
mini-swe-agent
The 100-line AI agent that solves GitHub issues and assists in your command line.
Quick Answer
AImini-SWE-agent is an open-source AI agent framework for researchers and developers building baseline AI systems. It achieves high performance on SWE-bench, solving GitHub issues and automating command-line tasks. Best for teams doing fine-tuning or reinforcement learning on agent scaffolds. Open-source.
mini-SWE-agent is an open-source AI agent framework built by Princeton and Stanford, designed to solve GitHub issues and assist with command-line tasks. It features a minimal Python codebase, high performance on SWE-bench, and supports various local and containerized environments. The agent is open-source and compatible with many LLM backends via LiteLLM, OpenRouter, and Portkey.
mini-SWE-agent is radically simpler than other agents, including its predecessor SWE-agent, by relying solely on bash for tool use and maintaining a completely linear history for debugging and fine-tuning. This minimal design allows it to run with virtually any language model and execute actions independently in sandboxed environments.
Decision Intelligence
Best For
AIType
Starting Price
$0/mo
Free Trial
No
Credit Card
Not Required
Free Plan
Yes
Dimension Scores
· 4.9 avgHow good it is, across universal quality axes
Task Scores
· 5.1 avgWhat it can do, per category it works in · showing 6 of 9 tasks scoring 5+
Scores are AI-estimated from publicly available data — not an independent test or a verified user rating. How we rank →
- -Does not have any tools other than bash
- -Does not use the tool-calling interface of LLMs
- -Requires Python knowledge for advanced customization

Open-source autonomous agent for GitHub issues & coding challenges
Supports all models via LiteLLM
Supports all models via OpenRouter
Supports all models via Portkey
Auto-updated
Complexity
Company Size
Team Size
Skill Level
Deployment
The Model(s) Behind It
Model details — extracted from public vendor sources by our pipeline (AI extraction plus a source check) or admin-entered. Shown as claimed by the vendor; not independently audited by Intelloro.
Underlying Model Benchmarks
Third-party leaderboard scores for the AI model(s) powering this — including price & speed. These describe the underlying model, not the product's own metrics.
llm-coding
Best submission: "Claude 4.5 Opus (high)" (2026-02-17)
Scores from official leaderboards or vendor-reported. Percentile is cross-benchmark normalized when populated by an aggregator. See methodology.
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User Reviews
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Who It's For4 rolesSoftware DevelopersComputer ProgrammersWeb Developers+1 more
Platform, Content & Languages2 content types1 languagesCodeTextEnglish+4 more
Content Types
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Frequently Asked Questions
What can mini-swe-agent do?
mini-swe-agent can: Minimal 100-line Python codebase, Bash-only tool execution, Linear history for debugging and fine-tuning, Independent action execution via subprocess.run. Best for: Researchers building baseline AI agent systems.
How much does mini-swe-agent cost?
mini-swe-agent is open source and free to self-host. Cloud hosting options may have separate pricing.
Is mini-swe-agent free?
Yes, mini-swe-agent is open source and free to self-host. Managed hosting may carry separate costs.
What makes mini-swe-agent unique?
mini-SWE-agent is radically simpler than other agents, including its predecessor SWE-agent, by relying solely on bash for tool use and maintaining a completely linear history for debugging and fine-tuning. This minimal design allows it to run with virtually any language model and execute actions independently in sandboxed environments.
Does mini-swe-agent have an API?
Yes, mini-swe-agent offers a public API for developers to integrate its capabilities into custom applications and workflows.
What platforms does mini-swe-agent support?
mini-swe-agent is available on CLI and API.
What languages does mini-swe-agent support?
mini-swe-agent supports English.
Who is mini-swe-agent for?
mini-swe-agent is designed for Researchers building baseline AI agent systems; Developers seeking a simple and hackable coding agent; Teams doing fine-tuning or reinforcement learning on agent scaffolds.
Trust Score
Good
Based on 7 data signals
Confidence: High
Reflects publicly available data, not an independent audit
No published data
Not yet checked
Some details are AI-generated estimates — verify with the vendor.
AI-generated estimate: Best For, Description, Limitations, Quick Answer, Tagline, What Makes Unique
How we source dataAI Governance & Regulatory Disclosures
Legally-sensitive fields — extracted from public vendor sources by our pipeline (AI extraction plus a source check) or admin-entered. Shown as claimed by the vendor; not independently audited by Intelloro.
