humanize-korean

REVIEW · 62
Registry indexed

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

Verified installs0
Stars128
Version1.5.0
Quality67/100 · Promising
Trust62/100 · Sandbox only
Audit77/100 · Needs review

Supply asset profile

Coding and developer agents

Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.

Browse track

Scenario

Coding agents

I need a coding agent that can understand a repository, edit code, and review pull requests.

Agent fit

Claude Code + OpenAI Agents + CLI

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add bam-bam-2/solo-skills --skill humanize-korean

Maintenance

fresh

Pushed today

Risk

Needs review

SKILL.md opens with a lengthy version changelog (v1.5 변경 고지 with prior v1.2–v1.4 failures) instead of a quick-start; new users must read through historical rollout notes before reaching usage instructions.

GitHub quality

128

67/100 Quality · 70/100 Trust

Coverage tags

CodingCoding agentsautomationagent-skill

Review notes

SKILL.md opens with a lengthy version changelog (v1.5 변경 고지 with prior v1.2–v1.4 failures) instead of a quick-start; new users must read through historical rollout notes before reaching usage instructions. · Workflow inconsistency: the fast-mode Phase 2 states the monolith agent '메모리에서 패턴 탐지 + 윤문 + 자체검증' and does not mention running metrics.py, but references/metrics.py documents itself as an 'external pre-processor for the monolith fast path' with a CLI designed to run BEFORE the monolith. It is unclear whether metrics.py is actually invoked in the default path.

Agent adoption scorecard

Trust, audit, and install readiness at a glance

These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.

Quality

Promising
67

Useful candidate, but compare it with alternatives before adopting.

Trust

Sandbox only
62

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

Audit

Needs review
77

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

OpenAgentSkill Trust Score v5

Human review before install

Run only in a sandbox and compare close alternatives before using it for real work.

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

128 GitHub stars

Repo activity

128 stars, 22 forks

Maintenance

Pushed today

License

MIT

Install

npx skills add bam-bam-2/solo-skills --skill humanize-korean

Install safety

standard package or runtime install path

Permission surface

shell or command execution

Agent outcomes

No agent outcome data yet

Docs

Strong README/SKILL.md context

Risk summary

Review before production

  • SKILL.md opens with a lengthy version changelog (v1.5 변경 고지 with prior v1.2–v1.4 failures) instead of a quick-start; new users must read through historical rollout notes before reaching usage instructions.
  • Quality score needs review
  • Stars/forks activity: 128 stars, 22 forks; issue activity unavailable in current metadata

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is declared
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.

Open JSON

Suited tasks

  • Content automation workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Summarize source material

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLIOpenAI AgentsCLI

Install decision

Command
npx skills add bam-bam-2/solo-skills --skill humanize-korean
Policy
review
Human review
yes

Trust and risk

Trust
62/100
Audit
77/100
Risk level
Needs review

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add bam-bam-2/solo-skills --skill humanize-korean

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • SKILL.md opens with a lengthy version changelog (v1.5 변경 고지 with prior v1.2–v1.4 failures) instead of a quick-start; new users must read through historical rollout notes before reaching usage instructions.
  • High-risk permission hints: Shell or command execution
  • Workflow inconsistency: the fast-mode Phase 2 states the monolith agent '메모리에서 패턴 탐지 + 윤문 + 자체검증' and does not mention running metrics.py, but references/metrics.py documents itself as an 'external pre-processor for the monolith fast path' with a CLI designed to run BEFORE the monolith. It is unclear whether metrics.py is actually invoked in the default path.

Agent safety v2

53/100 · Avoid automatic install

Experimentalreview

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

Resolve via API

high

Shell or command execution

Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

  • High-risk permission hints: Shell or command execution
  • SKILL.md opens with a lengthy version changelog (v1.5 변경 고지 with prior v1.2–v1.4 failures) instead of a quick-start; new users must read through historical rollout notes before reaching usage instructions.

Install targets

Install this skill in your agent workflow

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install bam-bam-2-humanize-korean

Agent resolve plan

Let an agent verify fit before installing.

The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.

Open text plan

Agent should check

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copy prompt

Task: Use humanize-korean in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20humanize-korean%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/bam-bam-2-humanize-korean/install
Install command: npx skills add bam-bam-2/solo-skills --skill humanize-korean
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Agent prompt

Use humanize-korean for this task. Review https://www.openagentskill.com/api/skills/bam-bam-2-humanize-korean/install, then install with: npx skills add bam-bam-2/solo-skills --skill humanize-korean

Registry metadata

Agent-readable profile for automatic skill selection.

