prompt-master

![](https://s6.imgcdn.dev/YvLVug.png)

<br/>

A Claude skill that writes the accurate prompts for any AI tool. Zero tokens or credits wasted. Full context and memory retention. No re-prompting your way to an answer you should have gotten on attempt one.

**Works with:** Claude, ChatGPT, Gemini, o1/o3, MiniMax, Cursor, Claude Code, GitHub Copilot, Windsurf, Bolt, v0, Lovable, Devin, Perplexity, Midjourney, DALL-E, Stable Diffusion, ComfyUI, Sora, Runway, ElevenLabs, Zapier, Make, and any AI tool you throw at it.

---

## 🚀 Installation

### RECOMMENDED - Claude.ai (browser)

1. Download this repo as a ZIP
2. Go to **claude.ai → Sidebar → Customize → Skills → Upload a Skill**


### OR Clone directly into Claude Code skills directory (Not Suggested)

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

## 🔥 The Problem This Solves

Every AI user wastes credits the same way:

> Write vague prompt → get wrong output → re-prompt → get closer → re-prompt again → finally get what you wanted on attempt 4

That's 3 wasted API calls. Multiply by 50 prompts a day. That's real money and real time gone.

### The key insight

> "The best prompt is not the longest. It's the one where every word is load-bearing."

Most "prompt generators" make prompts longer. This skill makes them sharper.

---

## 🎯 Usage

In Claude, you can invoke the skill naturally:

```
Write me a prompt for Cursor to refactor my auth module
```

```
I need a prompt for Claude Code to build a REST API — ask me what you need to know
```

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

```
Generate a Midjourney prompt for a cyberpunk city at night
```

```
I have a reference image — help me write a prompt to edit just the head angle
```

```
Break this prompt down and adapt it for Stable Diffusion
```

Or explicitly invoke it:

```
/prompt-master

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

---

## How It Works

Prompt Master runs a structured pipeline on every request:

1. **Detects the target tool** — figures out which AI system the prompt is for and routes silently to the right approach
2. **Extracts 9 dimensions of intent** — task, input, output, constraints, context, audience, memory, success criteria, examples
3. **Asks targeted clarifying questions** — max 3 questions if critical info is missing, never more
4. **Routes to the right framework** — picks and applies the correct prompt architecture automatically, never shown to the user
5. **Applies safe techniques only** — role assignment, few-shot examples, XML structure, grounding anchors, memory block as needed
6. **Runs a token efficiency audit** — strips every word that doesn't change the output
7. **Delivers the prompt** — one clean copyable block with a one-line strategy note

---
## Full Example #1: Generating Prompts for Images

### User Input
```
Write me a midjourney prompt for a realistic samurai standing in the rain at night
```

### Generated Prompt
```
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 and mood anchored early, aspect ratio and version locked, negative prompt prevents style drift.

---
## Full Example #2: Generating Prompts for Coding

### User Input
```
Build a claude code prompt for a landing page for a business 
dashboard that looks and feels exactly like notion - smooth animations, 
clean ui
```


