Self-Grading With a Rubric
Have the model score its own draft against an explicit rubric, then revise to hit the top score.
The prompt
Write a 100-word product pitch for [PRODUCT]. Then score it 1-5 on: clarity, specificity, and persuasiveness. If any score is below 5, revise and show the final version only.
What to replace
Swap these placeholders for your own details before running the prompt:
[PRODUCT]your own value
Pro tip: Give the rubric criteria explicitly — "clarity, specificity, persuasiveness" — so the self-grade is consistent, not vibes-based.
How to use this prompt
- Copy the prompt using the button above.
- Replace [PRODUCT] with your own details — the more specific you are, the better the output.
- Paste it into Claude and run it.
- If the answer feels generic, add constraints: audience, length, tone, and what to avoid. That single change fixes most weak output.
Learn the technique
Self-Grading With a Rubric
Module 4 — Prompt Patterns That Fix Bad Output · Prompt Engineering Fundamentals
Related prompts
The 5-Part Prompt Framework — ChatGPT
Every strong prompt combines five parts: Role (who the AI should act as), Context (background info it needs), Task (the specific ask), Format (how you want the output structured), and Constraints (length, tone, things to avoid).
ClaudeThe 5-Part Prompt Framework — Claude
Every strong prompt combines five parts: Role (who the AI should act as), Context (background info it needs), Task (the specific ask), Format (how you want the output structured), and Constraints (length, tone, things to avoid).
ChatGPTZero-Shot vs Few-Shot Prompting — ChatGPT
Zero-shot means asking directly with no examples.
GrokZero-Shot vs Few-Shot Prompting — Grok
Zero-shot means asking directly with no examples.
ChatGPTChain-of-Thought Prompting — ChatGPT
Asking a model to "think step by step" before answering measurably improves accuracy on reasoning, math, and multi-step logic tasks because it forces the model to externalize intermediate steps instead of jumping to a guess..
ClaudeChain-of-Thought Prompting — Claude
Asking a model to "think step by step" before answering measurably improves accuracy on reasoning, math, and multi-step logic tasks because it forces the model to externalize intermediate steps instead of jumping to a guess..
Topics
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