i-have-adhd
Use only after explicit Codex `$superloopy:i-have-adhd` or Claude Code `/superloopy:i-have-adhd` invocation, or when a qualifying leading `loopy`/`루피` task…
Korean prose humanizer for Codex and Superloopy that rewrites Korean text so it sounds naturally human while preserving meaning, register, facts, protected tokens, and evidence. Use when the user asks to remove Korean AI tells, make Korean copy sound human, fix 번역투, remove
$ npx -y skills add beefiker/superloopy --skill humanize-korean --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/humanize-koreanContext preview
The summary Claude sees to decide when to auto-load this skill.
Korean prose humanizer for Codex and Superloopy that rewrites Korean text so it sounds naturally human while preserving meaning, register, facts, protected tokens, and evidence. Use when the user asks to remove Korean AI tells, make Korean copy sound human, fix 번역투, remove
name: humanize-korean description: Korean prose humanizer for Codex and Superloopy that rewrites Korean text so it sounds naturally human while preserving meaning, register, facts, protected tokens, and evidence. Use when the user asks to remove Korean AI tells, make Korean copy sound human, fix 번역투, remove ChatGPT/Claude/Gemini tone, polish Korean without changing meaning, or says "AI 티 없애줘", "AI 윤문", "번역투 고쳐", "사람이 쓴 것처럼", "humanize Korean", "한글 AI 티 제거", "글 자연스럽게 다듬어줘". Inspired by Korean AI-tell ideas from https://github.com/epoko77-ai/im-not-ai. Handles Korean rewriting only; not for translation, fact expansion, SEO rewriting, legal drafting, or generic proofreading.
SUPERLOOPY HUMANIZE KOREAN ENABLED
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.
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`.
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:
9. Run `node skills/humanize-korean/scripts/audit-humanize-output.
Loop engineering for Codex, Claude Code, and Google Antigravity. Type loopy — an agent does the work, proves each piece with real evidence, and only then says it's done.
Repo: beefiker/superloopy
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