Humanize Korean

What it does

When your agent uses it

• Tasks that involve Humanizing AI text

Example prompts

• “AI 티 없애줘”
• “AI 같은 글 자연스럽게”
• “GPT/ChatGPT 문체”
• “/humanize-korean”

Requirements

• Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 0712439. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships script files (Python), which the agent can run.

  Shell commands in SKILL.md call:

  • bash

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Humanize Korean loads about 1.9k tokens when it runs, and up to ~46k if it reads all its reference files. Until then it costs about 145 tokens; SKILL.md has 953 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~145

When it runs · the whole SKILL.md, loaded when a task matches

~1.9k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~46k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from bam-bam-2/solo-skills at commit 0712439, republished under its MIT licence (© bam-bam-2). 953 words, ~1,871 tokens.

name

humanize-korean

description

AI(ChatGPT·Claude·Gemini 등)가 쓴 한글 텍스트를 "사람이 쓴 글처럼" 윤문해주는 오케스트레이터 스킬. 번역투·영어 인용 과다·기계적 병렬·관용구·피동태 남용·접속사 남발·리듬 균일성·이모지/불릿 과다 등 10대 카테고리 40+ AI 티 패턴을 탐지·분류해 내용은 한 글자도 건드리지 않고 문체·리듬·표현만 자연스러운 한국어로 재작성한다. 트리거 — "AI 티 없애줘", "AI 같은 글 자연스럽게", "GPT/ChatGPT 문체", "AI 번역투 고쳐", "사람이 쓴 것처럼 윤문", "AI 윤문", "ChatGPT 티 제거", "한글 AI 탐지·윤문", "AI 글 사람처럼", "번역투 제거", "영어 인용 많은 글 윤문", "AI 글 티 안 나게", "휴머나이저", "humanize Korean", "AI detector bypass 한글". 후속 작업 — "특정 카테고리만 다시", "윤문 강도 조정", "장르 바꿔서", "이 문단만", "2차 윤문" 도 모두 이 스킬. 단순 맞춤법·오탈자 교정은 직접 처리, 번역은 번역 스킬, 내용 추가·삭제를 동반한 재작성은 별도 집필 스킬.

version

1.5.0

humanize-korean v1.5 — {fast|strict} 모드 / run_id: {YYYY-MM-DD-NNN}

input_path: <abs path>/_workspace/{run_id}/01_input.txt
quick_rules_path: ${CLAUDE_SKILL_DIR}/references/quick-rules.md
genre_hint: 칼럼 | 리포트 | 블로그 | 공적 | null

01_input.txt
    ↓ [humanize-monolith — 단일 호출]
    ├ 메모리: quick-rules 로드 → 탐지 → 윤문 → 자체검증
    └→ final.md + summary.md

01_input.txt
    ↓ [ai-tell-detector]
02_detection.json
    ↓ [korean-style-rewriter]
03_rewrite.md + 03_rewrite_diff.json
    ↓ [병렬 팀]
    ├→ [content-fidelity-auditor] → 04_fidelity_audit.json
    └→ [naturalness-reviewer]      → 05_naturalness_review.json
    ↓ [오케스트레이터 종합]
    ├→ (재작업) Phase B로 복귀 (최대 3회)
    └→ (승인) final.md + summary.md

© bam-bam-2, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (references) in skills/humanize-korean of bam-bam-2/solo-skills.

• SKILL.md
• references/ai-tell-taxonomy.md
• references/baseline.json
• references/baseline_v2.json
• references/metrics.py
• references/metrics_v2.py
• references/quick-rules.md
• references/rewriting-playbook.md
• references/scholarship.md
• references/web-service-spec.md

Open the folder on GitHubat commit 0712439