…nstruction

- Add 868-line comprehensive instruction file covering prompt engineering fundamentals
- Include safety frameworks, bias mitigation, security best practices, and responsible AI usage
- Provide detailed templates, checklists, and testing methodologies
- Cover anti-patterns, prompt injection prevention, and ethical considerations
- Add educational content on prompt patterns, validation techniques, and documentation
- Include practical examples and real-world scenarios for developers
- Rename file to avoid conflict with existing prompt-engineer chat mode
- Update README with new instruction file

This instruction provides developers with industry-standard best practices for creating safe, effective, and responsible AI prompts for Copilot and other LLMs.

- Restore the original prompt-engineer.chatmode.md from upstream/main
- Remove overwritten comprehensive version to avoid duplication and conflict
- Ensure only the official, simple prompt engineer chat mode is present

All advanced prompt engineering best practices are now in the new instruction file only.

…t mode

- Re-run update-readme.js to ensure only the correct, original description for prompt-engineer.chatmode.md is present
- Remove any duplicate or outdated descriptions from previous comprehensive version
- README is now fully in sync with the restored chat mode and current repo state

- Add 150+ line prompt file for AI prompt engineering safety review and improvement
- Include systematic analysis framework covering safety, bias, security, and effectiveness
- Provide structured output format with detailed assessment criteria
- Include safety guidelines, testing recommendations, and educational insights
- Complement the existing AI prompt engineering safety best practices instruction
- Follow repository guidelines and best practices for prompt creation

This prompt enables developers to systematically review and improve prompts for safety, bias mitigation, security, and responsible AI usage.

…nsive analysis

- Expand prompt from basic to comprehensive 200+ line analysis framework
- Add advanced pattern analysis covering zero-shot, few-shot, chain-of-thought, role-based patterns
- Include technical robustness assessment (input validation, error handling, scalability)
- Add performance optimization metrics (token efficiency, response quality, consistency)
- Enhance output format with detailed scoring and assessment criteria
- Include bias mitigation strategies, security enhancements, and technical improvements
- Provide extensive testing recommendations and educational insights
- Follow repository guidelines for comprehensive, actionable prompt content

This expanded prompt provides developers with a thorough, systematic approach to prompt safety review and improvement.