Qf Prompt Optimizer
Skill by 371166758-qq
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/371166758-qq/qf-prompt-optimizerPrompt 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
- The user provides a vague prompt like "write something about marketing" and expects better results
- A prompt produces inconsistent or off-topic outputs
- Converting natural language requests into structured prompts
- Building prompt templates for repeated use
- Debugging prompts that fail in edge cases
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:
- "You are a senior staff engineer at Google with 15 years of distributed systems experience"
- "You are a Nature journal reviewer specializing in immunology"
- "You are a direct-response copywriter trained by Eugene Schwartz's methods"
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:
- "I will provide: (1) a product description, (2) target audience, (3) competitor list"
- "Input: A CSV file with columns [date, revenue, expenses]"
- "Here is the code to review:
<language>\n...\n"
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:
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-371166758-qq-qf-prompt-optimizer": {
"enabled": true,
"auto_update": true
}
}
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