Verified against ChatGPT · 2026-08-11
Synthesize a stack of clinical papers into a structured internal brief a clinician still has to sign off on
Turns a set of paper abstracts or excerpts a healthcare professional has gathered into a structured evidence brief with methodology, effect direction, and limitations laid out per source, framed explicitly as a synthesis aid requiring clinical review before informing any care decision.
The prompt
Ready to copy — highlighted parts are example details you can swap.
You are producing an internal evidence brief for a clinician or clinical researcher who has gathered a set of papers on one question and needs them synthesized into a structured working document — not a final answer to act on directly. CLINICAL QUESTION Does adding structured sleep hygiene counseling improve outcomes for adult patients on first-line treatment for mild insomnia? PAPERS OR EXCERPTS PROVIDED Three abstracts pasted in: a 2019 RCT (n=120) showing modest improvement, a 2021 observational study (n=450) showing no significant difference, and a small pilot (n=24) industry-funded study showing large improvement. INTENDED USE OF THIS BRIEF Internal discussion document for a clinic considering whether to add a counseling protocol, not a patient-facing document. AUDIENCE A small group of primary care physicians and a clinic administrator, all with a research-literacy background. PROCESS For each paper provided, extract only what is actually stated in the excerpt: study design, population/sample size if given, the reported direction and magnitude of effect, and any limitation the authors themselves note — never infer a finding that isn't explicitly present in the text given to you. Group papers by whether their findings point the same direction, point in opposing directions, or are too methodologically different to compare directly (e.g. different populations, different outcome measures), and say so plainly rather than averaging conflicting findings into a single smoothed-over conclusion. Write a short synthesis paragraph per question that describes the state of the evidence as provided (strong and consistent, mixed, thin, contradictory) without translating that into a clinical recommendation — a recommendation is a decision for the clinician using this brief, informed by patient-specific factors this brief has no access to. Flag explicitly anywhere the provided papers are old, small, industry-funded (if stated), or otherwise limited in a way that should temper how much weight the synthesis paragraph gives them. WHAT NOT TO DO Do not search your own general knowledge to fill in gaps the provided papers don't cover, do not cite a study, statistic, or guideline that was not given to you in the input, and do not phrase the synthesis as though it settles the clinical question — it organizes the evidence someone already collected, nothing more. MANDATORY DISCLAIMER Open the brief with a note that this is an evidence-organization aid built only from the material provided, requires independent verification of every source against the original publication, and must be reviewed and interpreted by a qualified clinician or researcher before informing any patient care decision. OUTPUT FORMAT 1. The disclaimer. 2. A per-paper table: citation as given, design, population, reported effect, noted limitation. 3. A grouping section: agreement / disagreement / not comparable. 4. A synthesis paragraph per question, ending in a plain statement of what remains uncertain.
Customize
Optional — swap in your own details for the highlighted parts above.
Why this works
The single biggest risk in literature synthesis tasks is a model quietly supplementing the provided papers with its own general training-data knowledge of a topic, producing a brief that reads as more comprehensive than the actual evidence base the clinician assembled — the explicit instruction to extract only what's stated in the given excerpts, and never to cite anything not provided, closes that gap by keeping the model's role strictly extractive rather than generative on the factual content. Requiring per-paper extraction of design, population, and self-reported limitations before any synthesis forces the model to surface the methodological differences that make studies hard to compare, rather than jumping straight to a smoothed conclusion that hides the fact that a 24-person industry-funded pilot and a 450-person observational study don't actually carry equal evidentiary weight. Grouping into agreement/disagreement/not-comparable, instead of a single blended paragraph, mirrors how an actual evidence review is read by a clinician deciding how much to trust it — averaging conflicting findings into one number is a well-documented failure mode in lay summarization of research and is exactly what this structure prevents. The explicit ban on translating synthesis into a recommendation matters because that is precisely the point where a language model's fluency becomes dangerous: it can produce a confident-sounding "should" statement about patient care with no access to the actual patient, and the brief's whole value is in organizing evidence for someone who does have that context to make the call. The disclaimer is framed around independent verification specifically because a model can misstate what a paper says even when instructed not to, so the clinician using this brief is told upfront to check the brief against the original sources, not just accept the synthesis at face value.
What you get back
Note: Built only from the three abstracts provided; verify each against the original publication before relying on this brief, and have a qualified clinician review it before it informs any care decision. Agreement: none of the three fully agree. Disagreement: the RCT and pilot show improvement, the larger observational study shows none. Limitation flagged: the pilot showing the largest effect is small (n=24) and industry-funded per the abstract, which should reduce how much weight it carries relative to the larger observational study.
Verified against
ChatGPT GPT-5.1 · 2026-08-11
Changelog
- 2026-08-11 — Initial publish, verified against ChatGPT GPT-5.1.
Need this built into your business?
If a prompt isn't enough — what Scult builds, built and maintained for you — that's Scult's day job.
EXPLORE WHAT SCULT BUILDS
