Comma density analyser

By Jack Stovell · published 2026-09-24

Comma density is the average number of commas in a sentence: total commas divided by total sentences. The median across 299 public pieces in ScriptGrain's reference corpus is 0.92. A voice profile stores the extraction model's reading of your samples; code counts the commas in a draft when it is scored, at a voice-match weight of 1.5.

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At a glance

What comma density measures

Comma density measures how often a writer pauses mid-sentence rather than stopping full. It says nothing about correctness: a writer can place every comma properly and still sit high or low. A writer who chains qualifications and asides into one sentence will show a high figure. Someone who favours short, declarative statements won't.

The unit is commas per sentence. It sits in the punctuation and format group alongside things like exclamation rate, ellipsis usage, and question marks in body.

How comma density is scored

Comma density enters the voice match score with a weight of 1.5, and it is counted from the draft in code. When a piece of text is checked against a profile, code counts its commas and sentences (the `measureTextFeatures` function), then compares the result with the profile's stored value, which is the extraction model's reading of your samples.

The comparison works like this: similarity equals one minus the gap divided by the tolerance, floored at zero. Tolerance is whichever is larger: 0.9, or 70% of the profile's own value. For example, if your profile stores 1.4, the tolerance is 0.98 (70% of 1.4): a draft 0.49 away scores 0.5 on this feature, and one 0.98 or more away scores 0. For any profile value up to about 1.29, the 0.9 floor applies instead.

This is one of the features that feed voice match, the overall 0 to 1 score a draft gets against a profile. If you want the full method, including how the other measurable and judged features combine, that's covered on the voice measurement framework page.

How to analyse comma density in your own writing

You don't need software to work this out. Grab a sample, at least a few paragraphs, and follow these steps.

  1. Count every comma in the sample.
  2. Count every sentence (a sentence ends at a full stop, question mark, or exclamation mark).
  3. Divide the comma count by the sentence count.
  4. Repeat across a few samples if you want a stable figure rather than one skewed by a single long sentence.
  5. Compare the result to a reference range, so the number means something rather than sitting there in isolation.

Five minutes with a highlighter and a calculator gets you there. The free writing style analysis tool and the habits report count it the same way, and ScriptGrain's free voice profile reads it from a writing sample among all 45 attributes.

Typical comma density in published writing

Typical comma density in published writing sits around 0.92 commas per sentence. That is the median of ScriptGrain's reference corpus: 299 public pieces from 47 sources (835,655 words), built 2026-09-20, each measured in code and then discarded. The spread across that corpus: p10 at 0.51, p25 at 0.73, median 0.92, p75 at 1.14, p90 at 1.4.

So if you're asking "am I using too many commas", here's a rough anchor: at or above 1.14 (the 75th percentile), the habits report calls that "Comma-heavy". At or below 0.73 (the 25th percentile), it's "Few commas". Anything between those two sits in the middle half of the corpus.

The homepage brand check shows a different signal called "Punctuation", in commas per 100 words. That unit is not comparable with comma density, which is per sentence, so don't check a homepage number against these figures.

How to make AI use more commas

If your AI-generated drafts feel clipped and you want the prose to breathe more, here's what to change.

  1. Let qualifications sit inside the sentence, set off by commas, rather than forcing them into separate sentences.
  2. Use commas for short lists inside a sentence instead of reaching for bullet points every time.
  3. Give the model a writing sample that already shows the comma habit you want; ask it to match that.

When ScriptGrain writes a draft, the profile's comma density sits in the voice profile JSON block of the system prompt, under "Treat every attribute as a hard constraint, not a suggestion." A named rule backs it: "Reproduce punctuation habits (parenthetical rate, comma density)". The same profile reaches ChatGPT, Claude and other tools through the API and MCP server.

How to make AI use fewer commas

If a draft reads breathless and overstuffed, cut the commas at the source rather than after the fact.

  1. Split long, comma-laden sentences into two or three shorter ones.
  2. Drop introductory phrases that need a comma after them; start the sentence plainly instead.
  3. Replace comma splices with full stops. If you catch yourself joining two complete thoughts with just a comma, that's the first one to fix.

The same mechanism works in this direction: a profile with a low stored comma density sends that low figure as a hard constraint, and ChatGPT, Claude or any MCP tool can read the same value from the profile.

Questions

How many commas per sentence is normal?

The reference corpus median is 0.92 commas per sentence, with the middle half of writing falling between 0.73 and 1.14. Below 0.51 puts a piece in the sparsest tenth of the corpus; above 1.4, in the densest tenth. The corpus is 299 public pieces from 47 sources, so 0.92 is a fair working benchmark for your own drafts.

Am I using too many commas?

If your figure sits at or above 1.14 commas per sentence (the 75th percentile of the reference corpus), the habits report labels it "Comma-heavy". That's not automatically wrong, some genres and voices run dense on purpose, but it's worth checking whether the commas are doing real work (setting off clauses, qualifications) or just papering over sentences that should be split.

How is comma density scored in a voice match?

Code counts it from the draft, compares it with the profile's stored value (the extraction model's reading), and weights it at 1.5 in the overall voice match score. Similarity is one minus the gap over the tolerance, floored at zero; tolerance is the larger of 0.9 or 70% of the profile's value. Full method detail sits on the voice measurement framework page.

How do I make ChatGPT write shorter clauses with fewer commas?

Ask it directly to split long sentences, drop comma-led introductory phrases, and replace comma splices with full stops. That's the manual route. The more reliable route is a voice profile: ScriptGrain's drafts send its comma density as a hard constraint in the system prompt, and ChatGPT can read the same figure through the MCP server, so the model works to a target number instead of guessing at "shorter".

Where does comma density sit among other attributes?

It's one of six attributes in the punctuation and format group, alongside things like list preference and capitalisation quirks. That group is one of eight in a full voice profile; the attributes page lists all of them, and the reference page covers how they're defined and measured.

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