aradotso/trending-skills/prompt-master-skill

---
name: prompt-master-skill
description: Claude skill that generates accurate, token-efficient prompts for any AI tool — Claude, GPT, Midjourney, Cursor, and 30+ more.
triggers:
  -write me a prompt for
  -generate a prompt for
  -help me prompt
  -fix my prompt
  -create a midjourney prompt
  -write a cursor prompt
  -make a prompt for claude code
  -I need a better prompt for
---
 
# Prompt Master
 
> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection.
 
Prompt Master is a Claude skill that writes sharp, token-efficient prompts for any AI tool. It eliminates the re-prompting loop by extracting full intent on the first pass, routing to the right prompt architecture, and auditing every word for necessity before delivery.
 
**Supports:** Claude, ChatGPT, Gemini, o1/o3/o4, DeepSeek, MiniMax, Qwen, Cursor, Windsurf, Claude Code, GitHub Copilot, Bolt, v0, Lovable, Devin, Perplexity, Midjourney, DALL-E, Stable Diffusion, ComfyUI, Sora, Runway, ElevenLabs, Zapier, Make, and any unknown tool via universal fingerprint.
 
---
 
## Installation
 
### Recommended — Claude.ai (browser)
 
1.Download the repo as a ZIP from [github.com/nidhinjs/prompt-master](https://github.com/nidhinjs/prompt-master)
2.Go to **claude.ai → Sidebar → Customize → Skills → Upload a Skill**
 
### Claude Code (CLI)
 

mkdir -p ~/.claude/skills git clone https://github.com/nidhinjs/prompt-master.git ~/.claude/skills/prompt-master

 
Once installed, the skill activates automatically when Claude detects prompt-generation intent, or you can invoke it explicitly.
 
---
 
## How to Invoke
 
### Natural language (auto-detected)
 

Write me a prompt for Cursor to refactor my auth module

I need a prompt for Claude Code to build a REST API

Here's a bad prompt I wrote for GPT-4o, fix it: [paste prompt]

Generate a Midjourney prompt for a cyberpunk city at night

 
### Explicit invocation
 

/prompt-master

I want to ask Claude Code to build a todo app with React and Supabase

 
---
 
## What Happens Internally (The Pipeline)
 
Prompt Master runs a 7-step pipeline on every request. You never see the machinery — only the output.
 
| Step | What It Does |
|------|-------------|
| 1. **Tool Detection** | Identifies the target AI system and routes to its profile |
| 2. **Intent Extraction** | Pulls 9 dimensions: task, input, output, constraints, context, audience, memory, success criteria, examples |
| 3. **Clarifying Questions** | Asks ≤3 targeted questions if critical info is missing |
| 4. **Framework Routing** | Selects the right prompt architecture from 12 templates |
| 5. **Safe Techniques** | Applies role assignment, few-shot, XML structure, grounding anchors, memory blocks |
| 6. **Token Efficiency Audit** | Strips every word that doesn't change the output |
| 7. **Delivery** | One clean copyable block + one-line strategy note |
 
---
 
## Prompt Templates (Auto-Selected)
 
You never choose a template — Prompt Master picks it. Shown here for understanding:
 
| Template | Used For |
|----------|----------|
| **RTF** (Role, Task, Format) | Fast one-shot tasks |
| **CO-STAR** | Professional documents, business writing |
| **RISEN** | Complex multi-step projects |
| **CRISPE** | Creative work, brand voice, iterative content |
| **Chain of Thought** | Math, logic, debugging, multi-step analysis |
| **Few-Shot** | Consistent structured output, pattern replication |
| **File-Scope Template** | Cursor, Windsurf, Copilot — code editing AI |
| **ReAct + Stop Conditions** | Claude Code, Devin — autonomous agents |
| **Visual Descriptor** | Midjourney, Stable Diffusion, image AI |
| **Prose Description** | DALL-E 3 |
| **Node Split** | ComfyUI (positive/negative node separation) |
| **Universal Fingerprint** | Any unknown tool — 4 questions, then generates |
 
---
 
## Real Usage Examples
 
### Example 1 — Image prompt (Midjourney)
 
**You say:**

Write me a midjourney prompt for a realistic samurai standing in the rain at night

