Official description2 sourcesyesterday
AutoPR
AI-generated pull requests agent that fixes issues
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Official description7e82-489e-905e-6ad79005adcb" /> AutoPR <video src="user-images.githubusercontent.com AutoPR autonomously wrote pull requests in response to issues.
- Source
- collected from the e2b-dev/awesome-ai-agents list · type: open-source project
- Harvest history
- first seen 2026-10-16 · last seen 2026-10-16 · seen 3× · listed by 2 sources
- Score
- score 203 · 2 sources · repo
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We have no tags recorded for it yet.
Who maintains it?
first catalogued 2026-10-16；last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
Third-party quality signals
🌳 AutoPR 🌳
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
AutoPR autonomously wrote pull requests in response to issues.
Built with Guardrails.
What is this?
A vision of user experience I had in March of 2023, back when OpenAI had just launched its first "ChatGPT API".
As far as I am aware, AutoPR was the first bot to autonomously generate pull requests in response to issues.
Like most demos back in the day, it worked about 20% of the time.
What inspired the initial weekend coding sprint was Guardrails,
who were prompting LLMs to generate structured data with JSON Schemas, and reasking it when it did not adhere.
This was a time before grammar-powered structured data generation.
Enjoy this brief glimpse into the past. 🜂
💪 How did it work?
Triggered by adding a label containing AutoPR to an issue, AutoPR would:
1. Plan a fix
2. Write the code
3. Push a branch
4. Open a pull request
💎 Examples
Well-written issues often lead to better results.
- Create a dice rolling bot
- Create a 'Tech Jargon Generator'
- Create a user-friendly weather app
- Write three programming interview challenges
- Replace GPT2FastTokenizer with tiktoken
🤞 Limitations
This GitHub Action was **in development**, and in **alpha release**.
It still:
- Incorrectly referenced code in other files
- Duplicated lines
- Called functions that don't exist
- Only worked on GitHub (see #46)
🔨 Usage
Please see USAGE.md for more information.
📝 Contributing
Please see CONTRIBUTING.md for more information.
Built with Guardrails.
What is this?
A vision of user experience I had in March of 2023, back when OpenAI had just launched its first "ChatGPT API".
As far as I am aware, AutoPR was the first bot to autonomously generate pull requests in response to issues.
Like most demos back in the day, it worked about 20% of the time.
What inspired the initial weekend coding sprint was Guardrails,
who were prompting LLMs to generate structured data with JSON Schemas, and reasking it when it did not adhere.
This was a time before grammar-powered structured data generation.
Enjoy this brief glimpse into the past. 🜂
💪 How did it work?
Triggered by adding a label containing AutoPR to an issue, AutoPR would:
1. Plan a fix
2. Write the code
3. Push a branch
4. Open a pull request
💎 Examples
Well-written issues often lead to better results.
- Create a dice rolling bot
- Create a 'Tech Jargon Generator'
- Create a user-friendly weather app
- Write three programming interview challenges
- Replace GPT2FastTokenizer with tiktoken
🤞 Limitations
This GitHub Action was **in development**, and in **alpha release**.
It still:
- Incorrectly referenced code in other files
- Duplicated lines
- Called functions that don't exist
- Only worked on GitHub (see #46)
🔨 Usage
Please see USAGE.md for more information.
📝 Contributing
Please see CONTRIBUTING.md for more information.
- Source
- awesome · https://github.com/irgolic/AutoPR
- added
- yesterday