ai-prompt-optimization（ai 提示优化）

AI Prompt Optimization

Core Capabilities

When users seek prompt optimization assistance, provide the following services:

1. Diagnosis & Optimization - Analyze existing prompt issues and provide specific improvement plans
2. Template Generation - Generate structured prompt templates for different scenarios
3. Few-Shot Generation - Create example-driven few-shot prompts
4. Chain-of-Thought Guidance - Design CoT (Chain of Thought) prompts

Usage

1. Diagnosis & Optimization Workflow

When a user provides a prompt for optimization:

Analyze Structure → Identify Issues → Provide Improved Version → Explain Changes

Diagnosis Checklist:

• [ ] Is the role/identity clearly defined?
• [ ] Is the task objective specific and clear?
• [ ] Are output format/style constrained?
• [ ] Is the necessary context/background information provided?
• [ ] Are boundary conditions and exceptions specified?
• [ ] Are there clear success criteria?

2. Template Generation

Generate structured templates based on user scenarios. Core template format:

# Role Definition
You are a [role] in [professional domain], skilled at [core competency].

# Task Description
Please help me [specific task], with the goal of [expected outcome].

# Context Information
- Background: [relevant background]
- Audience: [target users]
- Constraints: [boundary conditions]

# Output Requirements
- Format: [desired format]
- Style: [language style]
- Length: [length requirement]

# Quality Standards
[Key metrics for evaluating output]

3. Few-Shot Example Generation

Generate few-shot examples for complex tasks:

1. Select Representative Samples - 3-5 examples covering different variants
2. Format Examples - Input → Output structure
3. Add Explanations - Explain the rationale for selecting each example

4. Chain-of-Thought Design

Design CoT prompts for tasks requiring reasoning:

Before giving your final answer, please think through the following steps:
1. [Understand the Problem] - ...
2. [Decompose the Problem] - ...
3. [Step-by-Step Reasoning] - ...
4. [Verify the Conclusion] - ...

Scenario Reference

For complete scenario templates and examples, see references/templates.md:

• Writing assistance prompts
• Code generation prompts
• Image generation prompts
• Data analysis prompts
• Q&A and consultation prompts

Optimization Principles

1. Specific > Vague - Clearly specify what is wanted and what is not
2. Structured > Scattered - Use clear segmentation and markers
3. Constrained > Free - Appropriate constraints improve output quality
4. Iterative > One-Shot - Encourage users to continuously optimize based on output