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prompt-master

by nidhinjs · nidhinjs/prompt-master

A meta-skill that turns vague requests into tight, effective prompts for Claude, ChatGPT, Midjourney, Cursor, and 30+ other AI tools.

Prompt Master runs a 6-step pipeline on your ask: detect target tool, extract intent across 9 dimensions, clarify if needed, pick from 12 prompt templates, audit for waste, and deliver a clean copy-ready prompt. It preserves prior decisions in a Memory Block so your follow-ups don't contradict the setup.

▶ Watch demo 📦 Install 💡 Use Cases

Why use it

Key features

Live Demo

What it looks like in practice

prompt-master-skill.replay ▶ ready
0/0

Install

Author repository · Claude Skills documentation

Use Cases

Real-world ways to use prompt-master

Craft a Midjourney prompt that actually matches your mental image

👤 Designers and marketers working with image models ⏱ ~5 min beginner

When to use: Your first 3 Midjourney generations came back wrong and you're burning fast-hours.

Flow
  1. Describe what you want in plain language
    Use prompt-master. I want a hero image for a fintech landing page — serious, warm, not boring.✓ Copied
    → Claude asks 1-2 clarifying questions about aspect ratio and style anchors
  2. Get the optimized prompt
    Yes — 16:9, inspired by Monocle magazine.✓ Copied
    → A Midjourney-ready prompt with weights, --ar, --style, --s params

Outcome: A reusable prompt you can vary slightly for a full campaign.

Pitfalls
  • Skill over-clarifies for a simple request — Say 'skip clarification, one-shot it'

Write a tight Cursor system prompt for a recurring refactor

👤 Developers who use Cursor for codebase-wide changes ⏱ ~10 min intermediate

When to use: You're about to run the same refactor across 20 files and want a prompt that actually constrains the model.

Flow
  1. State the refactor
    prompt-master — write a Cursor prompt: convert all React class components in src/legacy to functional components with hooks, preserve prop types, no behavioral changes.✓ Copied
    → Structured prompt with explicit constraints, negative examples, output format
  2. Test on one file first
    Apply the prompt to src/legacy/UserList.tsx and show the diff. Does it hold?✓ Copied
    → Clean diff that matches the stated constraints

Outcome: A prompt you can paste into Cursor and trust across the full directory.

Pitfalls
  • Prompt too generic, model freelances — Ask prompt-master to add at least one concrete before/after example

Combinations

Pair with other MCPs for X10 leverage

prompt-master-skill + nano-banana-pro-prompts-recommend-skill

Use prompt-master to structure the intent, then the Nano Banana skill to pick a tested image prompt pattern

Use prompt-master to nail down what I want, then hand off to nano-banana-pro-prompts for the final image prompt.✓ Copied

Tools

What this MCP exposes

ToolInputsWhen to callCost
Tool detection user request First stage of the pipeline 0
Intent extraction request + context After tool detection 0
Clarification missing-critical-info flags Only when success criteria unclear 0
Framework selection task type Before composition 0
Efficiency audit draft prompt Final polish step 0

Cost & Limits

What this costs to run

API quota
None
Tokens per call
1-3k per prompt optimization — small
Monetary
Free — skill is local prompts
Tip
The whole point of the skill is reducing wasted tokens downstream; the upfront cost is tiny.

Security

Permissions, secrets, blast radius

Credential storage: No credentials — skill is pure prompts
Data egress: None

Troubleshooting

Common errors and fixes

Skill over-asks clarifying questions

Add 'make reasonable assumptions, don't ask more than 1 question' to your request.

Output prompt is too long

Explicitly request 'efficient mode' — the audit step will strip harder.

Memory Block loses context between sessions

Memory is per-working-directory; run follow-ups from the same folder.

Alternatives

prompt-master vs others

AlternativeWhen to use it insteadTradeoff
Manual prompting with a template libraryYou already know the patterns and just need a referenceFaster for experts; prompt-master wins for non-obvious cases

More

Resources

📖 Read the official README on GitHub

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