Create, optimize, and debug high-performing prompts for Claude 4 models with production-ready templates and evidence-based techniques. Use this skill when the user asks to create a prompt, write a prompt, improve a prompt, build a prompt chain, design a system prompt, or needs prompt engineering guidance. Also handles prompt refinement and follow-up modifications.
This skill is limited to using the following tools:
examples/optimization-report.mdexamples/prompt-chain-template.mdexamples/system-prompt-template.mdreferences/claude-4-guide.mdreferences/prompt-patterns.mdreferences/techniques-detailed.mdExpert prompt engineering service for Claude 4 models. Transform requirements into high-performing, production-ready prompts through evidence-based techniques and systematic optimization.
Create, optimize, and debug prompts by:
Deliverable: The output is always a prompt artifact—a ready-to-use prompt that users copy and use elsewhere. Never execute what the prompt describes; only deliver the prompt itself.
Before generating the prompt, understand its intended purpose. Gather information about what the prompt should accomplish—not implementation details of the subject matter it addresses.
Required clarifications about the prompt:
Clarify prompt ambiguities (stay at the prompt level, don't dive into subject matter):
When the user is modifying a prompt that was previously generated in this conversation:
Detection signals:
Streamlined workflow:
Select appropriate techniques based on task complexity:
For simple tasks:
For complex tasks:
For optimization:
Deliver prompts as ready-to-copy markdown blocks optimized for the target platform.
Default (Claude Web / Claude Desktop):
API format (only when explicitly requested):
<instructions>, <context>, <examples><thinking>, <answer>, <analysis><thinking> and <answer> tags<examples> tags with nested <example> tags{ for JSONClaude 4 models require explicit instruction for enhanced behaviors:
Request thoroughness explicitly:
Include as many relevant features and interactions as possible.
Go beyond the basics to create a fully-featured implementation.
Provide context for instructions:
Your response will be read aloud by a text-to-speech engine,
so never use ellipses since the engine won't know how to pronounce them.
Anti-reward-hacking for coding:
Write a high quality, general purpose solution. Do not hard-code
test cases. If the task is unreasonable, tell me rather than
creating a workaround.
Leverage thinking capabilities:
After receiving tool results, carefully reflect on their quality
and determine optimal next steps before proceeding.
Deliver all prompts using this structure:
# [Prompt Title]
## Purpose
[Clear description of what this prompt accomplishes]
## Best Used For
[Specific scenarios and use cases]
## Prompt
[Complete, ready-to-copy prompt in code block]
## Usage Notes
- Target model: [Claude Opus 4 / Sonnet 4 / Haiku]
- [Platform-specific notes if applicable]
## Testing Guide
[How to validate the prompt works correctly with example inputs]
For refinements, add after ## Prompt:
## Changes Made
- [What was modified and the rationale]
- [Key differences from previous version]
For prompt chains, add:
## Chain Overview
### Step 1: [Purpose]
[Prompt with clear output format]
### Step 2: [Purpose]
[Prompt consuming Step 1 output]
## Integration Notes
[How to connect the chain in practice]
Before delivering any prompt, verify:
Use the AskUserQuestion tool when:
Example clarification:
Before I create this prompt, I have a few questions:
- Should this prompt handle [specific edge case]?
- Do you want the output in [format A] or [format B]?
- Would you like me to provide alternative variations?
Consult for detailed techniques and patterns:
references/techniques-detailed.md - Comprehensive prompting techniquesreferences/claude-4-guide.md - Claude 4 specific optimizationsreferences/prompt-patterns.md - Reusable prompt templates and patternsexamples/system-prompt-template.md - Production-ready system promptexamples/prompt-chain-template.md - Multi-step workflow templateexamples/optimization-report.md - Prompt improvement documentationPrompt engineering succeeds when: