Stylometric Fingerprint
Measure sentence rhythm, lexical diversity, function-word density, punctuation profile, repetition pressure, and readability complexity as one descriptive writing fingerprint.
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Runs locally in your browser.
Plain-English method
Stylometry describes how a sample is written. It is useful as a layered signal and as a before/after comparison tool, but it is not courtroom authorship attribution.
Mechanism and scoring
The free fingerprint uses normalized feature extraction over tokens and sentences: coefficient of variation, unique-word ratio, function-word ratio, punctuation density, sentence-start diversity, repetition density, and complexity.
This is one deterministic signal, not a verdict.
What it catches
- Sentence-length rhythm
- Lexical diversity
- Function-word density
- Punctuation profile
- Repetition pressure
What it misses
- Proof of authorship
- AI-generation verdicts
- Truth, sourcing, or hallucination
Core dimensions
- Sentence rhythm variance
- Lexical diversity
- Function-word density
- Punctuation profile
- Sentence-start diversity
- Repetition pressure
- Readability complexity
This is one signal in a layered stack.
Single-method detectors are too easy to overtrust. Stylometric Fingerprint is useful when it changes routing: allow, revise, human_review, or reject. It should be layered with specificity, provenance, pattern pressure, Unicode sanitation, media provenance, and paid Deep Scan when the decision matters.
score_stylometric_fingerprint is available through local MCP with no LLM cost, and through the remote MCP endpoint with free unauthenticated rate limits. See all detection methodologies and the dedicated methodology page for the deepest treatment of this signal.