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open manifest

Agent fit

66/100

Content automation

Platforms

Claude Code, OpenAI Agents

Audit report

Needs review · 77/100

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

View audit reportView eval report

Agent decision cockpit

Fallback candidate for Content automation

Prototype with this skill first; keep a fallback candidate ready.

66
Readiness
Prototype
Stage

Role in stack

Fallback candidate

Primary fit

Content automation

Trust label

Prototype first

Install path

Command ready

Use when

  • Content automation workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 67/100 quality profile
  • 1 OpenAgentSkill engagement events

review first

  • SKILL.md opens with a lengthy version changelog (v1.5 변경 고지 with prior v1.2–v1.4 failures) instead of a quick-start; new users must read through historical rollout notes before reaching usage instructions.

Implementation path

  1. 1Install it in a sandbox agent and run one Content automation task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Sandbox only

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

62
OpenAgentSkill Trust Score

GitHub adoption

INFO

128 GitHub stars

Stars/forks activity

CHECK

128 stars, 22 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

Pushed today

License clarity

PASS

MIT

Good signals

  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • SKILL.md opens with a lengthy version changelog (v1.5 변경 고지 with prior v1.2–v1.4 failures) instead of a quick-start; new users must read through historical rollout notes before reaching usage instructions.
  • Quality score needs review
  • Stars/forks activity: 128 stars, 22 forks; issue activity unavailable in current metadata
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Run only in a sandbox and compare close alternatives before using it for real work.

Quality profile

Promising candidate for agent workflows

Useful candidate, but compare it with alternatives before adopting.

67
GitHub stars
128
Freshness
Today
Install ready
Yes
License
MIT
Review before install: SKILL.md opens with a lengthy version changelog (v1.5 변경 고지 with prior v1.2–v1.4 failures) instead of a quick-start; new users must read through historical rollout notes before reaching usage instructions.

Workflow fit

Use this skill in these scenarios

Workflow fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

Similar skills that may fit this task.

Compare all

Overview

--- name: humanize-korean version: "1.5.0" 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. ---

# Humanize Korean — AI 한글 티 제거 오케스트레이터 (v1.5)

> **v1.5 변경 고지 (2026-04-26) — v1.1 베이스라인 + Monolith Fast Path** > v1.2(voice profile)·v1.3(candidate pool)·v1.4(역할별 모델 분산)는 모두 핫패스 비용을 잡지 못해 5,000자 입력에 25분이 걸렸습니다. v1.5는 **v1.1 단순 구조로 롤백한 뒤 단일 호출 monolith 에이전트만 추가**한 설계입니다. > > - **Fast 모드(디폴트)** — `humanize-monolith` 에이전트가 한 콜에서 탐지·윤문·자체검증 일괄 처리. 도구 호출 4~5회. 5,000자 이하 wall-clock 2~3분 목표. > - **Strict 모드(`--strict`)** — v1.1 5인 파이프라인 그대로(detector·rewriter·auditor·reviewer + taxonomist 분류 자산 유지). 정밀 검증·장문(8,000자+) 처리·etc. > - **삭제됨**: voice profile·candidate pool·promotion-checklist·sample-collection·권한 위계 §1~§6. > - **유지됨**: 분류 체계 본진(C-9·C-10·D-7·H-3·I-3·I-4 등 v1.2~v1.3.1 신규 패턴)·rewriting-playbook·5인 에이전트 정의(strict 모드 백본).

## Phase 0: 컨텍스트 확인 및 모드 결정

작업 시작 시 가장 먼저 다음 한 줄을 사용자에게 출력한다.

