The Anatomy of a Great Prompt: 7 Building Blocks

Great prompts rarely feel clever. They feel complete — the model is never left guessing what you want, who it's for, or what "good" looks like. When a prompt reliably produces useful output, it almost always contains the same seven parts. Miss one and you get the vague, hedging answers everyone complains about.

The seven building blocks

1. Role — who the model should be. "You are a senior tax accountant" narrows vocabulary, assumptions, and depth in one line.
2. Context — the situation and background the model can't infer. Who's the audience, what's already been tried, what matters here.
3. Task — the single, explicit thing you want done. One prompt, one job. If you're asking for three things, you probably want three prompts.
4. Format — the exact shape of the output. Bullet list, table, JSON, 200 words, headings. Ambiguity here is where most "close but not usable" answers come from.
5. Constraints — the guardrails. Tone, reading level, what to avoid, hard limits ("no more than 5 items", "cite a source for each claim").
6. Examples — one or two samples of the input-to-output you expect. A single good example does more than three paragraphs of description.
7. Evaluation — how the model should check its own work before answering ("verify each number adds up; flag anything you're unsure about").

Most weak prompts have the task and nothing else. Adding even three of the remaining six transforms the output.

A copy-ready skeleton

Role: You are a [role].
Context: [audience, situation, what's been tried].
Task: [one clear objective].
Format: [structure, length, style].
Constraints: [must include / must avoid / limits].
Example: [one input → output pair].
Before answering: [self-check step].

Fill it in top to bottom and you'll have covered every block above. You don't always need all seven — a quick rewrite doesn't need an example — but you should consciously skip them, not forget them.

Where to go from here

If assembling this by hand every time sounds like work, that's exactly what our AI Prompt Refiner automates: paste a rough one-liner and it expands it into the structured shape above, tuned to the model you're targeting. And if you'd rather start from something proven, browse prompts already built on these blocks and adapt from there.

The habit worth building: when an answer disappoints, don't rewrite the whole prompt — ask which block was missing. Nine times out of ten it's Format or Constraints, and adding one sentence fixes it.