Humanize Korean

SUPERLOOPY HUMANIZE KOREAN ENABLED

What This Skill Is

Use this skill as a Korean prose post-editor: it takes already-written Korean text and removes AI-like rhythm, translationese, repetitive endings, formulaic transitions, and over-polished phrasing without changing the underlying message.

Shout out to https://github.com/epoko77-ai/im-not-ai for the Korean AI-tell inspiration. This Superloopy version keeps the workflow local, adds protected-span preservation, file-backed audits, and Superloopy evidence receipts.

Comparison Examples

Use these as calibration examples for the amount of change this skill should make. The Before side is intentionally more AI-like so the repair shape is obvious: remove stock transitions, translationese, inflated significance claims, and ~인 것입니다-style endings while preserving product names and facts.

Before	After
결론적으로, Fileloom은 무료로 사용할 수 있는 파일 뷰어 앱이라고 할 수 있습니다.	Fileloom은 무료로 사용할 수 있는 파일 뷰어 앱입니다.
이 앱은 PDF, EPUB, DOCX, PPTX, HWP, ZIP 등 다양한 파일 포맷을 열 수 있다는 점에서 주목할 만합니다.	이 앱은 PDF, EPUB, DOCX, PPTX, HWP, ZIP 등 다양한 파일 포맷을 열 수 있습니다.
또한 광고 없이 제공되기 때문에 사용자는 파일을 확인하는 과정에 있어 방해 요소 없이 문서를 읽을 수 있는 것입니다.	광고 없이 제공되기 때문에 사용자는 파일을 확인하는 과정에서 방해 요소 없이 문서를 읽을 수 있습니다.
따라서 Superloopy는 Codex 작업을 수행함에 있어 안정성을 높여주는 도구라고 할 수 있습니다.	Superloopy는 Codex 작업의 안정성을 높여주는 도구입니다.
이는 계획, 검증, 증거 기록을 통해 작업의 진행 상황을 관리할 수 있다는 점에서 매우 중요한 의미를 가지고 있습니다.	계획, 검증, 증거 기록으로 작업 진행 상황을 관리할 수 있습니다.

These examples scored audit grade A with protected tokens preserved and a 29.43% change rate. Do not copy their product claims into unrelated text; use them only as a rewrite-shape reference.

A much larger calibration set lives in references/golden-set.md: 28 established before/after pairs plus one semantic N-1 calibration for misplaced modifier targets. Every pair is verified against the bundled audit script by test/humanize-korean-golden.test.js.

Contract

• Rewrite only Korean text.
• Preserve meaning, claims, facts, numbers, dates, URLs, code, product names, model names, acronyms, and quoted spans.
• Preserve register: formal text stays formal, conversational text stays conversational, official text stays official.
• Prefer fewer, sharper edits over broad smoothing.
• Do not add examples, metaphors, facts, citations, or marketing claims that were not in the source.
• Remove em dashes and en dashes (—, –) from Korean prose (M-1): 줄표 is an English carryover and a strong AI tell in modern Korean writing. Restructure with 쉼표, 괄호, a colon, or a sentence split; write ranges with ~. Dashes inside code spans and quoted spans stay.
• N-1 — misplaced modifier target: 정확성은 시간·수치·사양·정보·식별·일치처럼 확인 가능한 대상에 붙인다. 정확한 컴퓨터/보드/펌웨어 이미지는 공급된 관계에 따라 대상 컴퓨터 확인, 보드 모델 확인, 보드와 일치하는 펌웨어로 고친다. 정확한 시간/수치/사양/정보는 보존한다. This is semantic review guidance, not an audit pattern or grade effect.
• P family — calques: 조용히는 사람이 하는 것이다. 프로그램은 조용히 하지 않는다. When 조용히/조용한, 우아하게, 투명하게 (unnoticed-by-the-caller sense), or 단일 진실 공급원 modifies a program action, say what the program did and which signal it did not give. P-1a, P-2, and P-4 gate the grade; P-1b, P-3, P-5, and P-6 only warn. Follow the repair ladder in references/quick-rules.md: delete first, state the symptom from supplied facts second, never insert a stock phrase such as 정본, 페일세이프, or 아무 표시 없이.
• Preserve modality (서법, upstream v2.4): a demand (~해야 한다) stays a demand and a hedge (~일 수 있다) stays a hedge. When deontic endings dominate paragraph closings, reposition the sentence (D-6); never substitute a plain assertion. The audit counts deontic and hedge markers and warns when they decrease.
• Load references/quick-rules.md before rewriting; load references/golden-set.md when you need more calibration pairs.
• Load references/quality-rubric.md before grading or finalizing.
• Use scripts/audit-humanize-output.mjs to validate any file-backed output.
• If adapting upstream rule text, respect references/upstream-notice.md.

Workflow

1. Identify source text from the prompt or from a .txt or .md path supplied by the user.
2. Refuse non-Korean source text with 한국어 텍스트만 처리할 수 있습니다.
3. Estimate genre as 공적, 리포트, 블로그, 칼럼, 대화체, or 제품 문구; user-provided genre wins. Record it to describe the output register.
4. Mark protected spans before editing: numbers, dates, units, URLs, emails, code spans, quoted spans, English acronyms, product names, model names, and legal/article references.
5. Detect AI-tell patterns from references/quick-rules.md, prioritizing S1 then repeated S2. Include the P calque rows; the audit reports every remaining P id with its ladder step in warnings.
6. Rewrite paragraph by paragraph in this order: protected spans unchanged, signature phrases, translationese, passive/hedging, structure/list rhythm, sentence endings, visual formatting.
7. Keep total character-change rate under 30% whenever possible; stop and report risk above 50%.
8. Write outputs:
   • Active Superloopy loop: .superloopy/evidence/humanize-korean/<run-id>/source.md, final.md, summary.md, audit.json.
   • No active loop: _workspace/humanize-korean/<run-id>/source.md, final.md, summary.md, audit.json.
9. Run node skills/humanize-korean/scripts/audit-humanize-output.mjs --source <source.md> --final <final.md> --report <audit.json> --genre "<genre>". The audit records the genre in the report.
10. If audit fails, repair once. If it still fails, keep the safest version and report the failing audit reason.
11. Respond concisely with output path, change rate, grade, preserved-token status, and 3 to 5 before/after highlights. Do not paste the full rewritten body unless the user asks.

Superloopy Evidence

When a Superloopy loop is active, the final line of the completion note must include:

SUPERLOOPY_EVIDENCE: .superloopy/evidence/humanize-korean/<run-id>/audit.json