Prompt Library

ChatGPT grant prompts that respect the funder's rubric and your actual program data

15 copy-paste prompts

Paste the RFP, your outcomes data, and the budget notes you have. ChatGPT drafts narrative sections and tags missing proof as [VERIFY]. Your grants team verifies every number.

In short: This page contains 15 copy-paste ready prompts, organized into 5 categories with a description and pro tip for each. The first 5 prompts are free instantly, no signup needed. Hand-curated and tested by the AI Academy team.

Louis Corneloup
By Louis Corneloup · Founder, Techpresso
Last updated ·Hand-curated & tested by the AI Academy team

Decode the funder

3 prompts

Rubric to checklist

1/15

✨ What it does

ChatGPT turns grant guidelines into a section checklist with limits and attachments. Confirm [VERIFY] limits against the portal before you outline.

Here is the grant guidelines: [PASTE]. Build a checklist: section, word or page limit, required attachments, scoring criteria if listed. Unknown limits [VERIFY].

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Pro tip: Funders repeat the same hidden attachment twice. Checklist beats memory.

Alignment paragraph

2/15

✨ What it does

ChatGPT writes one alignment paragraph linking funder priorities to your program summary. Cut or strengthen every [VERIFY] sentence with real partnership facts.

Funder priorities: [PASTE]. Our program: [PASTE PROGRAM SUMMARY]. Write one alignment paragraph in funder language without inventing shared history. Tag weak fits [VERIFY].

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Pro tip: Alignment is not flattery. Cite a priority word from their doc in each claim.

Eligibility sanity check

3/15

✨ What it does

ChatGPT marks eligibility requirements met or VERIFY from guidelines and org facts. Resolve VERIFY with your grants officer before you draft 40 pages.

From these guidelines: [PASTE] and our org facts: [PASTE ORG FACTS], list eligibility requirements and mark met, not met, or VERIFY for each. No legal advice.

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Pro tip: Stop early on a hard not met. ChatGPT will not save an ineligible org.

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Needs and case

3 prompts

Needs statement

4/15

✨ What it does

ChatGPT drafts a needs statement from your sourced stats with inline cites. Replace [VERIFY] with citable data before the program officer reads it.

Draft a needs statement for [POPULATION] in [GEO]. Data I have: [PASTE STATS AND SOURCES]. Structure: problem, who is affected, why now, gap. Cite sources inline. Tag missing stats [VERIFY].

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Pro tip: One local stat you can defend beats five national stats you cannot source.

Beneficiary story frame

5/15

✨ What it does

ChatGPT frames a 150-word beneficiary story from field notes with placeholders for names. Strip every [VERIFY] detail or confirm it with the caseworker.

Turn these field notes into a 150-word beneficiary story for a grant: [PASTE NOTES]. Change names to [NAME]. No invented outcomes. Mark any detail not in notes [VERIFY].

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Pro tip: Stories sell need, not fiction. If it is not in the notes, it does not go in.

Problem vs solution split

6/15

✨ What it does

ChatGPT splits your notes into problem and solution bullets and flags [DUP]. Fix duplicates before you expand bullets into prose.

From program notes: [PASTE], split content into problem section bullets and solution section bullets. Flag anything that belongs in both as [DUP]. Max 12 bullets total.

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Pro tip: Funders reject drafts that solve a problem you never proved. Split first.

Outcomes and logic

3 prompts

Logic model sketch

7/15

✨ What it does

ChatGPT sketches a text logic model from your program design and tags unmeasured outcomes [VERIFY]. Add a metric or cut each VERIFY outcome.

Build a text logic model: inputs, activities, outputs, short-term outcomes, long-term outcomes. Source: [PASTE PROGRAM DESIGN]. Tag any outcome without a measure [VERIFY].

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Pro tip: If you cannot measure it, the funder cannot fund it. Cut fluffy outcomes early.

SMART outcomes rewrite

8/15

✨ What it does

ChatGPT rewrites outcomes to SMART format using only numbers from your paste. Fill [TARGET OR VERIFY] with agreed targets from your M&E lead.

