naturalize

Rewrites non-English text to remove translationese and read as native-written prose.

Updated Jul 31, 2024
One-click install
npx skills add https://github.com/sharosoo/dotfile --skill naturalize-sharosoo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: naturalize
Source: https://github.com/sharosoo/dotfile/tree/main/.claude/skills/naturalize
Command: npx skills add https://github.com/sharosoo/dotfile --skill naturalize-sharosoo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? LLM-generated text in languages like Korean, Japanese, Chinese, Arabic, Vietnamese, or Hindi often reads as translated English — grammatically valid but rhythmically foreign. This Skill runs a dedicated polish pass that regenerates such text so it reads as if a native speaker wrote it from scratch. ## Core Features & Use Cases - Regenerate, don't patch: Re-composes the passage in the target language instead of spot-fixing awkward spans, avoiding post-editese. - Per-language symptom checklists: Ships reference guides for Korean, Japanese, Chinese, Arabic, Vietnamese, and Hindi covering pronoun overuse, passive calques, light-verb padding, register control, and idiom literalism, plus a language-agnostic fallback. - Strict output contract: Returns the naturalized text plus a change log flagging every meaning-affecting edit, so the calling agent can verify fidelity before surfacing the result. - Use Case: After drafting a Korean README or a Japanese commit message, hand the text to this Skill with context (register, audience, glossary) and receive a native-quality rewrite with an auditable change log. ## Quick Start Ask the agent to naturalize the Korean README draft you just generated so it reads like a native speaker wrote it, and return a change log of what changed.

Frequently Asked Questions about naturalize

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I make LLM-generated Korean text sound natural?▼

Run a separate rewrite pass that regenerates the text in Korean rather than patching awkward spans. The Skill loads a Korean checklist targeting nominalization, passive overuse, A는 B structures, and literal calques, then iterates up to three passes naming each symptom removed.

What is translationese in LLM output?▼

Translationese is text whose tokens are grammatically valid in the target language but whose rhythm and structure follow English. Common tells include pronoun overuse, calqued connectives, forced passives, and literal idiom renderings.

Which languages does the naturalize skill support?▼

It ships dedicated reference checklists for Korean, Japanese, Chinese, Arabic, Vietnamese, and Hindi. Other languages fall back to a language-agnostic symptom list, and new languages can be added by dropping a references/<lang>.md file.

Can I use this for English text or code?▼

No. The Skill explicitly excludes English output, pure code, single short phrases, and proper-noun lookups. It is a polish pass for non-English prose longer than a sentence or two.

How does the skill prevent meaning changes during rewriting?▼

It returns a strict two-part output: the naturalized text and a change log flagging every condensed, dropped, or glossary-mapped item as meaning-affecting or not. The calling agent must compare meaning and reject the result on any discrepancy.

Why does telling an LLM to write naturally not fix translated-sounding text?▼

Adjective instructions like write naturally do not reliably reduce translationese and can worsen it. Reframing the task as a separate rewrite-as-a-native-speaker pass, with a symptom checklist and named feedback loops, measurably improves naturalness.