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Voice fingerprint

Skill tchr-dev/autonovel/.claude/skills/evaluation/voice-fingerprint

Autonomous fantasy-novel pipeline as Claude Code skills, agents, and slash commands

Install
npx -y skills add tchr-dev/autonovel --skill voice-fingerprint

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Run the mechanical voice-fingerprint scanner across all chapters to identify outliers in sentence rhythm, vocabulary domain balance, dialogue ratio, abstract noun density, and similar metrics. No LLM call — just runs the Python script. Use during revision to find chapters that drift from the novel's voice.

SKILL.md

1.7 KB, as published. Nobody here has run it

Voice fingerprint

This skill runs scripts/voice_fingerprint.py and presents the result.

Procedure

  1. Set the env var so the script targets the right novel: 
    AUTONOVEL_NOVEL_DIR=<novel-dir> python scripts/voice_fingerprint.py
  2. Output is written to <novel-dir>/edit_logs/voice_fingerprint.json and a summary table is printed.

Important caveat

The vocabulary wells in scripts/voice_fingerprint.py (WELL_MUSICAL, WELL_TRADE, WELL_BODY) are defaults from "The Second Son of the House of Bells." For a different novel, these need to be replaced with vocabulary domains relevant to the new world.

If the vocab wells haven't been customised for this novel, edit the script first. Otherwise the well percentages are noise. The other metrics (sentence length CV, paragraph length, dialogue ratio, em-dash density, "the way" count, simile density, "He"-start %) are universal and worth running unchanged.

Reading the output

  • sentence_length_cv ≥ 0.4 is healthy. Below 0.3 is uniform-prose territory.
  • he_start_pct > 25% suggests sentence-start monotony.
  • the_way_count > 5 in a single chapter is leaning on a simile crutch.
  • Outliers (>1.5σ from mean) are the chapters where voice has drifted. Investigate them first.

After running, summarise outliers and recommend chapters to inspect with evaluate-chapter or hand to gen-brief for a voice-deviation revision.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.