Quick version: a mechanical engineering junior built a prompt that reads lab reports the way the toughest TA in the department does, and it will not let you off easy. It flags weak claims, gaps in your methods, and hidden assumptions, then asks a question and stops. No rewrites, no hand-holding.
The original poster, u/InsuranceNeither903, shared this in r/PromptEngineering after losing points report after report for the same three mistakes: claims the data does not back up, methods steps nobody could actually reproduce, and assumptions that never made it onto the page. Instead of hoping to catch these before submission, this student built an AI TA whose entire job is to hunt for them.
The problem behind the prompt
Anyone who has written a technical report knows the trap. You understand your own experiment so well that gaps in the writing become invisible to you. You know you skipped calibrating the sensor before Trial 2, so the report “obviously” implies it. You know your conclusion is a bit of a stretch, but it reads confident on the page. A real TA catches this stuff because they are reading cold, without your mental context filling in the blanks. That is exactly the trick behind this prompt: it strips the model of your context and forces it to read the report the way a stranger with a rubric would.
How the prompt works
The structure is simple, and that is the point. It hands the model two inputs, your draft report and the rubric or assignment sheet, then locks it into a strict role: skeptical, detail-obsessed, and explicitly banned from rewriting anything.
A few choices make it hold up better than a generic “review my report” prompt:
- Role plus constraint. “You are a skeptical TA” sets the lens, and “do not rewrite it, interrogate it” sets the boundary. Most people stop at the role and let the model default back into helpful-editor mode within a few lines.
- A numbered flag list. Four categories: unsupported claims, non-reproducible steps, unstated assumptions, and rubric gaps. Each one targets a specific, common way students lose points, not a vague “check my writing” ask that returns generic notes.
- Exact-line citation. Asking the model to flag “with the exact line” keeps the output tied to the actual text instead of a vague summary you cannot act on directly.
- Ask, then stop. The model raises the question a real TA would ask and stops there. You are still the one who has to think through the answer and fix the report yourself.
That last constraint is also where the author admits the prompt is weakest. It still tries to sneak in a rewrite sometimes, which lines up with a known failure mode: negative instructions like “do not fix it” are easier for a model to slip past than positive ones telling it exactly what to do instead.
Where the thread pushed it further
Two replies are worth stealing before you use this yourself. u/Zain proposed splitting the roles harder: keep the reviewer strictly read-only, flag the line, ask the question, stop, and do the actual fixing in a separate pass so the model never gets a chance to blur the two jobs. u/PhotographOverall126 named the mechanism behind the leaky “do not fix it” rule directly: negative instructions get ignored more often than positive ones, so swapping it for something like “respond exclusively in the form of pointed questions” gives the model far less room to drift back into editing.
Both fixes cost nothing to test. Swap the closing line for the positive version, run your own report and rubric through it, and see whether the rewriting urge actually disappears.
Use Cases 🔍
- 📝 Lab reports and technical write-ups, checked against the rubric before you hit submit.
- 🧾 Grant or funding applications, where unsupported claims and thin methods sections cost real money, not just a letter grade.
- Code review write-ups or incident postmortems, where reproducible steps and claims backed by evidence matter just as much as in a lab.
- Any draft with a rubric or checklist attached, since the “does the data support this” pass generalizes past mechanical engineering.
Prompt of the Day
You are a skeptical, detail-obsessed lab TA grading my report. Do not rewrite it. Interrogate it.
Here is my report:
{{paste your draft}}Here is the rubric or assignment sheet:
{{paste it}}Go through it and flag, with the exact line:
- Any claim in the results or conclusion that the data shown does not fully support.
- Any step in the methods that someone could not reproduce from what I wrote.
- Any assumption I used but never stated.
- Any place the rubric asks for something I didn’t clearly address.
For each, ask me the question the TA would ask, then stop. Do not fix it for me.
Paste your next draft and its rubric into this before you submit, and see how many points it saves you.
Frequently Asked Questions
Q: Why does the model keep trying to rewrite my report instead of just asking questions?
If your model keeps “helpfully” rewriting sections instead of asking questions, your role constraints need to be stricter. Make the reviewer explicitly read-only: no rewrite permission, no suggestions, no corrections , just flag the line and ask the TA question, then stop. The tighter you make the boundaries, the more it’ll stay in interrogation mode.
Q: Should I use the same AI model that helped me draft my report to critique it?
No , critics from the same model family tend to share the same blind spots as the original. Zain recommends running the critique on a different model family (e.g., if Claude helped you draft, use GPT or Gemini for the skeptical review). This catches gaps and assumptions that the original model missed because they’re baked into how it thinks.
Q: How do I stop the model from filling in gaps using its own knowledge of the subject?
Set an explicit “Information Boundary” at the top of your prompt. Tell it to use only what’s in your report and rubric, flag missing details rather than assume what you probably did, and distinguish explicitly stated information from missing information. This keeps it from hallucinating plausible-sounding steps you forgot to write.
Q: Is it okay if the model gives me a clean pass with no issues found?
Absolutely , if the model genuinely finds nothing after close inspection, that’s a real signal you’ve covered the bases. If it finds an issue on every single pass just to look thorough, that’s a red flag. Trust a clean pass when it’s actually earned.
Q: Which critique pass tends to catch the most points worth of mistakes?
The reproducibility check is the highest-impact , it catches steps you’ve skipped or explained unclearly in your methods, and these gaps often cost the most points. The “data support” pass (checking if your claims are backed by your data) catches overreach in conclusions, which is also a common point-killer. Focus those two first.
Here’s a prompt that reads your lab report like a skeptical TA and finds the holes before they do
by u/InsuranceNeither903 in PromptEngineering