Prompt Master: Accurate Prompts for Any AI Tool

Prompt Master: A Detailed Guide to Precision Prompts for Any AI Tool

Introduction In the rapidly evolving world of AI, the quality of a prompt often determines the quality of the output. Prompt Master stands out as a Claude skill that promises to write accurate prompts for any AI tool—without wasting tokens or credits. It blends full context retention, memory, and a disciplined, structured approach to prompt generation. The goal is simple: give you the exact prompt you need on the first attempt, every time. This guide dives into what Prompt Master is, how it works, and how you can deploy it to maximize your AI workflows across tools—from Claude and ChatGPT to Midjourney, Stable Diffusion, and countless coding and data tools.

What Prompt Master Is

• A structured, tool-aware prompting engine that translates vague user intent into precise, copyable prompts tailored to the target AI system.
• It detects the target tool from the request, extracts a rich set of intent dimensions, asks targeted clarifying questions, selects the right prompt architecture, and applies safe, proven techniques.
• It emphasizes token efficiency, ensuring every word adds value and trimming redundancies that waste money and time.
• It works with a wide spectrum of tools, including but not limited to Claude, ChatGPT, Gemini, Midjourney, DALL-E, Stable Diffusion, Runway, ElevenLabs, Zapier, Make, and more. If a tool isn’t listed, Prompt Master uses a universal fingerprint to craft a high-quality prompt for it.

The Problem Prompt Master Solves

• Real users waste money and time by prompting vaguely: vague prompt → wrong output → re-prompt → closer → finally useful after multiple attempts.
• The cost compounds with high-frequency usage. Even dozens of prompts per day can lead to significant spend and lost productivity.
• The core insight is crisp: “The best prompt is not the longest. It’s the one where every word is load-bearing.” Many prompt generators rely on length; Prompt Master sharpens prompts so every word matters.

A Key Insight: Load-Bearing Prompts

• The most effective prompts are engineered so every word serves a purpose.
• Rather than merely adding length, the skill emphasizes precision, structure, and constraints that prevent drift.
• This approach reduces wasted cycles, improves reproducibility, and helps non-native users achieve consistent results across tools.

How It Works: A Seven-Step Prompt Pipeline Prompt Master runs a disciplined pipeline on every request. Here is the core flow you’ll experience:

1) Detect the Target Tool

• The system identifies the AI tool at hand and routes the request to the appropriate prompt architecture without exposing you to the underlying framework.

2) Extract Nine Dimensions of Intent

• Task: what you want the AI to do
• Input: any provided data to analyze or transform
• Output: the expected form of the result
• Constraints: limits on style, length, or structure
• Context: background information or project scope
• Audience: who will read or use the result
• Memory: what should be remembered across sessions
• Success Criteria: explicit completion conditions
• Examples: sample inputs/outputs to guide behavior

3) Ask Targeted Clarifying Questions

• If critical information is missing, it prompts you with up to three precise questions to fill the gaps.

4) Route to the Right Framework

• The system automatically applies the correct prompt architecture for the task, keeping the user-facing view clean and focused.

5) Apply Safe Techniques Only

• Role assignment, few-shot examples, XML structure, grounding anchors, and a memory block as needed to stabilize results and reduce hallucinations.

6) Run a Token Efficiency Audit

• It strips any word that does not concretely influence the output, ensuring you don’t pay for fluff.

7) Deliver the Prompt

• You receive one clean, copyable block of text, along with a one-line strategy note for context.

Full Examples: How Prompt Master Produces Prompts

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 (illustrative): 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: Use comma-separated descriptors early; anchor lighting and mood; fix aspect ratio and version; use a negative prompt to prevent 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 (illustrative): 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: [detailed design spec follows] Sections to build in order: Navbar, Hero, Logos bar, Features, How it works, Pricing, CTA, Footer. Each section should be implemented with precise color values, spacing, and responsive rules. Include placeholders for images and ensure accessibility and keyboard navigation. Animations: fade-in, translate, staggered card animations, hover states, and smooth scrolling. Single-file deliverable with embedded CSS and JS; no external dependencies beyond Google Fonts.

• Target: Claude Code

• Framework: PAC2026-inspired Template (concealed to user)

• Tokens: Medium (~380)

• Strategy: Translate every Notion aesthetic cue into exact hex values and pixel specs; lock animation timing and triggers; ensure a single-file, dependency-free deliverable.

Tools and Compatibility: Works With Any AI Tool Prompt Master is designed to adapt to a broad ecosystem. It includes specific profiles for 20+ tools and uses a Universal Fingerprint for anything outside the known set:

• 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 more.
• The Universal Fingerprint: when faced with an unfamiliar tool, it asks four targeted questions to craft a high-quality prompt for the new system.

12 Prompt Templates (Auto-Selected) Prompt Master automatically selects the best architecture for the task and routes the prompt behind the scenes. Here are the templates it can pick from, without exposing the user to the framework name:

• RTF (Role, Task, Format)
• CO-STAR (Context, Objective, Style, Tone, Audience, Response)
• RISEN (Role, Instructions, Steps, End Goal, Narrowing)
• CRISPE (Capacity, Role, Insight, Statement, Personality, Experiment)
• Chain of Thought
• Few-Shot
• File-Scope Template
• ReAct + Stop Conditions
• Visual Descriptor
• Reference Image Editing
• ComfyUI
• Prompt Decompiler

5 Safe Techniques, Applied When Needed Prompt Master uses a curated toolkit to limit hallucinations and maintain control:

• Role Assignment: Calibrate depth by giving the AI an expert identity
• Few-Shot Examples: Add 2–5 examples when format consistency matters
• XML Structural Tags: Wrap sections in XML for reliable parsing (where supported)
• Grounding Anchors: Anti-hallucination rules for factual tasks
• Chain of Thought: For logic tasks, it’s used sparingly (and not for certain models)

