

// Overview

SWE-agent is an open-source coding agent from researchers at Princeton and Stanford. You give it a GitHub issue and the language model of your choice, such as Claude Sonnet 4 or GPT-4o, and it works through the problem on its own: it reads files, edits code, and runs tests inside a real repository until it produces a fix.

The project is built around a single YAML configuration file, which makes its behavior easy to read, change, and reproduce. It was designed for research, so it is meant to be simple and hackable. The same agent can also tackle general coding challenges or, in its EnIGMA mode, hunt for cybersecurity vulnerabilities.

The maintainers note that most active development has moved to mini-swe-agent, a much simpler successor that matches SWE-agent's performance. SWE-agent itself remains available and is state of the art on the SWE-bench benchmark among open-source projects.

// What it does

• Takes a GitHub issue and tries to fix it automatically, editing and testing code in the real repository
• Works with the language model of your choice, including Claude Sonnet 4 and GPT-4o
• Governed by a single YAML file, so the agent's behavior is fully documented and reproducible
• State of the art on SWE-bench among open-source projects
• EnIGMA mode for offensive cybersecurity and capture-the-flag challenges
• Simple and hackable by design, built for research and easy customization

// Getting started

Install SWE-agent from source, set the API key for your chosen model, then run it against a GitHub issue. You can also try it instantly in GitHub Codespaces from the repo.

git clone https://github.com/SWE-agent/SWE-agent.git

python -m pip install --upgrade pip && pip install --editable .

sweagent --help

sweagent run \
  --agent.model.name=claude-sonnet-4-20250514 \
  --agent.model.per_instance_cost_limit=2.00 \
  --env.repo.github_url=https://github.com/SWE-agent/test-repo \
  --problem_statement.github_url=https://github.com/SWE-agent/test-repo/issues/1

Commands and code are distilled from the project's own documentation — always check the official repo for the latest.

// When to use it

• Automatically fixing issues in a real GitHub repository by letting an LLM edit and test the code
• Solving general coding challenges or custom programming tasks with an autonomous agent
• Finding cybersecurity vulnerabilities and solving capture-the-flag challenges through EnIGMA mode
• Benchmarking and researching LLM coding agents, for example on SWE-bench

// How SWE-agent compares

SWE-agent alongside other open-source autonomous coding agents tools AI/TLDR tracks, ranked by GitHub stars.