prompt-optimizer

What This Skill Does

The Prompt Optimizer is a sophisticated AI agent skill designed to elevate the efficacy of your interactions with language models. It acts as an expert consultant, systematically evaluating your prompts against a rigorous framework of 58 proven prompting techniques, including Chain of Thought (CoT), few-shot learning, and role-based persona design. By analyzing clarity, specificity, structure, and tone, this skill identifies gaps in your current instructions and automatically reformulates them into highly optimized, high-performance prompts that ensure the AI understands your goals with maximum precision.

Installation

To integrate the Prompt Optimizer into your environment, run the following command in your terminal: clawhub install openclaw/skills/skills/hhhh124hhhh/prompt-optimizer

Use Cases

• Refining Ambiguous Instructions: Convert vague requests like "Write a marketing email" into professional, goal-oriented campaigns using target audience persona and brand constraints.
• Complex Logic Tasks: Enhance prompts for multi-step reasoning by injecting Chain of Thought patterns to reduce hallucinations and improve logical flow.
• Consistency & Style Alignment: Ensure your AI responses maintain a specific voice or formatting constraint by injecting structural requirements into your prompts.
• Few-Shot Learning Setup: Automatically generate high-quality examples to train the context window on the specific type of output you require.

Example Prompts

1. "I have this prompt: 'Help me write a blog post about AI'. It feels too generic. Can you optimize it to be more engaging and structured?"
2. "Please evaluate my current prompt and apply the Chain of Thought technique to ensure the model solves this math problem accurately."
3. "I need a prompt that asks the AI to act as a senior software architect. Please add structural constraints and specific coding standards to my existing prompt."

Tips & Limitations

• Be Specific: Always provide the original context or document you are trying to process when asking for optimization.
• Iterative Feedback: Don't hesitate to refine the output. If the first optimization is too complex, ask the skill to simplify the structure.
• Limitations: While the skill utilizes 58 techniques, it cannot magically provide context you haven't given it. It functions best when you provide the 'source' or 'target' material alongside the prompt you wish to improve.