SWE-agent

SWE-agent hands a language model a set of tools and lets it work. Point it at a real GitHub repository and it attempts the issue on its own, and the same machinery has been aimed at offensive cybersecurity challenges and at arbitrary custom tasks.

The project comes from researchers at Princeton University and Stanford University, and the design reflects that. Behavior is governed by one YAML file rather than scattered code, the agent is left maximal agency instead of being railroaded down a fixed script, and the codebase stays simple and hackable so an experiment is cheap to run.

Several points matter before you pick it up.

• Superseded by a smaller sibling: most development effort has moved to mini-swe-agent, which matches the performance while being much simpler, and the maintainers recommend it going forward.
• Model agnostic: bring the model you prefer, with GPT-4o and Claude Sonnet 4 named as examples.
• Benchmark record: it holds state of the art results on SWE-bench among open source projects.
• EnIGMA mode: an offensive security mode solves capture the flag challenges, currently requiring version 0.7 while it is brought up to date.
• Try it first: a Codespaces launch runs the agent in your browser with no local installation.

Documentation covers installation from source, a command line hello world and batch mode for benchmarking against SWE-bench. Given the maintainers' own advice, treat this repository as the research reference and the fuller feature set, and reach for the smaller agent when you simply want results.