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patina-cli

v8.1.1

Published

AI text humanizer CLI — detects and removes AI writing patterns

Readme

patina is a deterministic, pattern-based humanizer for Korean, English, Chinese, and Japanese. It finds AI-sounding phrasing and rewrites it without changing the claim, numbers, polarity, or causation — built for allowed AI-assisted drafting, not for evading detectors.

  • Auditable, not a black box — 184 named patterns drive every edit; --diff shows exactly what changed and why.
  • Meaning verified on the web — web gates each rewrite with MPS/fidelity floors, rejecting drift; CLI --verify and /patina --strict add checks.
  • Three independent axes — Document Type owns genre, Persona owns voice, Register owns delivery. Omit any axis to preserve the source.
  • Every surface — agent skill (Claude Code · Codex · Cursor · OpenCode), Node CLI, and a browser playground.
  • Honest about limits — scores are editing signals, not authorship proof; our own pre-registered study publishes where rewriting fails alongside where it works.

Quick Start

Browser — nothing to install. Open patina.vibetip.help and paste text. Rewrites run server-side with the MPS/fidelity gates; API mode forwards your own key per request (never stored or logged).

Hosted API (Pro)

Agent skill — paste this into Claude Code, Codex CLI, Cursor, or any agent:

Install patina by following https://raw.githubusercontent.com/devswha/patina/main/INSTALLATION.md

Then use it:

/patina --lang en

[paste your text here]

CLI — Node >= 18:

npx patina-cli --lang en input.txt          # rewrite
npx patina-cli doctor                       # check backends and keys

A logged-in codex, claude, or gemini CLI works with no API key: add --backend codex-cli. Full install options: INSTALLATION.md.

Three Independent Axes

patina does not infer one axis from another. Omit Persona and Register to keep the source voice and register.

| Axis | Controls | Does not control | Select with | |---|---|---|---| | Document Type | Genre, purpose, structural conventions, pattern policy | Voice, casual/professional delivery, meaning floors | --document-type · config document-type · Playground "Document Type" | | Persona | Reusable voice fingerprint: vocabulary, rhythm, explanation habits | Genre, pattern policy, register, meaning floors | --persona · config persona · Playground "Persona" | | Register | casual or professional delivery | Genre, persona identity, pattern policy | --register · config register · Playground "Register" |

Meaning preservation is the outer guard; an explicit value never fills an omitted axis.

Commands

patina input.txt                                          # rewrite with defaults
patina --audit input.txt                                  # detect patterns only
patina --score --offline --exit-on 30 input.txt           # deterministic CI gate, no API key
patina --diff input.txt                                   # pattern-by-pattern changes
patina --verify input.txt                                 # rewrite + MPS/fidelity floor check
patina --document-type email --register professional input.txt
patina persona new my-voice --from-sample past-posts.txt  # learn a reusable voice
patina --persona my-voice draft.md
patina --batch docs/*.md --outdir cleaned/

patina --help prints the full flag list. CI wrapper for GitHub Actions: devswha/patina-action — plus pre-commit, static-site, Docker, and release integrations.

Project config lives in .patina.yaml:

version: "8.1.1"
language: ko              # ko | en | zh | ja
document-type: default    # genre/purpose + pattern policy
persona:                  # optional reusable voice; omit to preserve source
register:                 # casual | professional; omit to preserve source

Facts

| | | |---|---| | 184 patterns | 37 rewrite-capable + 9 score-only viral-hook per language (46 each across KO/EN/ZH/JA) — see the full 184-pattern catalog in PATTERNS.md | | Modes | rewrite · verify · audit · score · diff | | Calibration | 67.3% editing-hotspot catch [63.5–71.0%] across GPT-5.5 / Claude Sonnet 4.6 / Gemini 2.5 Pro (n=600, KO+EN); 16.0% false positives [11.6–21.7%] on KO+EN human controls (n=200) | | License | MIT |

Scores are editing signals with false positives and false negatives, not proof of authorship. See Ethics.

Documentation

License

MIT. See LICENSE and NOTICE. Inspired by oh-my-zsh, Wikipedia's "Signs of AI writing", and blader/humanizer.