SWE-agent enables language models to autonomously resolve GitHub issues, find cybersecurity vulnerabilities, and perform custom tasks using external language models such as GPT-4o or Claude Sonnet 4. Current development has shifted to mini-SWE-agent, which the project recommends using instead.
Project overview
The project enables language models to autonomously use tools to fix issues in real GitHub repositories and has reported state-of-the-art results on SWE-bench.
Project type
AI Agent
Deployment
Refer to project documentation
License
MIT
Best for
Researchers and developers who need a configurable, hackable agent to autonomously resolve GitHub issues or custom tasks using an external language model.
Users investigating state-of-the-art SWE-bench performance approaches for autonomous issue fixing.
Key capabilities
Takes a GitHub issue and tries to automatically fix it using the language model of choice.
Can be employed to perform any custom task, such as competitive coding challenges.
Provides a mode for solving offensive cybersecurity capture the flag challenges.
Limitations and risks
Most current development effort is on mini-SWE-agent, which has superseded SWE-agent. The general recommendation is to use mini-SWE-agent.
There is no documented decision regarding data boundaries, telemetry, or cost dependencies.
Requires a language model of choice, such as GPT-4o or Claude Sonnet 4, meaning inference may depend on external services.
Getting started
The source provides links to installation and Codespaces but specific steps are not detailed; the first success path is not documented.
Alternatives and comparisons
Provides an agentic skills framework and software development methodology enforcing test-driven and subagent-driven development for coding agents.
A complete system providing skills, memory optimization, and continuous learning across multiple AI agent harnesses.
Small, composable, and adaptable engineering skills for AI coding agents that enforce software engineering fundamentals like test-driven development.