Key points
- Ask for output formats that force grounding: citations, study summaries, and uncertainty.
- Use constraints (population, setting, timeframe) to reduce irrelevant retrieval.
- Always include a ‘limitations’ clause to avoid confident overreach.
The core skill is not ‘prompting’ — it’s structured questioning. You’re trying to force the model into evidence-first behaviour: cite, summarise, and declare uncertainty.
1
Prompt 1 — Evidence table
“Give me a table: Recommendation | Evidence source | Year | Key limitation | Where it applies.”
2
Prompt 2 — Guideline alignment
“Summarise how major guidelines differ on this question and why.”
3
Prompt 3 — What would change the answer
“List the patient factors or setting constraints that would change your recommendation.”
4
Prompt 4 — Counter-evidence search
“Find the strongest counterargument or evidence that would contradict the top conclusion.”
5
Prompt 5 — Practical implementation
“If I had to implement this in a time-pressured setting, what is the minimum safe plan and what are the stop-triggers?”
SourceOpenEvidence: Product entry point
Open Link SourcePeer-reviewed overview referencing OpenEvidence’s RAG approach (PMC)
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“Give me a table: Recommendation | Evidence source | Year | Key limitation | Where it applies.”
Return to this section“Summarise how major guidelines differ on this question and why.”
Return to this section“List the patient factors or setting constraints that would change your recommendation.”
Return to this section“Find the strongest counterargument or evidence that would contradict the top conclusion.”
Return to this section“If I had to implement this in a time-pressured setting, what is the minimum safe plan and what are the stop-triggers?”
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