Grant Narrative — Biomedical
Structure the full proposal narrative against the funder's criteria. Purpose-built for biomedical contexts.
A structured researcher prompt for grants & peer review: structure the full proposal narrative against the funder's criteria, tailored to biomedical research with wet-lab methods and clinical relevance. It walks the model through a proven process with an explicit quality bar, and delivers a narrative outline.
The prompt
Variables to fill in: {{project_content}}{{context}}
You are a grant-review panelist and journal referee who knows what makes proposals fundable and reviews useful. I need your help in the context of biomedical research with wet-lab methods and clinical relevance.
TASK: Structure the full proposal narrative against the funder's criteria.
DELIVERABLE: Produce a narrative outline: section-by-section content mapped to review criteria, the preliminary-data placement strategy, the feasibility evidence per aim, and the reviewer-fatigue design (headers, figures, whitespace).
PROCESS:
1. Review the inputs below. If anything critical is missing or ambiguous, ask me up to three clarifying questions before producing the deliverable.
2. Read as the audience: a tired panelist skimming proposal #14, or an editor triaging reviews — clarity and structure decide outcomes.
3. Anchor every judgment to the stated criteria (significance, innovation, feasibility, rigor) with evidence from the text.
4. Be constructive with teeth: every criticism paired with what would fix it.
5. Produce the deliverable in a clean, skimmable format I can use directly.
QUALITY BAR:
- Aims/claims are specific, measurable, and connected to a coherent payoff.
- Feasibility is demonstrated, not asserted — preliminary evidence and fallback plans.
- Reviews are fair, specific, and free of status games.
INPUTS:
- The research project/proposal/manuscript material to work from: {{project_content}}
- Funder/venue, career stage, deadline, and the criteria used: {{context}}Try it out
Open in Playground →Run this prompt on a real model without leaving the page. Every run is saved to your history for this prompt.
Fill in the variables
How to use
- 1Fill in the {{project_content}}, {{context}} variables with your real details — specifics in, specifics out.
- 2Paste the prompt into ChatGPT, Claude, Gemini, or any capable model.
- 3Answer the clarifying questions it asks; that step is what makes the output fit your situation.
- 4Iterate on the deliverable: ask for alternatives, tighter versions, or a different angle on any section.
Pro tips
- If the output feels generic, add more concrete detail to the inputs — names, numbers, and constraints sharpen everything.
- Works well in a thread: keep the conversation going to refine a narrative outline.