This project uses an AI-first development workflow. Most features, bug fixes, and improvements are implemented through AI coding agents (Claude Code, GitHub Copilot, OpenAI Codex) working from structured issue descriptions.
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Issues are the starting point — Every task begins as a GitHub issue with a structured format: an overview, a human-readable plan, a detailed implementation plan (in a collapsible block), and optionally the original prompt that generated the issue.
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AI agents pick up issues — Issues can be assigned to AI coding agents (e.g. GitHub Copilot) which read the issue description,
AGENTS.md, andCLAUDE.mdfor context, then implement the changes autonomously. -
Human review — All AI-generated pull requests are reviewed by maintainers before merging.
When opening an issue, please use the provided issue templates. The Feature / Task Request template follows our standard format:
- Overview — What and why, in 2-4 sentences
- Plan — High-level bullet points (human-readable)
- Detailed implementation plan — File paths, steps, key files (in a collapsible block)
- Original Prompt — If you used an AI to help draft the issue, include the original prompt
If your feature involves a specific calculation, algorithm, or small piece of functionality — include example code. Even a rough script, a working prototype, or a snippet showing the existing behaviour you want to change makes a huge difference. Code examples give AI agents and human contributors concrete context to work from, and dramatically reduce misunderstandings about what you're asking for.
This structure ensures that both human contributors and AI agents can understand and act on the issue effectively.
Traditional contributions are equally welcome! If you prefer to work without AI tools, simply follow the development setup and pull request guidelines below. The issue templates are helpful for any contributor, AI or human.
Contributions are welcome and greatly appreciated!
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Install from source:
pip install -e ".[dev]" -
Create a feature branch:
git checkout -b feature/name-of-your-branch -
Make your changes and run tests:
python -m pytest test_autoarray/ -
Commit, push, and submit a pull request.
- The pull request should include tests for new functionality.
- If the pull request adds functionality, update docs accordingly.
- If changing public API, clearly document what changed — downstream packages depend on this.