가장 최근 윤문 결과를 2차로 다시 다듬는다 — 특정 카테고리·문단·강도 조정도 가능. humanize-korean
Scanned 9/2/2026
Install to Claude Code
npx -y skills add nota-america/forgecat-agent-profiles --skill humanize-redo --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Humanize Redo?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/nota-america-humanize-redo)More formats (shields.io, HTML) on the badges page.
---
name: humanize-redo
description: 가장 최근 윤문 결과를 2차로 다시 다듬는다 — 특정 카테고리·문단·강도 조정도 가능. humanize-korean
strict 윤문(Phase B)을 기존 run_id에 재실행해 잔존 finding을 처리한다. 트리거 — "/humanize-redo".
argument-hint: '[조정 지시 — 예: "번역투만 다시" "이 문단만" "강도 낮춰"]'
disable-model-invocation: true
---
# /humanize-redo — 2차 윤문 / 부분 재실행
cwd 기준 가장 최근 `_workspace/{run_id}/`를 찾아 `humanize-korean` 스킬의 strict 윤문(Phase B)부터 재호출한다.
## 사용자 지시
$ARGUMENTS
## 동작
1. `Glob`으로 `_workspace/YYYY-MM-DD-*/final.md`(또는 `01_input.txt`)를 매칭해 최신 `run_id` 식별. 없으면 "이전 실행이 없습니다. `/humanize`로 시작하세요" 안내 후 종료.
2. 사용자 지시 파싱:
- **카테고리 지정**("번역투만", "관용구만", "이모지만") → 해당 카테고리 finding만 재윤문
- **문단 지정**("이 문단만", "두 번째 문단만") → 해당 범위 finding만
- **강도 조정**("강도 낮춰"·"보수적으로" → S1만, "강도 높여" → S1+S2+S3)
- **롤백 요청**("이 변경 되돌려줘") → 해당 edit을 `content-fidelity-auditor` 롤백으로 처리
- 지시 없음·"2차 윤문해줘" → 잔존 finding 전체 대상 round 2
3. `korean-style-rewriter` 재호출 입력: 기존 `02_detection.json` 또는 `05_naturalness_review.json`의 잔존 finding + 사용자 지시를 `target_filter`로 전달.
4. 산출물은 `03_rewrite_v2.md`(또는 v3)로 버전 분리. 이전 `final.md`는 `final_prev.md`로 백업.
5. strict Phase C 병렬 검증 → Phase D 최종 출력(변경 비교 표 + 신규 등급).
## 루프 한도
최대 round 3. 그 이상 미해결이면 `hold_and_report`로 사람 검토 권고.
## 참고
- 풀 파이프라인 신규 실행은 `/humanize`.
- 분류 체계: `humanize-korean/references/ai-tell-taxonomy.md`
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
**Complete production-ready guide for Google Gemini embeddings API** This skill provides comprehensive coverage of the `gemini-embedding-001` model for generating text embeddings, including SDK usage, REST API patterns, batch processing, RAG integration with Cloudflare Vectorize, and advanced use cases like semantic search and document clustering. ---
Interview, source-challenge, verify, save, and ADR-gate fuzzy coding requests into Codex-ready implementation specs. Use when a feature, bugfix, refactor, migration, repo-wide change, or architecture task needs user-verified requirements, source-backed decisions, durable architecture decisions, acceptance criteria, validation commands, rollout notes, saved spec/ADR files, and a Codex execution prompt. Do not use when already fully specified or when the user wants direct implementation now.
Use when a repo needs CodeGraph plus ast-grep for Codex MCP setup, exploration, impact analysis, structural search, or safe refactor planning.