prompt-engineer

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Transforms user prompts into optimized prompts using frameworks (RTF, RISEN, Chain of Thought, RODES, Chain of Density, RACE, RISE, STAR, SOAP, CLEAR, GROW)

AI & Automation 39,350 stars 6386 forks Updated today MIT

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Description 5%
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Skill Content

## Purpose This skill transforms raw, unstructured user prompts into highly optimized prompts using established prompting frameworks. It analyzes user intent, identifies task complexity, and intelligently selects the most appropriate framework(s) to maximize Claude/ChatGPT output quality. The skill operates in "magic mode" - it works silently behind the scenes, only interacting with users when clarification is critically needed. Users receive polished, ready-to-use prompts without technical explanations or framework jargon. This is a **universal skill** that works in any terminal context, not limited to Obsidian vaults or specific project structures. ## When to Use Invoke this skill when: - User provides a vague or generic prompt (e.g., "help me code Python") - User has a complex idea but struggles to articulate it clearly - User's prompt lacks structure, context, or specific requirements - Task requires step-by-step reasoning (debugging, analysis, design) - User needs a prompt for a specific AI task but doesn't know prompting frameworks - User wants to improve an existing prompt's effectiveness - User asks variations of "how do I ask AI to..." or "create a prompt for..." ## Workflow ### Step 1: Analyze Intent **Objective:** Understand what the user truly wants to accomplish. **Actions:** 1. Read the raw prompt provided by the user 2. Detect task characteristics: - **Type:** coding, writing, analysis, design, learning, planning, decision-making, creative, etc. ...

Details

Author
sickn33
Repository
sickn33/antigravity-awesome-skills
Created
4 months ago
Last Updated
today
Language
Python
License
MIT

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