What is a Prompt Scorecard?

A Prompt Scorecard is a tool that evaluates the quality of your AI prompts against 15 key criteria for effective prompt engineering. It helps you identify areas for improvement and provides specific feedback to make your prompts more effective with AI models like ChatGPT, Claude, and others.

How does the scoring system work?

Your prompt is evaluated on a scale of 1-5 across 15 different criteria including clarity, context, task definition, output format, and more. The maximum possible score is 75. Scores of 60+ indicate excellent prompts, 40-59 are good but could use improvement, and below 40 need significant revision.

Is this tool free to use?

Yes! The Prompt Scorecard is completely free to use. You can analyze unlimited prompts and get detailed feedback on each one. No credit card or signup required.

What makes a good AI prompt?

A good AI prompt is clear, specific, and includes context. It defines the task explicitly, specifies the desired output format, and may include examples. The prompt should avoid ambiguity and be structured in a way the AI can easily follow.

Can I share my scorecard results?

Yes! After analyzing your prompt, you can click the "Share This Scorecard" button to generate a unique shareable link. This link allows others to view your prompt analysis results.

Does this work with all AI models?

The scoring criteria are based on universal prompt engineering best practices that apply to all major AI language models including ChatGPT (GPT-3.5/GPT-4), Claude, Gemini, and others. Well-scored prompts will generally perform better across all models.

🎯 Agentic Workers Tool

Prompt Engineering
Scorecard

Evaluate the quality of your AI prompts against 15 key criteria. Get detailed feedback and improve your results with ChatGPT and other AI models.

Enter Your Prompt

0/100 characters minimum

Prompt Evaluation Criteria

Your prompt will be evaluated against 15 key criteria for effective prompt engineering. Each criterion is rated on a scale of 1-5, with a maximum total score of 75.

Clarity & Specificity

Context / Background Provided

Explicit Task Definition

Desired Output Format / Style

View all 15 criteria

Prompt Analysis Results

Enter your prompt to get started

Our AI will analyze your prompt and provide a detailed score with improvement suggestions.

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The 15 Criteria for Effective Prompts

1. Clarity & Specificity

Is the request clearly stated without ambiguity? Does the prompt avoid vague or broad language? Does it specify exactly what needs to be done?

2. Context / Background Provided

Does the prompt include any important context, references, or background info? If the model needs domain knowledge, is that knowledge provided (via text, examples, or summarized references)?

3. Explicit Task Definition

Does the prompt clearly define the task, including any constraints (e.g., time limit, length limit)? Are sub-tasks or steps outlined if needed (instead of lumping everything into one statement)?

4. Desired Output Format / Style

Is the requested output format specified (e.g., bullet points, JSON, paragraph, code snippet)? Is the tone or style (formal, casual, academic, etc.) stated if relevant?

5. Instruction Placement & Structure

Are instructions separated from input data (e.g., with clear delimiters like triple backticks)? Is it obvious what is command vs. what is content for the model to act on (especially when providing large text excerpts)?

6. Use of Role or Persona (If Applicable)

If relevant, is a role/persona or point-of-view assigned (e.g. "You are an AI tutor")? Does the persona or role help the model understand the style or level of expertise expected?

7. Examples or Demonstrations (Few-Shot Prompts)

If the task is non-trivial, are one or more examples provided? Do the examples clearly show input → output pairs in the desired format? Is the prompt using zero-shot, one-shot, or few-shot examples effectively based on task complexity?

8. Step-by-Step or Chain-of-Thought Guidance (If Needed)

For complex tasks, does the prompt encourage reasoning steps (e.g., "Show your thought process," "Explain step by step")? If not needed, did you keep the prompt concise and direct?

9. Avoiding Common Pitfalls / Negative Triggers

Does the prompt avoid contradictory or overly negative instructions ("Don't do X" without positive guidance)? Are there any ambiguous references that the model could misunderstand? Is the scope limited enough to prevent confusion or tangential answers?

10. Iteration & Refinement Potential

Does the prompt invite refining or verifying the answer? (e.g., "Check your work," "If unsure, say so.") If relevant, do you plan multiple turns or a fallback approach if the first response is off?

11. Model & Scenario Fit

Is the prompt tailored to the model's strengths (text LLM vs. image model vs. code model)? Are you using the right approach for the scenario (e.g., chain-of-thought for math tasks, style modifiers for image creation, docstring approach for code generation)?

12. Length / Brevity vs. Detail

Is the prompt detailed enough to avoid confusion but not so long that it becomes unwieldy? Are the essential instructions front-loaded, so they don't get lost in a long paragraph?

13. Clear Audience Specification (If Relevant)

If the response is meant for a particular audience (e.g., "Explain to a 5-year-old," "Explain to senior executives"), is that stated? Does the prompt direct the level of detail or complexity required by that audience?

14. Structured or Numbered Instructions

If multiple distinct tasks are requested, are they separated (e.g., using bullet points or enumeration)? Is the sequence in which the model should do the tasks clearly indicated? (e.g., "First do X, then do Y.")

15. Realism in Constraints & Feasibility

Are your requests actually feasible given the model's capabilities and knowledge cutoff? If it's a domain where the model lacks training, do you provide the needed references or data?

How to Use Your Score

1. Review your detailed breakdown to identify your strengths and weaknesses.

2. Focus on improving the criteria where you scored lowest.

3. Refine your prompt based on the AI suggestions.

4. Re-analyze your improved prompt until you achieve an excellent score.

5. Test with real AI models to see improved results.

What People Say About Agentic Workers

James Miller

Marketing Manager

"After optimizing my prompts with Agentic Workers, our content creation process is 3x faster. The prompt library alone saved us countless hours of trial and error."

Sarah Kim

Product Designer

"The quality of AI outputs I'm getting now is night and day compared to before. Agentic Workers taught me how to structure prompts to get exactly what I need every time."

Thomas Davis

Developer

"I was skeptical about AI tools, but Agentic Workers changed my mind. Their prompt techniques have helped me build and document features in half the time."

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