Credit-Killing Patterns: 35 Patterns to Avoid Prompt Master documents patterns that drain tokens or degrade results and offers tangible before/after examples. While the full tables are extensive, the essence can be summarized as follows:

• Task Patterns (7 categories): Avoid vague verbs, combining tasks, missing success criteria, over-permissive agents, emotional descriptions, “build the whole thing,” and implicit references.
• Context Patterns (6 categories): Always include memory blocks, ensure project context is present, avoid forgotten stacks, cite sources, clarify audience, and restate prior failures explicitly.
• Format Patterns (6 categories): Define exact output formats, prevent implicit lengths, specify roles, fix aesthetic adjectives, and avoid undirected image prompts (with explicit negative constraints when needed).
• Scope Patterns (6 categories): Set clear boundaries, prescribe stack constraints, enforce stop conditions, pin exact file paths, and choose the correct template for the tool.
• Reasoning Patterns (5 categories): Prefer structured reasoning with clear steps where appropriate; avoid forcing internal CoT for tools that degrade performance; include self-checks to verify correctness.
• Agentic Patterns (5 categories): Define starting states, target states, permission gates, memory constraints, and human review triggers to maintain safe, auditable progress.

Memory Block System: Keeping Context Across Sessions To prevent the common pitfall of forgetting prior decisions, Prompt Master uses a Memory Block. This block is prepended to the AI’s context so it remembers critical decisions and project conventions across turns:

• Memory example (Carry Forward from Previous Context):
• Stack: React 18 + TypeScript + Supabase
• Auth uses JWT in httpOnly cookies
• Component naming: PascalCase
• Design system: Tailwind only
• Architecture: No Redux; use Context API
• The Memory Block is the single most effective fix for long sessions and repeated prompts.

Version History Highlights

• 1.6.0: Opus 4.7 update; added Template M; improved routing; expanded patterns.
• 1.5.0: More tool routing; new Agentic AI and 3D Model AI routing; description refined.
• 1.4.0: Reference image editing detection; added ComfyUI support; Prompt Decompiler mode.
• 1.3.0: PAC2026-inspired reorganization; silent routing; references folder introduced.
• 1.2.0: Attention architecture restructuring; removed several risky techniques; templates moved to references.
• 1.1.0: Expanded tool coverage; memory block system; added 35 credit-killing patterns.
• 1.0.0: Initial release

Installation: How to Add Prompt Master to Claude or Any Tool

• Recommended path: Claude.ai (browser) 1) Download this repository as a ZIP 2) In Claude.ai, go to Sidebar → Customize → Skills → Upload a Skill
• Alternative path: Clone into Claude Code skills directory (not the most recommended)
• Commands:
  • mkdir -p ~/.claude/skills
  • git clone https://github.com/nidhinjs/prompt-master.git ~/.claude/skills/prompt-master
• After installation, you can invoke the skill in Claude with natural language commands, for example:
• 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

What This Means for Your AI Workflow

• Efficiency gains: Fewer prompts, fewer credits wasted, faster route to helpful outputs.
• Consistency: A stable, repeatable approach to prompting that reduces variability across runs and tools.
• Memory-aware collaboration: Long-running sessions retain decisions and preferences, making complex projects far more manageable.
• Tool-agnostic design: Because the system recognizes the target tool and applies the right architecture, you’re not locked into a single ecosystem.

Visual and Practical Details: What You’ll See

• Clear prompts with precise structure: A single, clean copy block that you can paste directly into the target tool.
• Memory blocks and decision trail: When used, you’ll notice consistent behavior across sessions, with remembered constraints and preferences.
• Targeted, minimal questions: If details are missing, the system asks only what’s essential, up to three questions.
• Safe, boundaries-first approach: Role assignments, grounding anchors, and explicit task boundaries prevent drift and unwanted exploration.

Why You’ll Love Prompt Master

• It respects your time and budget by focusing on load-bearing language, not verbose prose.
• It adapts to a wide range of AI systems, so you don’t need to learn multiple prompting styles.
• It keeps your project coherent through a memory block, ensuring consistency across conversations.

A Quick Start Summary

• Install via Claude.ai or preferred route.
• Provide a concise task or prompt idea.
• Let the system detect the target tool and extract intent.
• Answer any clarifying questions if prompted.
• Receive a single, ready-to-use prompt tailored to the target tool, with optional notes on strategy.

Closing Thoughts Prompt Master offers a disciplined, methodical approach to prompting—one that prioritizes clarity, efficiency, and safety across the wide landscape of AI tools. By focusing on load-bearing words, precise structure, and a robust memory system, it helps you achieve reliable, high-quality results on the first attempt. Whether you’re drafting prompts for image generation, coding assistants, data analysis, or multi-tool workflows, Prompt Master is designed to translate your intent into exactly the right prompt—no fluff, no guesswork, just the output you need.

Images and Visual Elements from the Input

• Banner image: Prompt Master banner at the top of the post provides immediate visual context to readers and anchors the piece in the brand’s identity.

Section-by-Section Recap

• Introduction explains the promise of prompt precision across tools.
• The Problem and Key Insight frame the motivation behind Prompt Master.
• The How It Works section breaks down the seven-step pipeline in accessible terms.
• Full Examples illustrate practical outcomes (image prompts and coding prompts).
• Works With Any AI Tool demonstrates broad compatibility and the universal fingerprint approach.
• The Templates, Safe Techniques, Credit Patterns, and Memory Block sections offer a deep dive into the mechanisms that prevent waste and drift.
• Installation provides practical steps to get started with Claude or other tools.
• Version History, Licensing, and Closing Thoughts provide a complete, rounded view of the project’s lifecycle.

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