 
**Prompt Master delivers:**

lone samurai standing in heavy rain at night, traditional armor, neon reflections on wet cobblestone street, cinematic lighting, dramatic shadows, fog, ultra detailed, photorealistic, shallow depth of field --ar 16:9 --v 6 --style raw

negative: blurry, low quality, watermark, cartoon, anime, extra limbs

 
> 🎯 Target: Midjourney · ⚡ Framework: Visual Descriptor · 💰 Tokens: Light (~60)
> 💡 Strategy: Comma-separated descriptors over prose, lighting anchored early, version locked, negative prompt prevents style drift.
 
---
 
### Example 2 — Coding prompt (Claude Code)
 
**You say:**

Build a claude code prompt for a landing page that looks like Notion

 
**Prompt Master delivers:**

Objective: Build a fully detailed, production-quality static landing page for a business dashboard product. Design must match Notion's exact aesthetic — clean, minimal, typographic, with smooth animations throughout.

Stack: Single HTML file with embedded CSS and vanilla JS. No frameworks. No external dependencies except Google Fonts (Inter).

Design Spec — match these exactly:

• Background: #ffffff
• Primary text: #1a1a1a
• Secondary text: #6b7280
• Border color: #e5e7eb
• Accent: #000000
• Font: Inter, weights 400 / 500 / 600 / 700
• Base spacing unit: 8px
• Border radius: 6px on cards, 4px on buttons
• Box shadows: 0 1px 3px rgba(0,0,0,0.08) only

Sections to build in order:

1. Navbar — logo left, nav links center, CTA right. Sticky, border-bottom on scroll.
2. Hero — large left-aligned heading, subtext, two CTAs, mockup placeholder.
3. Logos bar — "Trusted by teams at..." with 5 placeholder names, muted gray.
4. Features — 3-column grid, icon + bold title + 2-line description.

Hover: border darkens to #d1d5db, translateY(-2px), 200ms ease.

1. How it works — alternating left/right, 3 steps.
2. Pricing — 2 tiers. Free: outlined. Pro: black bg, white text, badge.
3. CTA banner — full-width dark section, centered heading, single CTA.
4. Footer — 4-column links, copyright.

Animations:

• Fade-in + translateY(20px→0) on scroll via IntersectionObserver. Threshold 0.15. 500ms ease-out.
• Feature cards: 100ms stagger delay.
• All hover transitions: 200ms ease.
• Smooth scroll on all anchor links.

Constraints:

• Single file only. All CSS and JS embedded.
• No dependencies except Google Fonts CDN.
• Placeholder images = styled gray divs.
• Pixel-perfect at 375px and 1440px.
• Zero console errors.

Done When: All 8 sections render, animations trigger without layout shift, hover states work, navbar sticks and border appears on scroll.

 
> 🎯 Target: Claude Code · 💰 Tokens: Medium (~380)
> 💡 Strategy: Every vague aesthetic cue translated into exact hex values and pixel specs — Claude Code cannot guess wrong.
 
---
 
### Example 3 — Fix a bad prompt
 
**You say:**

Here's a bad prompt I wrote for GPT-4o, fix it:

"write me some python code to handle user auth"

 
**Prompt Master delivers:**

You are a senior Python backend engineer.

Task: Implement a complete user authentication module.

Requirements:

• Framework: FastAPI
• Auth method: JWT (access token 15min, refresh token 7 days)
• Password hashing: bcrypt via passlib
• Endpoints: POST /auth/register, POST /auth/login, POST /auth/refresh, POST /auth/logout
• Store refresh tokens in Redis with TTL
• Return format: { access_token, refresh_token, token_type }

Constraints:

• No third-party auth services (Auth0, Firebase, etc.)
• No ORM — use raw asyncpg queries
• Include input validation with Pydantic v2 models
• Include error handling with proper HTTP status codes

Deliver:

• auth/router.py
• auth/schemas.py
• auth/utils.py
• auth/dependencies.py

Do not scaffold a full app. Auth module only.

