Writing footprint

Writing footprint is separate from templates: it describes style and variation in prose, not repeating log lines or JSON keys. It is computed only for text-like content after template mining (plain text, markdown, HTML body, EPUB body).

It does not appear for logs, JSON template runs, or metadata-only formats.

Where it appears in JSON

Location	When
writing_footprint on MiningResult	Templates-only path for text-like files
Top-level writing_footprint on Output	Same metrics, also in templates-only export
html_metadata	HTML-specific counts plus footprint from body text
epub_metadata	EPUB bibliographic fields plus footprint from spine body

UBLX shows this in the Writing pane (table layout, same family as Metadata).

How it is derived

Writing metrics are computed from the same sentences used for templates:

1. Exact-pattern pass — group sentences by shared phrases / n-grams; build templates and example diversity.
2. Shape fallback — if no templates emerge, group by sentence length and ending punctuation (period, ?, !).
3. Aggregate — vocabulary, punctuation, template entropy, and optional SVO-style pivot analysis over template examples.

Logs use line templates only; log_metadata covers line endings and timestamp heuristics instead.

WritingFootprint fields

{
  "vocabulary_richness": 0.42,
  "avg_sentence_length": 18.3,
  "template_diversity": 27,
  "avg_entropy": 0.61,
  "punctuation": {
    "period_percent": 72.5,
    "question_percent": 4.1,
    "exclamation_percent": 0.8,
    "dialogue_percent": 12.0,
    "avg_commas_per_sentence": 1.4
  },
  "svo_analysis": {
    "svo_structure_percent": 38.0,
    "avg_subject_length": 5.2,
    "avg_object_length": 8.1,
    "common_pivots": ["is", "was", "has"]
  }
}

Field	Meaning
vocabulary_richness	Unique words ÷ total words (0.0–1.0)
avg_sentence_length	Mean words per sentence
template_diversity	Count of distinct template patterns
avg_entropy	Mean placeholder variation across templates (0.0–1.0; higher = more varied wording in slots)
punctuation	Sentence-ending and dialogue punctuation profile (see below)
svo_analysis	Optional inferred subject–verb–object structure from template pivots

punctuation object

Field	Meaning
period_percent	Share of sentences ending with .
question_percent	Share ending with ?
exclamation_percent	Share ending with !
dialogue_percent	Share containing quotes
avg_commas_per_sentence	Mean commas per sentence

svo_analysis object (optional)

Present when the analyzer finds enough pivot structure in template examples:

Field	Meaning
svo_structure_percent	Share of templates with pivot-like structure
avg_subject_length	Mean words before pivot
avg_object_length	Mean words after pivot
common_pivots	Frequent pivot tokens (often verbs or structural words)

Related: Template mining overview, Metadata extraction.