An advanced prompt engineering skill designed to systematically deconstruct, diagnose, and optimize raw inputs into highly effective prompts for ChatGPT, Claude, Gemini, and DeepSeek.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install yq-prompt-optimizer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install yq-prompt-optimizer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is yq-prompt-optimizer?
The AI Prompt Optimizer is a master-class utility engineered to convert vague, raw user requests into highly structured, high-performing prompts tailored for modern Large Language Models. Built to integrate seamlessly with Openclaw Skills, this agent uses a systematic approach to unlock the maximum potential of AI platforms including ChatGPT, Claude, Gemini, and DeepSeek.
By leveraging advanced prompt engineering techniques and a multi-dimensional analysis framework, the skill eliminates ambiguity and guesswork. It ensures that the generated instructions are clear, robust, and highly executable, saving developers and creators valuable time while drastically improving output quality across any AI task.
yq-prompt-optimizer Use Cases
- Refining vague or brief ideas into comprehensive instructions for complex software development tasks.
- Tailoring creative writing, marketing copy, or technical documentation prompts to achieve specific tones and formats.
- Debugging and correcting underperforming LLM prompts that produce hallucinated or low-quality results.
- Designing structured multi-turn instructions and systems prompts for custom AI agents within Openclaw Skills.
- Optimizing code generation and technical analysis prompts specifically for reasoning models like DeepSeek or Claude.
How yq-prompt-optimizer Works
- Input & Welcome Capture: The system receives your raw prompt along with your chosen target AI platform (e.g., ChatGPT, Claude, Gemini, DeepSeek).
- Complexity Assessment: The skill automatically analyzes the complexity of the input. Short, straightforward tasks (<50 characters) activate Basic Mode, while professional, multi-layered queries trigger Detail Mode.
- Deconstruction & Diagnosis (4D Framework): It systematically extracts your core intent, identifies missing context, and diagnoses clarity, completeness, and structural issues in your original prompt.
- Targeted Strategy Development: The skill applies specialized strategies (such as Chain-of-Thought, Few-Shot Learning, or strict boundaries) customized to the specific AI model's strengths.
- Multi-Role Internal Review: Before outputting, an internal simulation evaluates the draft across four dimensions: precision, completeness, efficiency, and robustness.
- Result Delivery: It outputs the finalized, high-fidelity prompt along with explanations of the key improvements and usage guidance.
yq-prompt-optimizer Setup
To configure and utilize this prompt optimization capability within your workspace, follow these straightforward steps:
- Ensure you have the core agent framework running.
- Install the skill config file directly into your environment:
openclaw install yq-prompt-optimizer
- Initialize the skill in your workspace configuration:
skills:
- name: yq-prompt-optimizer
version: 1.0.0
enabled: true
- Restart your agent session. The optimizer will greet you on its first execution and automatically detect your prompt optimization style.
yq-prompt-optimizer Data Schema & Taxonomy
The AI Prompt Optimizer processes input data dynamically without preserving session history, guaranteeing privacy and stateless efficiency. The metadata and processing criteria are categorized as follows:
| Attribute | Description | Values / Formats |
|---|---|---|
| Target LLM | Specific model optimizations | ChatGPT/GPT-4, Claude, Gemini, DeepSeek, Universal |
| Execution Mode | Complexity-based processing path | BASIC (Direct Output), DETAIL (Interactive Questions) |
| Optimization Framework | Systematic improvement steps | Deconstruct, Diagnose, Develop, Deliver (4D Framework) |
| Evaluation Criteria | Multi-role internal audit metrics | Precision, Completeness, Efficiency, Robustness |
| Response Format | Structure of the returned optimized prompt | Markdown (including Key Improvements, Application Tips, and Usage Guides) |
yq-prompt-optimizer Advanced Features
- Dynamic Complexity Routing: Automatically detects prompt complexity to choose between instant, fast-tracked Basic Mode and deep-dive, interactive Detail Mode.
- Multi-Model Specialization: Fine-tunes instructions using model-specific structures, such as XML tags for Claude or advanced reasoning chains for DeepSeek.
- Stateless Privacy Guarantee: Processed queries are executed in isolated sessions, ensuring no sensitive prompt engineering data or proprietary templates are retained.
- Collaborative Internal Evaluation: Runs a simulated peer-review panel consisting of a Precision Auditor, Completeness Checker, Efficiency Optimizer, and Risk Evaluator to stress-test prompts before final output.
- Modular Integration: Designed to operate alongside other Openclaw Skills to dynamically refine the system instructions of downstream workflows.
SKILL.md
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