| name | how-to-write-prompts-claude-engineer |
| description | Anthropic engineers' best practices for prompt writing. Use when improving prompts, teaching prompt engineering, or understanding model interaction. Trigger phrases: "Claude工程师", "提示词技巧", "不要角色扮演", "实话实说" |
How to Write Prompts - Claude Engineer Insights
Overview
Anthropic prompt engineers' key principles: clear communication, iteration, honesty with models, no unnecessary role-play.
Core Principles
1. Clear Communication
- Write very clear task descriptions, not abstract constructs
- Articulate clearly so model understands the task
- Organize everything you know but model doesn't, then write it down
2. Iteration
- Prompt engineering = trial and error process
- Willingness to iterate and observe is critical
- Test edge cases: empty input, unusual data, boundary conditions
- When model errs: ask "Why did you get this wrong? Can you help fix my prompt?"
3. No Role-Play Needed
- As models improve, no need to lie to them
- Don't pretend "I'm a teacher giving a quiz" - say "I'm building an LLM evaluation dataset"
- Imagine a capable temp worker with little context - describe your task directly
- Record yourself explaining the task, transcribe, paste into prompt - often works better
4. Trust Model Capability
- Don't treat model like a child; don't over-simplify
- Models can understand complex information
- Give papers directly instead of simplified "baby version"
- Respect model's ability to handle context
5. When to Give Up
- Some tasks: every adjustment pushes result further from goal → abandon
- Better to wait for next model than spend months on unsolvable prompt
Research vs Consumer Prompts
- Research: Fewer examples, seek diversity, explore model boundaries
- Consumer: Many examples, prioritize stability and consistency
- Enterprise: Must handle millions of uses, consider all edge cases
Usage Example
User input: "我的提示词效果不好，怎么改进？"
AI action: Applies principles - clarify task, test edge cases, try transcribing verbal explanation, avoid role-play shortcuts
Expected result: Improved prompt with clear task description and edge case handling