 
> 🎯 Target: GPT-4o · ⚡ Framework: RTF + File-Scope
> 💡 Strategy: Vague "some python code" collapsed into exact stack, endpoints, constraints, and file deliverables.
 
---
 
### Example 4 — Stable Diffusion
 
**You say:**

Write a stable diffusion prompt for a futuristic city interior, warm lighting

 
**Prompt Master delivers:**

Positive: futuristic city interior, (warm golden lighting:1.3), (volumetric light rays:1.2), glass and steel architecture, holographic displays, busy atrium, people walking, ultra detailed, 8k, cinematic composition, (photorealistic:1.4), depth of field, bokeh background

Negative: (blurry:1.3), (low quality:1.3), (watermark:1.2), cartoon, anime, flat lighting, oversaturated, extra limbs, bad anatomy, deformed, ugly, duplicate, morbid, mutilated, out of frame

 
> 🎯 Target: Stable Diffusion · ⚡ Framework: Node Split
> 💡 Strategy: Weight syntax applied to critical elements, mandatory negative prompt, photorealism locked.
 
---
 
### Example 5 — Workflow automation (Zapier)
 
**You say:**

Write a prompt for Zapier to automatically save Gmail attachments to Google Drive

 
**Prompt Master delivers:**

Trigger:

• App: Gmail
• Event: New Email Matching Search
• Search filter: has:attachment

Filter (add a Filter step):

• Only continue if: Attachment exists = True

Action 1:

• App: Gmail
• Action: Get Email
• Field: Use email ID from trigger step

Action 2:

• App: Google Drive
• Action: Upload File
• File: Attachment from Action 1
• Drive: My Drive
• Folder: /Gmail Attachments/{{trigger.from_email}}/{{trigger.date_formatted}}
• File name: {{trigger.subject}} - {{attachment.filename}}

Notes:

• Add a second Action 2 loop if email can have multiple attachments
• Set folder path dynamically using sender email and date to avoid clutter
• Test with a single known email before enabling live Zap

 
> 🎯 Target: Zapier · ⚡ Framework: Trigger-Action Map
> 💡 Strategy: Trigger app + event + filter + field mapping fully specified — no Zapier configuration guesswork.
 
---
 
## Tool Profile Reference
 
Prompt Master includes built-in profiles that know the quirks of each tool:
 

Claude → XML structure, length spec, no padding ChatGPT → Output contract, verbosity control, completion criteria Gemini → Grounding anchors, citation rules, format locks o3/o4-mini → Short clean instructions only — never add CoT (they think internally) DeepSeek-R1 → Short instructions, suppresses thinking output if needed MiniMax → Temperature hints, thinking tag control Ollama → Asks which model is loaded, includes system prompt for Modelfile Cursor → File path, function name, do-not-touch list Claude Code → Stop conditions, file scope, checkpoint output Copilot → Exact function contract as docstring Bolt/v0 → Stack spec, version, what NOT to scaffold Devin → Starting state, target state, stop conditions Midjourney → Comma descriptors, --parameters, negative prompts DALL-E 3 → Prose description, text exclusion, edit vs generate detection Stable Diff → Weight syntax (word:1.3), CFG, mandatory negatives ComfyUI → Positive/negative node split, checkpoint-specific syntax Sora/Runway → Camera movement, duration, cut style ElevenLabs → Emotion, pacing, emphasis, speech rate Zapier/Make → Trigger + event + action + field mapping

 
For any unlisted tool, Prompt Master uses the **Universal Fingerprint** — 4 questions to characterize the tool and generate a quality prompt anyway.
 
---
 
## Clarifying Questions Logic
 
Prompt Master asks ≤3 questions only when critical info is genuinely missing. It never asks for information it can reasonably infer.
 
**It will ask when:**
- Target tool is ambiguous and it changes the output significantly
- Task scope is completely undefined (e.g. "write a prompt for building an app" — what app?)
- Output format has high-stakes options (e.g. single file vs multi-file for Claude Code)
 
**It will NOT ask:**
- For style preferences it can default to sensibly
- For confirmation of things clearly stated
- More than 3 questions ever
 
---
 
## Key Principles
 
### The core insight
> "The best prompt is not the longest. It's the one where every word is load-bearing."