Front-load the context

Stop the back-and-forth. Put every fact the model needs into the first message.

The problem

Missing context is the #1 cause of multi-turn 'context setting'. The model asks clarifying questions, you answer, repeat. Each round costs time and tokens.

The fix

Add a CONTEXT block: who the audience is, what inputs/data the model has, and what success looks like. If a fact would change the answer, it belongs in the prompt.

Try it

Add enough context (audience, inputs, goal) to make this one-shot. Aim for 70+.

61structure

Target: 70. Keep working the prompt — the score moves as you type.

Context: Front-load all context the model needs: inputs, audience, goal, and constraints — so it can answer in one shot.
Constraints: State limits and do/don't rules, e.g. "Keep it under 200 words. Do not invent APIs."
Output format: Specify the exact shape, e.g. "Return JSON: { title, steps[] }" or "Use a markdown table.".