### Generated Prompt
```
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 — no dramatic shadows
- Buttons: black fill, white text, no border radius above 6px

Sections to build in order:
1. Navbar — logo left, nav links center, "Get started free" CTA right. 
   Sticky on scroll, adds subtle border-bottom on scroll with JS.
2. Hero — large left-aligned heading (max 3 lines), subtext, two CTAs 
   (primary black + secondary outlined), hero screenshot mockup 
   placeholder (gray rounded card, 16:9 ratio).
3. Logos bar — "Trusted by teams at..." with 5 placeholder company names 
   in muted gray, centered.
4. Features — 3-column grid. Each card: icon (use emoji), bold title, 
   2-line description. Hover state: border darkens to #d1d5db, 
   translateY(-2px), transition 200ms ease.
5. How it works — alternating left/right layout, 3 steps. Number badge, 
   heading, description, placeholder screenshot card.
6. Pricing — 2 tiers side by side. Free tier: outlined card. Pro tier: 
   black background, white text, "Most popular" badge. List 4 features 
   each with checkmarks.
7. CTA banner — full-width dark section, centered heading, subtext, 
   single CTA button.
8. Footer — 4-column links, copyright line, minimal.

Animations — implement all of these:
- Fade-in + translateY(20px) to translateY(0) on scroll for every section, 
  using IntersectionObserver. Threshold 0.15. Duration 500ms ease-out.
- Staggered animation on feature cards: 100ms delay between each card.
- Navbar CTA button: background transitions from black to #333 on hover, 
  200ms ease.
- Hero CTA primary: same hover transition. Secondary: background goes from 
  transparent to #f3f4f6 on hover.
- Smooth scroll on all anchor links.
- Navbar border-bottom fades in on scroll past 60px using JS scroll event.

Constraints:
- Single file only — all CSS and JS embedded, no external files
- No dependencies except Google Fonts via CDN link tag
- All placeholder images replaced with styled gray div elements
- Must be pixel-perfect at 375px mobile and 1440px desktop
- No CSS frameworks, no utility classes from external sources

Done When:
- All 8 sections render correctly at both breakpoints
- All animations trigger on scroll without layout shift
- Navbar sticks and border appears on scroll
- Hover states work on all interactive elements
- Opens in browser with zero console errors
```
**🎯 Target:** Claude Code · **💰 Tokens:** Medium (~380) · **💡 Strategy:** Every vague Notion aesthetic cue translated into exact hex values and pixel specs — Claude Code cannot guess wrong. Animations defined with exact timing, method, and trigger so there is no interpretation needed.

---

## 🤝 Works With Any AI Tool

Prompt Master includes specific profiles for 20+ tools. For anything not on the list, it uses a **Universal Fingerprint**: 4 questions that let it write a quality prompt for any AI system it has never seen before.

<details>
<summary><h3> Click to view all 30+ tool profiles </h3></summary>

| Tool | Category | What Prompt Master Fixes |
|------|----------|--------------------------|
| **Claude** | Reasoning LLM | Removes padding, adds XML structure, specifies length |
| **ChatGPT / GPT-5.x** | Reasoning LLM | Output contract, verbosity control, completion criteria |
| **Gemini 2.x** | Reasoning LLM | Grounding anchors, citation rules, format locks |
| **o3 / o4-mini** | Thinking LLM | Short clean instructions only — never adds CoT (they think internally) |
| **Ollama** | Local LLM | Asks which model is loaded, includes system prompt for Modelfile |
| **Qwen 2.5 / Qwen3** | Open-weight LLM | Chat template format, thinking vs non-thinking mode detection |
| **Local models (Llama, Mistral)** | Open-weight LLM | Shorter prompts, simpler structure, no complex nesting |
| **DeepSeek-R1** | Reasoning LLM | Short clean instructions, strips CoT, suppresses thinking output if needed |
| **MiniMax (M2.7 / M2.5)** | Reasoning LLM | Temperature clamping, thinking tag control, structured output optimization |
| **Claude Code** | Agentic AI | Stop conditions, file scope, checkpoint output |
| **Cursor / Windsurf** | IDE AI | File path, function name, do-not-touch list, sequential prompt guidance |
| **Cline (formerly Claude Dev)** | Agentic IDE | File scope, approval gates, stop conditions, task breakdown |
| **GitHub Copilot** | Autocomplete AI | Exact function contract as docstring |
| **Antigravity** | Agentic IDE | Task-based prompting, Artifact verification, autonomy level |
| **Bolt / v0 / Lovable** | Full-stack generator | Stack spec, version, what NOT to scaffold |
| **Figma Make** | Full-stack generator | Component name references, frame-to-code scope |
| **Google Stitch** | Full-stack generator | Interface goal over implementation, Material Design 3 spec |
| **Devin / SWE-agent** | Autonomous agent | Starting state, target state, stop conditions |
| **Manus** | Autonomous agent | Task outcome focus, permission scope, memory anchors |
| **OpenAI Computer Use** | Computer-use agent | Screen state, allowed apps, stop before irreversible actions |
| **Perplexity Computer** | Computer-use agent | Artifact-first prompting, scoped permissions, verification steps |
| **OpenClaw** | Computer-use agent | Conversational precision, persistent memory, security constraints |
| **Perplexity / SearchGPT** | Search AI | Mode spec: search vs analyze vs compare |
| **Midjourney** | Image AI | Comma-separated descriptors, parameters, negative prompts |
| **DALL-E 3** | Image AI | Prose description, text exc