Grant Tone-Matcher

Does your draft sound like the grants that win? Paste a draft and one or more winning examples. See, dimension by dimension, where your voice drifts from the funder's house style, with concrete words to swap.

1 · Your draft

The grant text you want to match to the winners (your in-progress proposal)

2 · Winning examples (the target voice)

Alignment

0/ 100

Dimension by dimension (draft vs winners' average)

Concrete rewrite suggestions

Specific words and phrases to add or drop so your draft moves toward the winners' voice. These come from the same rule sets the engine scores on. Nothing hidden.

This matches STYLE, not content. It says how closely your voice tracks the examples you trust, never whether the idea will be funded. A coach for a funder's house voice, not a grader. Every number traces to a rule you can read.

Grant Tone-Matcher · All Light Industries (sandbox). Browser port of the stdlib engine in grant_tone_matcher.py, which reuses the live tells.py and plainlight.py rule sets. Your text is analysed entirely in your browser: nothing you paste is ever sent anywhere, and there are no network calls during analysis. The one optional request is the Atkinson Hyperlegible font from a CDN; if it is blocked, the page falls back to a system font and still works.