Provide comprehensive feedback on copilot custom instructions

[Copilot]

This PR provides detailed analysis and recommendations for improving the .github/copilot-instructions.md file based on:

1. Repository context analysis - Understanding AC Training Lab as an autonomous laboratory equipment control system
2. Latest GitHub/VS Code best practices (2024-2025) for Copilot custom instructions
3. Hardware integration and IoT development requirements for AI coding assistants
4. Current codebase patterns and practices examination

Key Findings

Critical Safety Issue ⚠️

The current instruction to "avoid defensive error handling for hypothetical failures" is dangerous for hardware control systems. Hardware operations controlling robotic arms, 3D printers, and laboratory equipment require robust error handling to prevent equipment damage and ensure safety.

Missing Elements (70% of GitHub Best Practices)

• No project context - Users don't understand this controls autonomous lab equipment
• No development workflow - Missing build/test/lint commands (tox, pre-commit)
• No repository structure guide - 20+ device modules in src/ac_training_lab/ unexplained
• No domain-specific patterns - Missing MQTT, hardware integration, scientific Python guidance

Recommendations

What Should Be KEPT ✅

• Minimal implementation approach for rapid prototyping
• MCP tool integration guidelines
• Communication clarity principles
• Prioritizing official documentation

What Should Be MODIFIED 🔧

• Error handling philosophy: Distinguish hardware operations (require error handling) from pure computational functions (minimal OK)
• Add project overview: Explain autonomous laboratory equipment domain
• Add development workflow: Include tox, pre-commit, device testing patterns

What Should Be ADDED 📈

• Hardware integration patterns: MQTT command/response, safety protocols, connection retry logic
• Repository structure: PyScaffold layout, device module organization
• Scientific data handling: NumPy patterns, metadata requirements, reproducibility

Research Sources

• GitHub's official best practices
• Latest VS Code Copilot agent mode documentation
• Hardware integration and IoT development best practices
• Scientific Python and laboratory automation patterns

Impact

Current instructions miss critical safety considerations and modern best practices. The recommendations align with GitHub's 2024-2025 standards while addressing the unique requirements of autonomous laboratory equipment control.

Detailed analysis and improved instructions provided in the PR discussion for implementation reference.

Fixes #413.

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[sgbaird]

This was pretty good. Nice!