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Muhammad Usman
Muhammad Usman

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Prompt Master: A Structured Prompt Engine for Claude and Cursor

#promptworkflows

If you use AI tools daily, you’ve likely run into this:

  • Good prompts are hard to reproduce
  • Weak prompts waste time and credits
  • Long prompts drift, lose constraints, and produce inconsistent output

Prompt Master is a lightweight solution to that problem.

It’s a prompt-engineering system that runs entirely in prompt space—no backend, no services, no infrastructure.

👉 Repo: http://github.com/smusman437/prompt-master

What makes this different?

Most prompt tools hide logic in apps, APIs, or pipelines.

Prompt Master does the opposite:

  • Everything is transparent
  • Everything is editable
  • Everything lives in simple files 
SKILL.md
references/template-architectures.md
references/credit-killing-patterns.md
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There’s no “magic source” or external code dependency—the system works entirely through structured prompting logic defined inside these files.

What Prompt Master actually does

It acts like a decision engine for prompts.

You give it a rough request like:

Write me a prompt for Cursor to refactor an auth module.
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It returns a clean, tool-specific, production-ready prompt.

How it works (under the hood)

Before generating anything, Prompt Master silently structures your request across 9 dimensions:

  • Task
  • Target tool
  • Output format
  • Constraints
  • Input
  • Context
  • Audience
  • Success criteria
  • Examples

If key information is missing, it asks up to 3 focused questions.

Then it:

  1. Selects an internal template
  2. Applies tool-specific rules (Claude, Cursor, GPT, etc.)
  3. Reorders and strengthens constraints
  4. Runs a verification pass
  5. Outputs a single usable prompt

Why this approach matters

Most prompt failures come from predictable issues:

  • Constraints appear too late
  • Target model/tool is unclear
  • Instructions are too generic
  • Prompt style doesn’t match model behavior
  • Bad prompts get reused instead of fixed

Prompt Master fixes this by enforcing structure + validation before output.

Key capabilities

Structured intent extraction

Prompts are complete without becoming bloated.

Minimal clarification

Only asks questions when necessary (max 3).

Tool-aware generation

Adapts prompts for:

  • Claude
  • GPT
  • Cursor
  • Gemini
  • Coding environments
  • Reasoning models

Repair mode

Turn weak prompts into production-ready ones without changing intent.

Decompiler mode

  • Break large prompts into components
  • Adapt prompts across tools
  • Clean up messy prompt chains

Built-in quality checks

Every output is validated for:

  • Explicit target tool
  • Constraints early in the prompt
  • Strong directive language (MUST, NEVER, REQUIRED)
  • Removal of ineffective patterns
  • Proper handling of reasoning models

Important clarification (missing in most posts)

One common confusion:

“Where does Prompt Master get its logic/code from?”

Answer:
It doesn’t fetch logic from anywhere.

  • No external API
  • No hidden backend
  • No training pipeline

All behavior comes from:

  • SKILL.md → defines system behavior
  • template-architectures.md → defines structure patterns
  • credit-killing-patterns.md → defines what to avoid

That’s the entire engine.

Installation (quick version)

Claude

  • Upload the repo as a skill
  • Or place it in your local skills directory

Cursor (recommended) 

mkdir -p ".cursor/skills/prompt-master/references"
cp "SKILL.md" ".cursor/skills/prompt-master/SKILL.md"
cp "references/template-architectures.md" ".cursor/skills/prompt-master/references/template-architectures.md"
cp "references/credit-killing-patterns.md" ".cursor/skills/prompt-master/references/credit-killing-patterns.md"
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Reload Cursor → done.

How to use it

Natural:

Write me a prompt for Cursor to refactor an auth module.
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Slash command:

/prompt-master Write me a prompt for Cursor to refactor an auth module.
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Repair:

/prompt-master repair:
"Help me make this code better quickly."
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Decompile:

/prompt-master decompile:
Analyze and split this long prompt for Claude.
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What problems it solves (practically)

  • Eliminates vague prompts
  • Forces clear structure
  • Aligns prompts with the target tool
  • Reduces iteration cycles
  • Makes prompts reusable across teams

Why developers might care

This isn’t just a prompt helper.

It’s closer to:

👉 “Prompt linting + formatting + compilation”

You start treating prompts like:

  • Code
  • Reviewable artifacts
  • Reusable assets

Final thoughts

Prompt Master is simple by design—but that’s the point.

No infrastructure.
No hidden logic.
No abstraction layers.

Just a clean, inspectable system for generating better prompts consistently.

If you already use Claude or Cursor heavily, this can help reduce trial-and-error and make your prompting workflow far more predictable.

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