⚠️ PLEASE READ THIS ENTIRE FILE BEFORE GENERATING PROMPTS ⚠️

Prompt Assistant Skill

Help users generate, optimize, and adapt high-quality AI prompts for diverse use cases. This skill provides specialized templates for different scenarios, ensuring prompts are precise, structured, and effective.

Overview

This skill helps with:

•🎯 Prompt generation - Create effective prompts from scratch
•🔄 Prompt optimization - Refine existing prompts for better results
•📋 Template selection - Match the right template to the use case
•📊 Structured outputs - Parse data with consistent formatting
•🔪 Complex decomposition - Break down multi-step tasks
•📝 Markdown formatting - Generate well-structured markdown with sections, content, and diagrams

When to Use This Skill

Use for: ✅ Generating prompts for data parsing and extraction ✅ Creating multi-step instruction prompts ✅ Building prompts that require markdown structured output ✅ Optimizing prompts for better AI responses ✅ Adapting prompts for different tools/models ✅ Creating system prompts and role-based prompts

Don't use for: ❌ Direct task execution (use domain-specific skills instead) ❌ General conversation (not needed for simple questions) ❌ Content that violates policies

Core Concept: Scenario-Based Templates

This skill uses 4 primary template categories based on different use cases:

1️⃣ Data Parsing Template

Use when the user needs structured, consistent output from unstructured data.

Characteristics:

•Requires precise data extraction
•Output needs schema/format validation
•Often involves JSON, CSV, or table formats
•Example use cases: Invoice parsing, entity extraction, log analysis

Key prompt elements:

markdown

## Role & Context
Define the parser's expertise and context

## Input Specification
Describe the format of incoming data

## Output Schema
Specify exact output structure with examples

## Parsing Rules
- Rule 1: ...
- Rule 2: ...
- Rule 3: ...

## Error Handling
Instructions for ambiguous or invalid data

## Examples
- Example 1: [Input] → [Expected Output]
- Example 2: [Input] → [Expected Output]

2️⃣ Complex Task Decomposition Template

Use when the user needs step-by-step instructions for multi-part problems.

Characteristics:

•Large task with multiple phases
•Sequential dependencies between steps
•Requires intermediate validation
•Example use cases: Content creation, analysis, research planning

Key prompt elements:

markdown

## Objective
Clear, measurable end goal

## Phase Overview
High-level breakdown of major phases

## Detailed Steps
Phase 1: [Step 1a, 1b, 1c...]
Phase 2: [Step 2a, 2b, 2c...]
Phase 3: [Step 3a, 3b, 3c...]

## Success Criteria
How to validate each phase

## Key Considerations
Important context and constraints

## Fallback Options
Alternative approaches if something fails

3️⃣ Markdown Structured Output Template

Use when the user needs formatted markdown output with specific sections, hierarchy, and visual elements.

Characteristics:

•Output must be well-structured markdown
•Different section types (narrative, code, diagrams)
•Visual hierarchy and readability important
•Example use cases: Documentation, reports, educational content

Key prompt elements:

markdown

## Output Structure
Section 1: [Description]
Section 2: [Description]
Section 3: [Description]

## Formatting Rules
- Use H2 (##) for main sections
- Use H3 (###) for subsections
- Bold for emphasis: **term**
- Code blocks: \`\`\`language

## Visual Elements
- ✅ Use checkmarks for done items
- ❌ Use X for issues
- 📌 Use pins for important info
- 📊 Describe diagrams as Mermaid or ASCII

## Content Guidelines
- Write in [tone/style]
- Keep sections under [target length]
- Include [specific elements]

## Example Output
[Detailed example showing desired structure]

4️⃣ Prompt Optimization Template

Use when the user wants to improve an existing prompt.

Characteristics:

•Take user's existing prompt
•Identify weaknesses
•Propose improvements
•Validate with examples

Key analysis elements:

markdown

## Current Prompt Analysis
- Clarity: [Assessment]
- Completeness: [Assessment]
- Structure: [Assessment]
- Examples: [Assessment]
- Constraints: [Assessment]

## Identified Issues
1. Issue: [problem] → Impact: [effect]
2. Issue: [problem] → Impact: [effect]

## Optimization Recommendations
1. Clarify the objective
2. Add structured output format
3. Include more specific examples
4. Better error handling instructions

## Optimized Prompt
[Full improved prompt]

## Before/After Comparison
- Before: [snippet showing old approach]
- After: [snippet showing new approach]
- Expected improvement: [description]

Workflow: How to Use This Skill

Step 1: Understand User's Needs (Always ask questions first)