Rewrite these outcome statements to be SMART: [PASTE LIST]. Keep numbers only if present in paste. Otherwise use [TARGET OR VERIFY]. One sentence each.

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Pro tip: Paste the M&E plan fragment if you have one. ChatGPT will not invent baselines.

Evaluation plan stub

9/15

✨ What it does

ChatGPT drafts an evaluation stub with questions, sources, and roles from your program info. Confirm [VERIFY] tools match what staff actually use.

Draft an evaluation plan stub: questions, data source, cadence, responsible role. Program info: [PASTE]. Do not name software we do not use. Tag tools [VERIFY].

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Pro tip: Evaluation plans fail on cadence, not jargon. Name who collects data monthly.

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Budget narrative

3 prompts

Line item justification

10/15

✨ What it does

ChatGPT writes budget narrative paragraphs tied to activities for each major line. Finance must confirm every dollar before upload.

Here is our budget table: [PASTE]. Write a budget narrative paragraph per major line: [LINE LIST]. Tie each to activities in [PASTE ACTIVITIES]. No new line items.

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Pro tip: Narrative follows the spreadsheet, not the other way around.

Match and leverage

11/15

✨ What it does

ChatGPT drafts match and leverage from your notes with [VERIFY] on unknown amounts. Attach letters or board minutes for every VERIFY amount.

From notes: [PASTE MATCH SOURCES AND AMOUNTS], draft a match and leverage section. Tag any amount not in notes [VERIFY]. Plain language.

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Pro tip: Funders audit match. If it is not documented, it is not match.

Salaries defensible

12/15

✨ What it does

ChatGPT explains salary lines from duties you pasted with [RATE OR VERIFY] placeholders. HR fills rates; you do not guess.

Explain salary lines for roles: [ROLE LIST] using job duties from [PASTE]. Include FTE and period. Do not invent pay rates. Use [RATE OR VERIFY].

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Pro tip: Duty-based justification survives audit. Title-only justification does not.

Assembly and polish

3 prompts

Section merge order

13/15

✨ What it does

ChatGPT proposes merge order and cuts to fit the funder limit from your section list. Apply cuts yourself; do not let ChatGPT delete proof.

We have drafts: [LIST SECTION TITLES AND WORD COUNTS]. Funder limit: [LIMIT OR VERIFY]. Propose merge order and cuts to fit. No new content.

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Pro tip: Cut adjectives before you cut outcomes. Funders notice missing outcomes.

Plain language pass

14/15

✨ What it does

ChatGPT simplifies your section while keeping numbers and flagging [DEFINE] jargon. Add one-line definitions for each [DEFINE] term in a footnote.

Simplify this grant section for a general reviewer: [PASTE]. Keep all numbers and proper nouns. Flag jargon you cannot define in 8 words as [DEFINE].

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Pro tip: Reviewers are not specialists. If your board member would stumble, fix it.

Final consistency

15/15

✨ What it does

ChatGPT lists conflicts between narrative and budget sections with cites. Reconcile headcount and timeline before portal submit.

Compare narrative [PASTE A] and budget narrative [PASTE B]. List conflicts in headcount, timeline, or geography. Cite sentence. Tag unsure [VERIFY].

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Pro tip: Portal submit with mismatched headcount is an automatic desk reject at many foundations.

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Frequently Asked Questions

No. These prompts stay inside ChatGPT's official product. It drafts from program notes you paste; funders still verify facts. If a setting is missing on your plan, the prompt says so.
A current ChatGPT account. Some features sit on paid plans. The prompts still work as checklists if a feature is off.
Every prompt tells it to use only what you paste and to tag gaps as [VERIFY]. You still check the grant narrative before you save it.
Yes to copy. Running them needs your ChatGPT account. Long files fit better on a paid plan.
No. It is a draft of your grant narrative. You own the facts, the files, and whatever your job or policy requires.

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