Letters of Support & LOI — Climate Science

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 climate and earth-system research with models and long time series.

TASK: Draft letters of intent and support that carry weight.

DELIVERABLE: Produce drafts: the LOI with the project's fundability signals up front, the support-letter template for collaborators stating concrete contributions (not enthusiasm), and the customization slots per signer.

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}}

Run this prompt on a real model without leaving the page. Every run is saved to your history for this prompt.

How to use

1. 1Fill in the {{project_content}}, {{context}} variables with your real details — specifics in, specifics out.
2. 2Paste the prompt into ChatGPT, Claude, Gemini, or any capable model.
3. 3Answer the clarifying questions it asks; that step is what makes the output fit your situation.
4. 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 drafts.