Add AI agent instructions for Checkbox development#2298
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zyga wants to merge 2 commits intocanonical:mainfrom
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Add AI agent instructions for Checkbox development#2298zyga wants to merge 2 commits intocanonical:mainfrom
zyga wants to merge 2 commits intocanonical:mainfrom
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Add .github/copilot-instructions.md with comprehensive guidance for AI coding agents working on Checkbox. The instructions cover: - Big picture architecture (checkbox-ng core, providers, packaging) - Provider anatomy and structure (manage.py, bin/, units/, tests/) - Developer workflows (venv setup, provider build/test/validate) - Project conventions (Black formatting, setuptools_scm, signed commits) - Provider code style rules from providers/README.md: - Python: pathlib, .format(), subprocess, argparse, avoid regexes - PXU: avoid nested bash, declare env vars, no Jinja templates - Dependencies: strict avoidance (Ubuntu 18.04+ ESM compatibility) - Integration points (pyproject.toml, manage.py, tox.ini) - Copyable examples for common development tasks This provides AI agents with project-specific knowledge to be immediately productive and follow Checkbox conventions.
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Pull request overview
This PR adds comprehensive AI agent instructions in .github/copilot-instructions.md to help AI coding assistants understand Checkbox project structure, conventions, and development workflows. The instructions provide guidance on architecture, provider development, testing, code style rules, and common development tasks.
Changes:
- Added
.github/copilot-instructions.mdwith project-specific guidance for AI agents - Covers architecture (checkbox-ng, providers, packaging), developer workflows, testing, conventions, and copyable examples
- References existing documentation sources (CONTRIBUTING.md, providers/README.md) for detailed guidelines
💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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Add .github/copilot-instructions.md with comprehensive guidance for AI coding agents working on Checkbox. The instructions cover:
This provides AI agents with project-specific knowledge to be immediately productive and follow Checkbox conventions.
Description
Resolved issues
Documentation
Tests