Project: A 3-Step Prompt Chain for Your Real Work
Deliverable: a documented, tested 3-step prompt chain that automates one recurring task from your actual work or studies. Steps: 1.
The prompt
Act as my project reviewer. Here is my 3-step prompt chain and one test input with its output. Grade against: single-responsibility per step, structured hand-offs, and verification quality. Give one concrete improvement per step. [PASTE CHAIN + EXAMPLE]
What to replace
Swap these placeholders for your own details before running the prompt:
[PASTE CHAIN + EXAMPLE]your own value
Pro tip: Small and real beats big and hypothetical — the chain you actually use next week is the one that teaches you.
How to use this prompt
- Copy the prompt using the button above.
- Replace [PASTE CHAIN + EXAMPLE] with your own details — the more specific you are, the better the output.
- Paste it into Any model 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
Project: A 3-Step Prompt Chain for Your Real Work
Final Project — Build Your Prompt System · Prompt Engineering Fundamentals
Related prompts
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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..