AI Prompt Improver
Paste any AI prompt and get an instant quality score across 7 dimensions, plus an improved version ready to copy.
Why Your AI Prompts Are Not Working the Way You Expect
If you have ever typed a question into ChatGPT or Claude and felt like the answer missed the point, you are not alone - and it is almost never the AI's fault. The response you get is only as good as the instructions you give. That is the core idea behind prompt engineering: writing instructions that leave no room for the AI to guess.
This tool scores your prompt across 7 dimensions and rewrites it to close every gap it finds, so you can immediately see - and copy - a version that works better.
The 7 Things Every Good Prompt Should Cover
Think of a prompt like a job brief you hand to a new hire. If you leave out key details, they will make assumptions - and those assumptions may not match what you had in mind.
- Clarity - Can your request be misread? "Write something about social media" could produce a history lesson, a marketing guide, or a personal essay. "Explain how the Instagram algorithm ranks posts, for a small business owner" cannot be misread.
- Specificity - Vague requests produce vague answers. Adding concrete details - word count, a deadline, a specific constraint - tells the AI exactly how much work to do and where to stop.
- Context - The AI has no idea who you are or why you need this. A sentence of background ("I am building a landing page for a fitness app targeting beginners") changes everything about how the response is shaped.
- Role / Persona - Starting with "Act as a senior copywriter" or "You are a patient tutor explaining to a 12-year-old" unlocks a focused subset of the AI's knowledge and shifts its tone immediately. This is one of the fastest wins for beginners.
- Output Format - If you do not specify a format, you will get a wall of prose. Ask for a bullet list, a table, step-by-step numbered instructions, or a JSON object and you will never need to copy-paste into a formatter again.
- Examples - Showing one example of what you want is worth ten lines of description. Even a rough sample removes the AI's biggest source of ambiguity: what your ideal output actually looks like.
- Tone / Style - "Professional", "casual and friendly", "technical for senior engineers", "ELI5" - without this, the AI defaults to a generic middle ground that rarely fits your actual audience.
A Before and After to Make It Concrete
Before (scores ~3/14):
Write me a cover letter.
The AI will write something, but it will be generic. It does not know your name, the job, the company, your experience, or the tone you want.
After (scores ~13/14):
Act as an experienced career coach. Write a cover letter for a junior front-end developer with 1 year of experience applying for a remote role at a fintech startup. Highlight adaptability and a passion for clean UI. Keep it under 250 words and use a confident but approachable tone.
Same task. Completely different output. The only difference is filling in the 7 dimensions.
How to Use This Tool as a Beginner
You do not need to know anything about prompt engineering before you start.
- Paste any prompt you have written - even a rough one-liner
- Click Analyze My Prompt
- Read the per-dimension breakdown to see exactly what is missing
- Copy the improved version and use it directly in ChatGPT, Claude, or Gemini
- Come back to analyze your next prompt - within a few sessions you will start writing better prompts from scratch
The goal is not just to get a better prompt today. It is to build the habit of thinking in all 7 dimensions so you eventually do not need the tool at all.
No. That is exactly what this tool is for. Paste whatever you have written - even a rough draft - and the tool will show you which dimensions are missing and rewrite it for you. Reading the per-dimension feedback a few times is usually enough to internalize the pattern.
A good prompt covers 7 dimensions: clarity (unambiguous request), specificity (concrete details and constraints), context (who you are and why you need this), role (a persona for the AI to adopt), output format (structure or length), examples (sample output), and tone (audience or style). Most first-draft prompts cover 2-3 of these. Covering all 7 is what separates responses that feel generic from ones that feel tailored.
The improved prompt works with any large language model - ChatGPT (GPT-4o), Claude (Haiku, Sonnet, Opus), Gemini, Mistral, and others. The improvements target structural weaknesses, not quirks of any specific model, so the same prompt will perform better across all of them.
A prompt can feel detailed and still miss entire dimensions. "Write a 3000-word article on Kubernetes networking with code examples" scores well on specificity and format but scores 0 on role, context, and tone. The rubric catches structural gaps that feel invisible until you see them labelled.
No. Your prompt is sent to the scoring API to generate the analysis and improved version, then immediately discarded. It is never stored, logged, or used to train any model.
Each of the 7 dimensions is scored 0 (absent), 1 (partially addressed), or 2 (fully covered), for a maximum of 14. Scores of 12-14 are excellent, 9-11 are good, 5-8 need work, and 0-4 are poor. The model runs at temperature 0, so the same prompt will receive the same score on every run.
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