SWE-agent

SWE-agent

SWE-agent is a research framework that enables large language models (LLMs) like GPT-4o or Claude Sonnet to autonomously interact with codebases, fix GitHub issues, and perform complex software engineering tasks. It provides a configurable, tool-using agent environment built by researchers at Princeton and Stanford. The tool is designed for maximum agent autonomy and is highly hackable. It's configured via a single YAML file and supports adding custom tools. While it's state-of-the-art on the SWE-bench benchmark, the project is now in maintenance mode, with development focused on its successor, mini-swe-agent.

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Added on
Sep 16, 2026
Open-sourceSWE-bench SOTAGitHub integrationYAML configResearch-focused
Product information

Everything worth knowing about SWE-agent

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Autonomous GitHub Issue Fixing
Enables an LLM to autonomously use tools to fix issues in real GitHub repositories.
Multi-Tool Execution
Provides the agent with a set of tools (like file editing, searching) to interact with the codebase.
Model Agnostic
Works with your language model of choice (e.g., GPT-4o, Claude Sonnet 4).
Configurable via YAML
The entire agent setup is governed by a single YAML configuration file.
Technical capabilities
Custom Tool Integration
Allows adding your own custom tools for the agent to use.
Trajectory Inspection
Includes a trajectory inspector to debug and analyze agent actions.
Must watch videos
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AI Agent Automatically Codes WITH TOOLS - SWE-Agent Tutorial ("Devin Clone")
13:59
Tutorial13:59
AI Agent Automatically Codes WITH TOOLS - SWE-Agent Tutorial ("Devin Clone")
SWE-Agent is an open-source, fully autonomous coding agent that can solve GitHub issues. It scores almost as high as Devin in the coding benchmark. Here's a full review and tutorial. Be sure to check out Pinecone for all your Vector DB needs: https://www.pinecone.io/ Join My Newsletter for Regular AI Updates 👇🏼 https://www.matthewberman.com Need AI Consulting? ✅ https://forwardfuture.ai/ My Links 🔗 👉🏻 Subscribe: https://www.youtube.com/@matthew_berman 👉🏻 Twitter: https://twitter.com/matthewberman 👉🏻 Discord: https://discord.gg/xxysSXBxFW 👉🏻 Patreon: https://patreon.com/MatthewBerman Rent a GPU (MassedCompute) 🚀 https://bit.ly/matthew-berman-youtube USE CODE "MatthewBerman" for 50% discount Media/Sponsorship Inquiries 📈 https://bit.ly/44TC45V Links: Github: https://github.com/princeton-nlp/SWE-agent Website: https://swe-agent.com/ Chapters: 0:00 - SWE-Agent 3:41 - Tutorial 7:41 - Demo 1 11:20 - Demo 2
A First Look at SWE-agent
2:19
Tutorial2:19
A First Look at SWE-agent
swe-agent.com

Who uses it

Real use cases, no hype
Automated GitHub Issue Resolution
Autonomously fix bugs and issues in real-world GitHub repositories.
SWE-bench Competitive Benchmarking
Run and optimize models against the standard SWE-bench evaluation suite.
Codebase Refactoring & Debugging
Analyze and modify complex codebases to resolve technical debt or errors.
Custom AI Agent Tooling Research
Experiment with and develop new AI agent tool interfaces and architectures.
Security Vulnerability Hunting
Scan code for and identify potential cybersecurity vulnerabilities.
Batch Processing Coding Challenges
Solve multiple, independent coding problems in an automated batch run.
Vision-Aided Code Task Execution
Use multimodal models to interpret issue screenshots and modify code accordingly.
What's great
  • State-of-the-art performance on SWE-bench for open-source projects.
  • Free-flowing and generalizable design, giving the language model maximum agency.
  • Highly configurable and fully documented with a single YAML config file.
  • Built for research—simple and hackable codebase.
  • Active research community from top institutions (Princeton, Stanford).
Technical strengths
  • Supports multimodal inputs for vision-capable models.
  • Tool bundle architecture for custom, environment-specific tool definitions.
Where it falls short
  • Officially superseded; now in maintenance-only mode.
  • More complex than its recommended successor, mini-swe-agent.
  • Documentation can be sparse or error-prone (e.g., 404 FAQ page).
  • Requires specific model API keys and environment setup.
  • Core value is in solving SWE-bench; may be overkill for simpler tasks.
Technical limitations
  • Heavy dependency on specific LLM providers for top performance.
  • Action parser and history processor systems add configuration complexity.
For technical folks

The deep-dive specs

Architecture
Agent-based system with configurable tools and actions
Primary Benchmark
SWE-bench
Core Component
Action Cycle Interface (ACI)

FAQ

Includes technical Q&A
You should almost certainly use mini-swe-agent. It matches SWE-agent's performance but is much simpler and more flexible. SWE-agent is now in maintenance-only mode.

Traffic Insights

Monthly Visits

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October 2026

Growth Rate

0%

vs last month

Dominance

0%

in Coding

Top Country

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Top Countries Breakdown

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Growth Trend

Stable

Traffic has remained stable.

Pricing overview
Unknown Pricing

SWE-agent Pricing

SWE-agent uses a unknown pricing structure. Real-time rates, custom enterprise quotas, and plan details are managed directly on their official platform.

Check Pricing on SWE-agent
Reviews

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