Yesterday, a Claude skill crossed 600 GitHub stars. That number is worth paying attention to.
The project is called prompt-master. A developer named u/CompetitionTrick2836 built it after getting fed up with the most common and expensive problem in AI workflows: bad prompts burning credits and forcing re-runs. The premise is simple. Instead of asking you to get better at prompting every tool manually, the skill writes the accurate prompt for you.
Here’s the twist. This is a Claude skill that writes structured prompts for other AI tools, including Cursor, ChatGPT, Midjourney, Kling, Eleven Labs, and Stable Diffusion. You describe what you want, name the tool you’re targeting, and it routes your request silently to the exact right approach for that specific model. No manual configuration. No toggling settings. No guessing how o1 is different from GPT-4o.
What’s actually packed inside
The core of prompt-master is not a single template. It’s a system that pulls 9 dimensions out of your rough idea before writing anything: context, constraints, output format, audience, memory from prior messages in the session, success criteria, and more. Nothing important gets missed because the skill asks the right questions before generating anything. Think of it as a structured intake form that runs invisibly before any output gets produced.
On top of that, the skill ships with 35 credit-killing patterns, each paired with a before and after example showing the fix. These are real, specific patterns people actually run into. Adding chain-of-thought instructions to o1 models makes performance worse, not better. Skipping the file path when prompting Cursor causes entire requests to miss the mark. Building a whole app in one single prompt instead of breaking it into logical chunks. All 35 patterns are documented. All have concrete fixes. Reading through even a handful of them reshapes how you approach AI tools from that point forward.
Twelve prompt templates round out the system and auto-select based on what you’re doing. Writing an email needs a completely different structure than asking Claude Code to build a feature from scratch. The skill knows this and adjusts automatically. Templates and pattern references also load on demand, meaning only the ones relevant to your specific task get pulled in. Nothing bloated or slow.
🔧 How to get started
The creator says setup takes about 2 minutes. Here’s the basic flow:
- 📥 Find the repo link in the original Reddit post on r/PromptEngineering
- Clone it and follow the setup guide in the README
- Install it as a Claude skill in your environment
- Start a session and specify your target: “I’m using Cursor, I want it to add error handling to this function”
- ⚡ Receive a fully structured, accurate prompt built specifically for that model and task
- Run the prompt. No re-prompts. No wasted credits.
Memory is built in from the start, so the skill tracks context across a long session automatically. You don’t lose the thread halfway through a complex project.
Pro tips worth knowing
For vibe coding sessions with Cursor or Claude Code, start with prompt-master before writing a single line. Let it structure your first prompt properly. One well-structured setup prompt saves you from three frustrating back-and-forth rounds. The time you invest upfront in a solid prompt pays back immediately in cleaner output and fewer correction cycles.
Don’t skip the audience field when generating prompts for visual tools like Midjourney or Kling. Image and video models respond very differently depending on whether you’re using abstract language or specific visual descriptors. The skill’s media tool templates are separate from text tool templates for exactly this reason.
For corporate or school use cases, there are dedicated template contexts for those workflows too. This isn’t only for developers. The creator built it for day-to-day use across all kinds of contexts.
The community feedback loop is tight
v1.4 dropped yesterday, built entirely from user suggestions. v1.5 is already in planning with a focus on agent-based workflows. The iteration speed is real. Open source means every improvement feeds back into the tool and every user benefits from what others report. The GitHub issues tab is active, the creator responds quickly, and feature requests from last week are showing up in this week’s builds.
4,000+ GitHub traffic visits and 600 stars tell you this is not a one-weekend hobby project. It’s being used regularly.
🚀 Worth your 2 minutes
Free, open source, and built for the tools you’re already using every day. Head to the r/PromptEngineering thread to find the repo link and drop feedback directly to the creator. The community is active and suggestions are actually making it into new versions.
Frequently Asked Questions
Q: Do I really need a prompt optimization tool?
Even skilled prompters miss context-specific patterns that waste credits. The skill detects 35 “credit-killing” patterns, things like missing file paths for Cursor or using chain-of-thought with o1 (which actually makes it worse). It’s a safety net, not a replacement for knowing how to write.
Q: Isn’t this just about remembering file paths?
File paths are one of 35 patterns. The skill also routes to tool-specific strategies (Claude Code vs. Midjourney need different structures), auto-selects from 12 task templates, and extracts 9 dimensions from rough ideas. Users report fewer re-prompts and measurable credit savings, especially on complex projects.
Q: How does it support so many different tools?
It detects your target tool and routes to its specific approach, each tool has different strengths and needs different prompt structure. You describe what you want; it adapts automatically.
Q: Is setup complicated?
Takes 2 minutes. You describe your goal in natural language; the skill handles optimization behind the scenes with no special syntax or learning curve.
I built a Claude skill that writes accurate prompts for any AI tool. To stop burning credits on bad prompts. We just hit 600 stars on GitHub‼️
by u/CompetitionTrick2836 in PromptEngineering