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prompt-master

Name: prompt-master (Claude Skill)
Author: nidhinjs

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.

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핵심 기능

Supports 30+ target tools (Claude, ChatGPT, Midjourney, DALL-E, Cursor, Copilot, etc.)
Detects 35 'credit-killing' patterns — vague verbs, missing success criteria, assumed context
Memory Block preserves prior decisions across the session to avoid contradictions
Applies only proven techniques (role assignment, few-shot, XML structure); excludes unreliable ones
Asks up to 3 clarifying questions rather than guessing

라이브 데모

실제 사용 모습

prompt-master-skill.replay ▶ 준비됨

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설치

작성자 저장소 · Claude Skills 공식 문서

사용 사례

실전 활용법: prompt-master

Craft a Midjourney prompt that actually matches your mental image

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

언제 쓸까: Your first 3 Midjourney generations came back wrong and you're burning fast-hours.

흐름

Describe what you want in plain language

Use prompt-master. I want a hero image for a fintech landing page — serious, warm, not boring.✓ 복사됨

→ Claude asks 1-2 clarifying questions about aspect ratio and style anchors
Get the optimized prompt

Yes — 16:9, inspired by Monocle magazine.✓ 복사됨

→ A Midjourney-ready prompt with weights, --ar, --style, --s params

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

함정

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

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

흐름

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.✓ 복사됨

→ Structured prompt with explicit constraints, negative examples, output format
Test on one file first

Apply the prompt to src/legacy/UserList.tsx and show the diff. Does it hold?✓ 복사됨

→ Clean diff that matches the stated constraints

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

함정

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

조합

다른 MCP와 조합해 10배 효율

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.✓ 복사됨

도구

이 MCP가 노출하는 것

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

비용 및 제한

운영 비용

API 쿼터: None
호출당 토큰: 1-3k per prompt optimization — small
금액: Free — skill is local prompts
팁: The whole point of the skill is reducing wasted tokens downstream; the upfront cost is tiny.

보안

권한, 시크릿, 파급범위

자격 증명 저장: No credentials — skill is pure prompts

데이터 외부 송신: None

문제 해결

자주 발생하는 오류와 해결

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.

대안

prompt-master 다른 것과 비교

대안	언제 쓰나	단점/장점
Manual prompting with a template library	You already know the patterns and just need a reference	Faster for experts; prompt-master wins for non-obvious cases