OpenClaw

prompt-enhancer

Automatically rewrites rough user inputs into optimized, structured prompts for dramatically better AI responses. Prefix any message with "p:" to activate.

gyaan-dub☆ 0 Repository starsv1.0.0

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install gyaan-dub/prompt-enhancer

View source ↗Guides

Skill instructions

Prompt Enhancer

You have a Prompt Enhancer skill. When a user prefixes their message with p: or prompt:, you must enhance their rough input into a high-quality structured prompt, then execute that enhanced prompt to produce a superior response.

This is a two-step process: first rewrite the prompt, then answer the rewritten prompt.

Trigger Detection

Check every incoming user message for the trigger prefix:

  • The message starts with p: or prompt: (case-insensitive, leading whitespace is OK)
  • Everything after the prefix (trimmed) is the raw user intent
  • If the prefix appears mid-sentence, do NOT trigger — only match at the start

If there is no trigger prefix, process the message normally. This skill does nothing for unprefixed messages.

Empty Input Handling

If the user sends just p: or prompt: with no content (or only whitespace after the prefix), reply with:

What would you like me to help with? Usage: Start your message with p: followed by what you want. Example: p: write me a python script that sorts a list

Do not proceed further.

Step 1: Enhance the Prompt

Take the raw user intent and mentally rewrite it into an optimized prompt using these principles:

1. Role Assignment

Assign yourself a specific expert role relevant to the task. Example: "As a senior full-stack developer specializing in React and Node.js..."

2. Task Clarification

Restate the task with precision and specificity. Infer what the user actually needs, including things they didn't explicitly mention. Break complex tasks into clear subtasks or steps if appropriate.

3. Context Inference

Fill in reasonable assumptions about what the user probably wants. A user asking for "a landing page" probably wants responsive design, a CTA, modern styling, etc. If assumptions are significant, note them briefly so you can adjust if needed.

4. Output Format Specification

Decide exactly how to structure the response. Examples: provide code in a singl...

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