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WHEN refining or structuring prompts; NOT executing tasks; outputs XML-tagged instructions with roles, tasks, constraints, and examples.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
| name | prompt-master |
| description | WHEN refining or structuring prompts; NOT executing tasks; outputs XML-tagged instructions with roles, tasks, constraints, and examples. |
Transform simple prompts into comprehensive, context-rich instruction sets following Claude's XML tagging best practices.
Understand the objective, desired outcome, and success criteria.
Ask for missing inputs when unclear:
Wrap user-provided details in descriptive XML tags (e.g., <user_prompt>, <context>, <audience>, <tone>, <constraints>). Keep directives outside user-data tags.
Expand the prompt into detailed, ordered instructions with explicit actions:
<example> tags (mark as illustrative)<tools>, <function_call>, <api_schema>Use descriptive, properly nested tags; close all tags.
Helpful tags:
<role> - Define the AI's persona and objective<key_responsibilities> - List core duties<approach> - Break down the workflow<step number=""> - Sequential actions<tasks> - Specific actionable items<additional_considerations> - Edge cases, safety, compliance<reasoning visibility="hidden"> - Internal thought process guidanceStructure the response as:
[One-line introduction]
```markdown
[Enhanced prompt with XML tags]
```
**Key Improvements Made:**
- [Improvement 1]
- [Improvement 2]
- [Improvement 3]
Wrap the enhanced prompt in a markdown code fence (markdown ... ) for clear presentation.
<role>You are an AI-powered [role description]. [Concise persona and objective]</role>
<user_input>
<user_prompt>[Original prompt]</user_prompt>
<context>[Background or constraints]</context>
<audience>[Intended audience]</audience>
<tone>[Desired tone]</tone>
</user_input>
<key_responsibilities>
- [Responsibility 1]
- [Responsibility 2]
</key_responsibilities>
<approach>
<step number="1" title="[Step title]">
- [Actions or questions]
</step>
<step number="2" title="[Step title]">
- [How to add detail and structure]
</step>
<step number="3" title="[Step title]">
- [Formatting, checks, validation]
</step>
</approach>
<tasks>
- [Specific actionable tasks]
- [Edge cases or validations]
</tasks>
<additional_considerations>
- [Safety, compliance, or scope boundaries]
- [Note assumptions; invite clarifications]
</additional_considerations>
<example>
[Optional illustrative refined prompt]
</example>
WHEN scraping iOS/macOS App Store data (apps, reviews, ratings, search); NOT for installing or testing apps; retrieves structured JSON data using iTunes/App Store APIs with curl and jq formatting
Comprehensive guide for implementing on-device AI models on iOS using Foundation Models and MLX Swift frameworks. Use WHEN building iOS apps with (1) Local LLM inference, (2) Vision Language Models (VLMs), (3) Text embeddings, (4) Image generation, (5) Tool/function calling, (6) Multi-turn conversations, (7) Custom model integration, or (8) Structured generation.
WHEN building ChatGPT apps using the OpenAI Apps SDK and MCP; create conversational, composable experiences with proper UX, UI, state management, and server patterns.
WHEN building SwiftUI views, managing state, setting up shared services, or making architectural decisions; NOT for UIKit or legacy patterns; provides pure SwiftUI data flow without ViewModels using @State, @Binding, @Observable, and @Environment.
WHEN building design systems or component libraries with Tailwind CSS; covers design tokens, CVA patterns and dark mode.
WHEN building React components/pages/apps; enforces scalable architecture, state management, API layer, performance patterns.