Readability rewriter
Matching text to its audience’s reading level is one of the highest-leverage edits you can make — too complex and consumers bounce, too simple and professionals lose trust. This tool uses your own API key to rewrite any passage to a target Flesch-Kincaid grade level and shows the measured grade before and after so you can confirm the rewrite actually landed.
How it works
You paste your own OpenAI or Anthropic key, the text, and a target grade. The
tool sends a single instruction asking the model to rewrite the text to that
reading level while preserving meaning and key facts, calling the provider
directly from your browser (Anthropic requests carry the
anthropic-dangerous-direct-browser-access header). It then computes the
Flesch-Kincaid grade of both the original and the rewrite locally using the
standard formula — 0.39 × (words/sentences) + 11.8 × (syllables/words) − 15.59
— with a heuristic syllable counter, so you get an objective before/after rather
than just trusting the model’s claim.
Tips and notes
- Grade 6–8 for consumer copy. Most general-audience web content targets this band; technical documentation often sits at grade 10–12.
- Verify, do not assume. Models sometimes overshoot or undershoot the target, which is exactly why the measured scores are shown — rerun if it missed.
- Shorter sentences move the needle most. The formula is dominated by sentence length, so splitting long sentences is the fastest way to drop a grade.
- Your key never leaves the browser. It is used only for the direct provider request and is never stored.