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

### 모드 결정 - 사용자가 `--strict`·"정밀 모드"·"5인 파이프라인" 명시 → **strict** - 입력 8,000자 초과 → **strict** (자동 승급 + 사용자에 1줄 고지) - 그 외 모두 → **fast (디폴트)**

### run_id 결정 - 모든 경로는 **cwd 기준**. 새 폴더 생성도 cwd 기준 `_workspace/{YYYY-MM-DD-NNN}/`에 만든다. - 기존 시퀀스 확인은 **`Glob` 도구**로 표지 파일을 매칭해 간접 조회. 올바른 사용법: `Glob(pattern="_workspace/YYYY-MM-DD-*/01_input.txt")` → 결과에서 폴더명 추출 후 NNN 최댓값 + 1. 주의: Glob은 디렉토리 자체는 매칭하지 못한다. 반드시 그 안의 표지 파일(`01_input.txt`)을 매칭할 것. `Bash ls`는 OS·셸 환경에 따라 경로 해석이 달라지므로 사용 금지. - 당일 폴더가 없으면 NNN = 001. 있으면 마지막 NNN + 1. - 부분 재실행 신호("이 카테고리만 다시"·"2차 윤문")일 경우 기존 run_id 재사용 + strict 모드로 자동 승급.

## Fast 모드 (디폴트)

### Phase 1: 입력 저장 1. cwd 기준 `_workspace/{run_id}/` 생성 2. 입력 텍스트를 `01_input.txt`에 저장 3. 첫 300자로 장르 자동 추정 (사용자 명시 시 우선)

### Phase 2: Monolith 호출 `humanize-monolith` 에이전트를 `Agent` 도구로 1회 호출.

입력: ``` 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 ```

출력 (에이전트가 직접 작성): - `_workspace/{run_id}/final.md` — 윤문본 - `_workspace/{run_id}/summary.md` — 메트릭·자체검증·하이라이트

monolith는 단일 호출 안에서 다음을 모두 수행 (자세히는 에이전트 정의 참조): 1. quick-rules 룰북 로드 → 메모리에서 패턴 탐지 + 윤문 + 자체검증 6항 점검 2. 변경률 50% 초과 시 자동 롤백 3. 자체검증 위반 시 1회 부분 재실행 4. final.md + summary.md 작성

### Phase 3: 결과 전달 사용자에게 다음 4개를 반환: 1. 한 줄 상태: `완료. 변경률 X% / 등급 Y / 자체검증 N/6 통과` 2. 윤문본 본문 (마크다운 블록) 3. summary.md의 핵심 표 (메트릭 + 카테고리 탐지 + 자체검증) 4. 등급 B 이하면 "정밀 검증이 필요하면 `--strict`로 5인 파이프라인" 안내

**디폴트 wall-clock 목표:** 5,000자 이하 2~3분, 8,000자 5~7분.

## Strict 모드 (`--strict` 또는 자동 승급)

v1.1 5인 파이프라인 그대로. 검증 분리·재윤문 루프가 의미 있을 때만 사용.

### Phase A: 탐지 `ai-tell-detector` 호출 → `02_detection.json`

### Phase B: 윤문 (최대 3회 루프) `korean-style-rewriter` 호출 → `03_rewrite.md` + `03_rewrite_diff.json`

### Phase C: 병렬 검증 (에이전트 팀) `TeamCreate`로 `humanize-review-team` 구성: - `content-fidelity-auditor` → `04_fidelity_audit.json` (의미 동등성) - `naturalness-reviewer` → `05_naturalness_review.json` (잔존·과윤문)

`TeamDelete` 후 종합 판정 매트릭스에 따라 분기:

| fidelity | naturalness | 종합 | 후속 | |---|---|---|---| | full_pass | accept / accept_with_note | **최종 승인** | Phase D | | full_pass | rewrite_round_2 | **2차 윤문** | Phase B 재호출 (target finding) | | full_pass | rollback_and_rewrite | **롤백 후 재윤문** | 윤문가에 edit 롤백 지시 | | conditional_pass | - | **롤백된 edit만 재시도** | Phase B 재호출 | | fail | - | **전면 재작업** | Phase B 전면 재호출 |

2차/3차 윤문 진입 시 `03_rewrite_v2.md`·`v3.md`로 버전 분리. **최대 3회 후 미해결이면 `hold_and_report`**로 사람 개입.

