Imported from reason-machines/trending-skills (
skills/prompt-master-skill/SKILL.md). Install upstream withnpx skills add reason-machines/trending-skills --skill prompt-master-skill. Copyright stays with the author.
---
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)
```bash
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.
5. How it works — alternating left/right, 3 steps.
6. Pricing — 2 tiers. Free: outlined. Pro: black bg, white text, badge.
7. CTA banner — full-width dark section, centered heading, single CTA.
8. 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."
What Prompt Master does differently from prompt generators
- Other tools: Make prompts longer
- Prompt Master: Makes prompts sharper — token efficiency audit strips everything that doesn't change the output
The 9 dimensions of intent it extracts
- Task — what action needs to happen
- Input — what the AI is working with
- Output — what the result should look like
- Constraints — what must not happen
- Context — background the AI needs
- Audience — who the output is for
- Memory — what should persist across turns
- Success criteria — how to know it's done
- Examples — patterns to replicate or avoid
Troubleshooting
Prompt Master isn't activating
- Ensure the skill is uploaded/installed correctly in Claude's skill directory
- Try explicit invocation:
/prompt-master [your request] - Make sure your request mentions a target tool or prompt-related intent
Generated prompt is too long for my use case
- Tell Prompt Master the token budget:
"Write me a Midjourney prompt, keep it under 50 tokens" - It will re-run the token efficiency audit with a hard cap
Generated prompt doesn't match my tool's syntax
- Name the exact tool version:
"for Stable Diffusion 1.5"vs"for SDXL"— these have different optimal syntax - If it's an obscure or new tool, paste 1-2 example prompts that work:
"Here's a prompt that worked for [Tool X], use that style"
It asked me questions but I want a prompt now
- Say:
"Just generate your best guess, I'll refine after" - Prompt Master will use reasonable defaults and flag its assumptions in the strategy note
The prompt works but I want a variation
- Say:
"Give me 3 variations of that prompt, different approaches" - Or:
"Make it more cinematic"/"Make it more technical"— it retains full context
I want to see which framework it used
- Ask:
"Which prompt framework did you use and why?" - It will explain the routing decision
Tips for Best Results
# Be specific about the target tool
"Write a prompt for Claude Code" ✅
"Write a prompt for an AI" ❌ (will ask for clarification)
# Include your stack when relevant
"Claude Code prompt for a React app using Supabase and Tailwind" ✅
"Claude Code prompt for an app" ❌
# Paste bad prompts for fixing — Prompt Master thrives on this
"Fix this: write me some code for auth" ✅
# Give reference style when you have one
"Generate a Midjourney prompt like this example: [paste]" ✅
# Specify constraints upfront
"Single file only, no external dependencies" ✅ (saves a clarifying question round)
Project Info
- Repo: github.com/nidhinjs/prompt-master
- License: MIT
- Topics: claude-ai, claude-skills, llm, prompt-engineering
- Works with: Claude.ai browser skill system, Claude Code skill directory