Beautiful visualizations of how language differs among document types.
AI-writing humanizer for KO/EN/ZH/JA
The Java Graphical Authorship Attribution Program
A local detector for AI-writing patterns. Scores every prose file your agent saves. Python standard library only, no network, no model.
Collected solutions from Google Code Jam programming competition (2008-2021).
Stylometry library for Burrows' Delta method
Stylometric Data Mining Library with a focus on identifying Satoshi Nakamoto as a case study.
Data and code for Kang et al., EMNLP 2019's paper titled "(Male, Bachelor) and (Female, Ph.D) have different connotations: Parallelly Annotated Stylistic Language Dataset with Multiple Personas"
Ghost Writer — AI Content Engine with 40-point QA, 18 platform formatters, and triple-detector validation. Built on Ghost Protocol. Passes GPTZero, Pangram, and Originality.ai.
Interpretable stylometric profiling + author-style transfer built on explicit and LLM-genenated JSON fingerprints and local measurements. Fingerprint your corpus, inspect/visualize signals, then LLM-generate stylistically similar text with meaning preserved, deterministic post-processing, normalization controls, and deviation reports. CLI + API.
Source code embeddings for various programming languages
Measure how closely writing matches a learned author's style. Japanese & English, local-first CLI for LLMs and humans.
Python package to deal with PAN corpora and extract stylometric features from text documents.
Measures how you write and builds a voice profile, then enforces it with a deterministic checker: em dashes, filler, hedges, and AI tells are caught by code, not by asking the model to be careful. Multiple named voices, eval harness with golden tests, no dependencies.
A command-line tool for masking authorship of text, by changing the writing style with a Large Language Model.
QuitaUp: A tool for quantitative stylometric analysis
A Claude Code skill that extracts your writing persona from real messages, measures its accuracy, and writes in your voice.
POSNoise: An Effective Countermeasure Against Topic Biases in Authorship Analysis
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