Before generating any prompt, ask the user:

code

💡 让我帮你创建完美的提示词！首先，我需要了解您的需求：

🎯 **任务目标：**
1. 您想要AI完成什么任务？
2. 输入数据或信息的格式是什么？
3. 您期望的输出是什么（格式、结构、长度）？

📊 **场景分类：**
4. 这个任务属于以下哪一类？
   - □ 数据解析（从文本/文件中提取结构化数据）
   - □ 复杂多步任务（多个阶段的工作流）
   - □ Markdown文档生成（需要格式化的结构化输出）
   - □ 优化现有提示词（我已有提示词想改进）

⚙️ **具体需求：**
5. 是否有特殊要求？
   - 输出格式要求？
   - 数据验证规则？
   - 错误处理方式？
   - 特定的示例或参考？

📋 **约束条件：**
6. 有什么限制条件吗？
   - Token预算（长度限制）？
   - 特定的格式标准？
   - 需要支持的语言或工具？

Step 2: Select Appropriate Template

Based on responses, recommend:

•✅ Data Parsing Template if task involves extraction, validation, structuring
•✅ Complex Decomposition if task has multiple dependent phases
•✅ Markdown Output if needs formatted, readable documentation
•✅ Optimization if improving existing prompt

Step 3: Generate Tailored Prompt

Create the prompt by:

•Starting with template structure
•Filling in user-specific details
•Adding examples from user's context
•Ensuring clarity and completeness

Step 4: Present as Markdown Block

Always present the generated prompt in a fenced markdown code block:

markdown

```
[Generated Prompt Here]
```

With clear sections:

•Purpose: What this prompt does
•When to use it: Best use cases
•How to adapt: Customization guidance
•The Prompt: The actual prompt text
•Example usage: Before/after or input/output examples

Step 5: Offer Refinement

After generating, always ask:

code

✨ **这个提示词可以如何改进？**

- 是否需要调整输出格式？
- 需要添加更多示例吗？
- 有特定的业务规则需要包含？
- 是否需要为不同工具改编？

Template Files Reference

See /templates directory for detailed templates:

•data-parsing-template.md - Structured data extraction
•complex-decomposition-template.md - Multi-step workflows
•markdown-output-template.md - Formatted documentation
•prompt-optimization-guide.md - Improving existing prompts
•role-based-system-prompt-template.md - System level prompts
•financial-rule-analysis-prompt.md - [新增] 财务规则集分析与输出（优化提示词）
•financial-rule-output-template.md - [新增] 财务规则集结构化输出模板
•financial-rule-output-example.md - [新增] 财务规则集输出示例

Reference Materials

See /reference directory for:

•best-practices.md - Prompt engineering best practices
•common-patterns.md - Proven prompt patterns
•anti-patterns.md - What to avoid
•tools-specific-prompts.md - Prompts optimized for specific AI tools

Best Practices for Generated Prompts

✅ DO:

• Start with clear role/context
• Define inputs explicitly
• Specify output format precisely
• Include 2-3 concrete examples
• Set constraints and boundaries
• Add fallback/error handling
• Use clear formatting and structure

❌ DON'T:

• Use vague language or unclear intent
• Assume the AI understands context
• Mix multiple unrelated tasks
• Forget to specify format requirements
• Leave edge cases undefined
• Write overly long prompts without structure
• Forget examples

Example Scenarios

Scenario 1: Data Parsing - Invoice Extraction

User: "I need to extract invoice data from PDFs" Recommended Template: Data Parsing Template Output: Prompt with schema for invoice fields, parsing rules, error handling

Scenario 2: Content Generation - Product Launch Blog

User: "I need a step-by-step guide for writing product launch content" Recommended Template: Complex Decomposition Template Output: Prompt with phases for research, outline, drafting, editing, publishing

Scenario 3: Documentation - API Reference Generator

User: "I need to generate API documentation in markdown with examples" Recommended Template: Markdown Structured Output Template Output: Prompt with markdown structure, formatting rules, example sections

Scenario 4: Improving a Prompt

User: "Here's my prompt but it's not giving good results" Recommended Template: Prompt Optimization Template Output: Analysis of issues, improvements, and the optimized prompt

Template Syntax Reference

When building prompts, use these consistent elements:

markdown

## [Section Title]
Description of what goes here

### [Subsection]
More specific details

**Bold text:** For key terms
`code`: For variables or commands
- Bullet: For lists
- More items:

> Quote: For important notes or examples

Support and Customization

For Tool-Specific Prompts

If user needs prompts for specific models (Claude, GPT, Gemini, etc.), ensure:

•Prompt syntax matches tool requirements
•Any tool-specific features are leveraged
•Output format is compatible

For Multiple Languages

If user requests prompts in non-English:

•Generate prompt in requested language
•Maintain same structure and clarity
•Note any language-specific patterns

For Integration/API Usage

If prompt will be used in code/automation:

•Make variables clear: {variable_name}
•Specify placeholder format
•Include usage example