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Text analysis

Text Formality Analyzer

Estimate how formal or informal your text sounds. Looks at slang, contractions, pronouns, sentence length, passive structure, and Latin-root vocabulary. Includes target presets (academic / business / casual).

Built and maintained by Paul Clark, Redmoon Software · Changes and corrections

When to use this

Use to match tone to audience — academic submissions, business proposals, conference talks, or marketing emails. The target selector gives you an instant fit check.

How it compares

Where lexical density measures information packing and readability measures grade level, formality measures *register* — a third independent axis.

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How it works

Formality is a 0–100 score combining slang count, contraction count, first/second-person pronoun rate, passive voice frequency, formal markers ("furthermore", "consequently"), and average word length.

The target selector adjusts which range the score should fall into — academic (70–100), business (50–80), or casual (0–45).

Contractions are recognised with either a straight (') or a typographic (’) apostrophe, so text pasted from a word processor or phone, which substitutes the curly one, scores the same as typed text.

Suggestions are generated when your text falls outside the target range, focusing on the most impactful adjustments.

FAQs

How does the formality score work?

It starts at 50 and adjusts for slang, contractions, first/second-person pronouns, passive voice, formal marker words ("furthermore", "utilize") and average word length, giving a single 0–100 score.

What scores fit common audiences?

Academic ~70–100, business ~50–80, casual ~0–45. The target selector adjusts the suggestion thresholds.

Can I tune the rules?

Not yet — the slang and formal-marker lists are baked in. Submit feedback if you have a list for a specific genre.

Worked example

Input

Hey! Just wanted to let you know we're gonna ship the update next week. Pretty cool, right?

Output

Formality: 32 / 100 — Casual.

Slang ("gonna", "cool"), a contraction ("we're") and direct address ("you") pull the score down from the neutral starting point of 50, and nothing formal pulls it back up, so it lands in the casual band.

Common pitfalls

  • Slang list is general — domain-specific slang may not be caught.
  • Heavy passive voice falsely boosts formality (sometimes desirable, sometimes not).
  • Very short text scores unreliably.

Register as a measurable thing

Formality is estimated from markers that reliably track register: contractions, first- and second-person pronouns and colloquial vocabulary pull informal; formal connectives and Latinate verbs ("therefore", "facilitate"), longer average word length and passive constructions pull formal.

The output is a position on a scale, not a grade. There is no correct formality — only formality that matches the audience and the medium, and the same content is wrong at both extremes for different readers.

Consistency is what to watch

The failure the score catches best is drift. A document that opens conversationally and turns institutional halfway through — usually where the writer switched to text adapted from another source — reads as two documents stitched together, and readers register that as untrustworthy without identifying why.

Formality creep is the common direction, particularly in anything reviewed by several people, because each round of edits tends to add hedging and nominalisation. Checking a document against an earlier draft is the fastest way to see it happening.

Read more about this

· 8 min read

How to measure the formality of your writing (and hit the register you are aiming for)

Tone is hard to judge in your own writing. A formality analyzer turns the casual-to-formal axis into a 0–100 score by counting the signals readers react to: slang, contractions, pronouns, passive voice, and Latin-root vocabulary. Here is how it works and how to use it.

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