Prompt Optimizer
Transform vague, underperforming prompts into precise, structured prompts that consistently produce high-quality AI outputs.
by 371166758-qq · published 2026-04-01
$ claw add gh:371166758-qq/371166758-qq-qf-prompt-optimizer# Prompt Optimizer
Transform vague, underperforming prompts into precise, structured prompts that consistently produce high-quality AI outputs.
Description
This skill takes any user prompt — whether vague, ambiguous, or poorly structured — and systematically refines it into a professional-grade prompt following established prompt engineering principles. It applies techniques from chain-of-thought, role-prompting, few-shot learning, and structured output formatting to maximize AI performance.
When to Use
Instructions
The OPTIMIZE Framework
When refining a prompt, apply these six principles in order:
#### O — Objective (明确目标)
**Problem**: Vague verbs like "write about," "explain," "help with"
**Fix**: Specify exact deliverable and success criteria
| Vague | Optimized |
|-------|-----------|
| "Write about AI" | "Write a 500-word blog post explaining how large language models work, targeting software developers with 2+ years of experience" |
| "Make it better" | "Improve clarity and reduce sentence length by 30% while preserving all technical details" |
| "Fix the code" | "Refactor this Python function to reduce cyclomatic complexity below 5 and add type hints" |
#### P — Persona (设定角色)
Assign a specific role to ground the AI's expertise:
Include constraints: "Respond only with what you're confident about. If uncertain, say so."
#### T — Task Structure (任务结构)
Break complex tasks into ordered steps:
1. First, analyze X and identify Y
2. Then, based on Y, generate Z using method A
3. Finally, format the output as...For multi-step tasks, use numbered steps rather than one compound instruction.
#### I — Input Specification (输入规范)
Define what the user will provide:
Explicit input templates reduce ambiguity.
#### M — Metrics & Constraints (约束条件)
Add specific constraints:
Constraints:
- Maximum 500 words
- Use only peer-reviewed sources
- No jargon; explain all technical terms
- Output in Chinese
- Format as a comparison table
- Must include 3 concrete examples#### I — Ideal Output (理想输出)
Show or describe the desired output format:
Prompt Optimization Process
Given a raw prompt, produce:
1. **Diagnosis**: What's wrong with the original (vague goal? missing context? no format? no constraints?)
2. **Optimized Prompt**: The refined version following OPTIMIZE framework
3. **Explanation**: What was changed and why
Common Anti-Patterns
| Anti-Pattern | Problem | Fix |
|-------------|---------|-----|
| "Just make it good" | No quality criteria | Define what "good" means with measurable criteria |
| Giant wall of text | AI loses focus | Break into numbered sections with clear headers |
| Contradictory instructions | AI guesses priority | Remove conflicts; rank priorities explicitly |
| Missing negative constraints | AI makes unwanted assumptions | Add "Do NOT..." instructions for known failure modes |
| No examples | AI style is unpredictable | Provide 1-3 input/output examples |
Examples
**Raw Prompt**: "Write an email to my boss asking for a raise"
**Optimized Prompt**:
You are a professional career coach helping a software engineer draft a salary negotiation email.
Task: Write a salary increase request email to my manager.
Context:
- I'm a mid-level software engineer, 2 years at the company
- I recently led a project that saved the company $200K annually
- The company just closed a successful funding round
- My current salary is below market rate based on Levels.fyi data
Requirements:
- Professional but warm tone (not aggressive, not passive)
- 150-250 words
- Lead with value delivered, not personal needs
- Include a specific meeting request
- No ultimatums or comparisons with colleagues
Format: Standard email with subject line**Raw Prompt**: "分析这个数据"
**Optimized Prompt**:
You are a senior data analyst. Analyze the provided dataset and produce a business report.
Input: I will provide a CSV file with monthly sales data (columns: date, product, quantity, revenue, region).
Steps:
1. Identify the top 3 revenue-generating products
2. Detect any seasonal trends or anomalies
3. Compare regional performance
4. Provide 3 actionable business recommendations
Output format:
- Executive summary (3 sentences)
- Key findings as a numbered list
- Recommendations with expected impact (high/medium/low)
- Any data quality concerns
Language: ChineseTips
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