TL;DR: Most AI reports bury the actual finding under a paragraph explaining why the topic matters. This prompt forces the finding into sentence one and bans the filler entirely.
Here’s the thing about ask-for-a-report prompts. You get an intro nobody asked for, then the numbers hiding somewhere in paragraph three, then a closer that starts with “in summary” like you forgot what you just read. Reddit user raw-hit10 got tired of that and flipped the whole order.
The Prompt
Data: [PASTE NUMBERS / BULLET POINTS]
Audience: [WHO reads this and what decision they make]
Write a short report with this order:
- The single most important finding, in one sentence, first.
- Two or three supporting points, each starting with the number then what it means.
- One thing that looks off or needs a decision.
Rules:
- No introduction about why the topic matters
- No “in conclusion”
- Do not describe a number without saying why it matters to the audience
- If the data does not support a claim, say “not enough data” instead of guessing
Why It Works
Three things are doing the heavy lifting here, and it’s worth knowing which one to lean on if you’re adapting this for your own reports.
- The “no introduction” rule kills the throat-clearing paragraph. That’s where almost all AI filler lives, right at the top, explaining a topic you already know.
- Tying every number to the audience’s decision stops the model from listing stats nobody asked for. A number without a “so what” is just noise.
- “Not enough data” is the guardrail against the model’s favorite trick: drawing a trend line through two points because a trend sounds more confident than a shrug.
One commenter added a fourth rule worth stealing: append “every sentence must contain a number or a call to action” at the end. That closes the loophole where the model tries to sneak a vague wrap-up sentence back in anyway.
Use Cases
- Weekly metrics recap for a manager who just wants to know what changed
- Ad spend or campaign summary before a budget decision
- Customer feedback themes for a product team deciding what to fix next
- Support ticket trends for whoever’s staffing next week
Prompt of the Day
Copy the prompt above, drop in your numbers and your audience, and run it once before your next status update. Then check the last line. If it drifted back into a summary paragraph, add the “every sentence needs a number or a call to action” rule and run it again.
Try this on your next report and see how much shorter it gets when the model can’t hide behind an introduction.
Frequently Asked Questions
Q: My report still ends with a summary paragraph. How do I kill that?
The core rules cut obvious filler but trailing summaries can sneak back in, they’re baked into model training. Try adding this meta-rule at the end of your prompt: “every sentence must contain a number or a call to action.” It forces the model to justify every sentence and eliminates soft conclusions that don’t contribute.
Q: Do I need all four rules, or which one matters most?
The “no introduction about why the topic matters” rule is the heavyweight. That’s where most AI filler accumulates. The others (single finding first, tie numbers to audience decisions, “not enough data”) all matter for edge cases and enforcement, but removing the intro is the biggest win against waste.
Q: What if I only have a couple of data points?
Don’t let the model extrapolate. Use “not enough data” instead to flag uncertainty. This prevents models from confidently inventing trends from thin evidence. It’s especially important with small datasets where the model loves to fill gaps.
Here’s a prompt that turns raw numbers into a readable report without the usual AI report generator filler
by u/raw-hit10 in PromptEngineering