### Phase D: 최종 출력 1. `final.md`에 최종 윤문본 복사 2. `summary.md` 생성 (fast 모드와 동일 포맷) 3. 사용자에게 결과 + 등급 + 안내

## 부분 재실행 / 후속 명령

| 사용자 신호 | 처리 | |---|---| | "특정 카테고리만 다시" | strict 모드로 자동 전환, 해당 카테고리 finding만 Phase B 재실행 | | "이 문단만" | strict 모드, 해당 문단만 입력으로 새 run_id 생성 | | "2차 윤문"·"`/humanize-redo`" | 기존 run_id의 `final.md`를 새 입력으로 strict Phase B 재실행 | | "윤문 강도 조정" | strict 모드, `min_severity` 옵션 변경 후 Phase A부터 재실행 | | "장르 바꿔서" | `genre_hint` 변경 후 Phase A부터 재실행 |

## 옵션 (인자 끝에 자연어로)

- `장르: 칼럼|리포트|블로그|공적` — 장르 명시 (생략 시 자동 추정) - `강도: 보수|기본|적극` — 윤문 강도 (기본값: 기본) - `최소심각도: S1|S2|S3` — 탐지 임계값 (기본값: S2) - `--strict` — 5인 파이프라인 강제 사용

## 데이터 흐름 요약

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

### Strict 모드 ``` 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 ```

## 에이전트 호출 규칙

**모델:** 모두 `model: opus` 통일 (v1.1 베이스라인). 모델 다운그레이드는 v1.4에서 시도했으나 도구 호출 chain이 진짜 병목이라 효과 미미했음.

**에이전트 정의 위치:** 저장소 루트 `agents/`에 12종 정의(플러그인 컨벤션). Claude Code 탐색 경로: 1. 플러그인 설치 시 — `humanize-korean` 플러그인이 `agents/`를 번들로 제공(전역). 2. 스크립트 설치 시 — `install.sh`가 `agents/*.md`를 `~/.claude/agents/`에 심링크(전역).

필요 에이전트 6종: - `humanize-monolith` (v1.5 신규, fast 전용) - `ai-tell-detector` · `korean-style-rewriter` · `content-fidelity-auditor` · `naturalness-reviewer` (strict 5인 중 4명) - `korean-ai-tell-taxonomist` (분류 체계 유지·확장 — 본 스킬 실행 중에는 호출 안 됨, 별도 명령으로만 트리거)

## 테스트 시나리오

### Fast 정상 흐름 - 입력: ChatGPT가 생성한 AI 칼럼 초안 (2,000~5,000자, 번역투·결말 공식·hype 어휘 풍부) - 기대: monolith 1콜로 변경률 15~25%, 등급 A/B, wall-clock 2~3분, 자체검증 5~6/6

### Strict 정밀 검증 흐름 - 사용자 명시 `--strict` 또는 8,000자+ 입력 - 5인 파이프라인 끝까지 실행, 변경률 18~22%, 검증팀 full_pass

### 엣지 케이스 — 이미 사람이 쓴 글 - monolith 자체 탐지에서 매치 거의 없음 → 변경률 5% 미만 + summary.md에 "윤문 불필요 가능성" 메모 - 사용자가 `--strict`로 강제 검증 가능

## 주의 사항

- **의미 불변이 최상위 불문율.** monolith·strict 모두에서 위반 즉시 롤백. - **수치·고유명사·직접 인용은 탐지/윤문 대상 아님.** Do-NOT list 엄수. - **장르 이탈 금지.** 칼럼이 에세이로, 에세이가 문학으로 옮겨가지 않는다. - **register 보존.** 격식체 입력 → 격식체 출력. AI 티는 문법·수사이지 격식 자체가 아님. - **변경률 30% 초과 → 경고, 50% 초과 → 강제 중단.** - **자동 로드 금지.** 프로젝트 CLAUDE.md 등 다른 파일을 자동 파싱해 옵션을 추론하지 않는다.

## 참고 자료

- 슬림 룰북 (Fast 전용): [`references/quick-rules.md`](references/quick-rules.md) — S1·S2 핵심 패턴 + 자체검증 체크리스트 - 분류 체계 본진 (Strict 전용): [`references/ai-tell-taxonomy.md`](references/ai-tell-taxonomy.md) — 10대분류 × 40+ 패턴 전수 - 윤문 처방 (Strict 전용): [`references/rewriting-playbook.md`](references/rewriting-playbook.md) — 카테고리별 치환 레시피·장르별 허용 표 - 웹 서비스 스펙 (옵션): [`references/web-service-spec.md`](references/web-service-spec.md) — 웹 확장 시 로드

Technical details

Version
1.5.0
License
MIT
Last updated
Aug 23, 2026
Published
Aug 23, 2026

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humanize-korean: AI(ChatGPT·Claude·Gemini 등)가 쓴 한글 텍스트를 "사람이 쓴 글처럼" 윤문해주는 오케스트레이터 스킬. 번역투·영어 인용 과다·기계적 병렬·관용구·...

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