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-dub0 来源安装数☆ 0 仓库 Starsv1.0.0

查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install gyaan-dub/prompt-enhancer

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

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...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/gyaan-dub/prompt-enhancer
Version: 1.0.0
Commit: 8abd1e57d293ee152fc0fd367f15e17f874f1076
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# 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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