Shop / Prompts & Skills / Grant Application Answers for Nonprofits — AI Prompt That Drafts From Your Real Figures

Grant answers from your documents — not from the AI's imagination

Grant answers drafted question by question from your organisation's documented facts and real numbers — any slot without evidence behind it is blocked, not filled. As AI writing tools become the default way applications get drafted, the invented beneficiary count is no longer a rounding error — it is the claim a funder's checker finds first. The defence is not better prompting. It is drafting from sources, with the sources attached.

The source-first method

1. Start from the funder's actual question sheet — the real questions, in their wording, not a generic application template.
2. Answer only from documented figures — your organisation's own records: counts, budgets, outcomes and evidence that exist on paper.
3. Attach the citation to the draft — each answer line maps to its source in a fact citation ledger, so a reviewer can verify it in seconds.
4. Block what is not documented — the slot stays visibly open, in a missing-evidence queue, until the evidence exists.

READY, BLOCKED, and nothing in between

This is a real output from the grant-answer skill — one question drafted with its sources, one refused:

**Q1 — READY:** River Table is a volunteer-run community food distribution group (N1). It operates a weekly collection and handoff on Saturdays (P1).

**Q2 — BLOCKED:** TO VERIFY — documented count of people served last year.

**Evidence:** N1 maps to volunteer-run purpose; P1 maps to weekly activity. No invented annual beneficiaries. **Submission:** human review required; Q2 incomplete.

Sample data above is fictional, shown so you can judge the output before buying.

What the 'not yet documented' flag buys you

A blocked slot looks like a failure and works like a to-do list: it names the exact evidence to gather — the documented count of people served last year — while there is still time to gather it. Readiness flags then say, per question, whether the application is genuinely ready for human review or only looks finished. A draft that admits its gaps can be fixed. A draft that hides them gets submitted.

Questions