SWE-Agent

An open-source AI tool that transforms large language models into software engineering agents capable of autonomously resolving issues in real GitHub reposit...

4.8 (4)

Перевірено Daniel Nikulshyn·Оновлено травень 2026 р.

GitHub Integration AI Agent Automation Open Source Software Engineering LLM Developer Tools

Огляд

SWE-Agent — An open-source AI tool that transforms large language models into software engineering agents capable of autonomously resolving issues in real GitHub reposit...

Кейси використання

Autonomous GitHub Issue Resolution

Deploy SWE-Agent to automatically analyze and resolve open issues in GitHub repositories, reducing manual triage and debugging effort for maintainers.

LLM-Powered Code Fixes

Transform large language models into software engineering agents that can navigate codebases, propose patches, and submit fixes without constant human guidance.

Open-Source Agent Research

Use SWE-Agent as a foundation for experimenting with agentic AI workflows in software engineering tasks and benchmarking LLM coding capabilities.

Відгуки

4.8

Середнє з 4 оцінок.

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Wei Chen

Solid for our team

We rolled this out across the team last quarter and support is responsive. The API fits neatly into how we already work, and the onboarding removed a step we used to do by hand. A few rough edges remain, which is the main caveat, but it has held up under daily use.

Sanjay Gupta

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on the integrations, and it is genuinely easy to set up caught me off guard. still, I'd recommend giving it a real trial.

Hiroshi Tanaka

Use it every day

Honestly didn't expect to like it this much. The integrations is exactly what I needed, and it saves real time. but I reach for it almost every day now and it just clicks.

Yuki Mori

Compared a few options

Evaluated this against two competitors. Where it wins: the onboarding and the value for money is strong. On balance the feature set — especially the API — justifies the 5 stars for our use case.