Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mupengi-bot/mupengism --skill content-pipelinegit clone --depth 1 https://github.com/mupengi-bot/mupengismWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mupengi-bot/mupengism/content-pipeline)<a href="https://agentmods.dev/skills/mupengi-bot/mupengism/content-pipeline"><img src="https://agentmods.dev/badge/skills/mupengi-bot/mupengism/content-pipeline/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mupengi-bot/mupengism/content-pipeline"><img src="https://agentmods.dev/badge/skills/mupengi-bot/mupengism/content-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.01025 |
| Opus 5.5 | $0.00016 | $0.00410 |
| Sonnet 5.5 | $0.00008 | $0.00205 |
| Haiku 4.5 | $0.00004 | $0.00103 |
Grade A, and why
content-pipeline scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
content-pipeline
콘텐츠 생산 전체 흐름을 오케스트레이션하는 메타 스킬.
파이프라인 단계
1. seo-content-planner → 키워드 분석 & 콘텐츠 기획
2. copywriting → 본문 작성
3. cardnews → 카드뉴스 이미지 생성
4. social-publisher → 인스타그램/SNS 게시
5. 성과 추적 → 일일 리포트로 피드백
사용법
전체 자동 실행
content-pipeline --auto --topic "포토부스 활용법"
개별 단계 실행
# 1단계: 기획
content-pipeline --step plan --topic "포토부스 트렌드"
# 2단계: 본문 작성 (이전 단계 이벤트 자동 로드)
content-pipeline --step write
# 3단계: 카드뉴스 생성
content-pipeline --step design
# 4단계: 게시
content-pipeline --step publish
# 5단계: 성과 확인
content-pipeline --step track
이벤트 연동
각 단계는 이전 단계의 결과를 events/ 디렉토리에서 자동으로 읽어옵니다:
seo-plan-YYYY-MM-DD.json→ copywriting 입력content-draft-YYYY-MM-DD.json→ cardnews 입력content-published-YYYY-MM-DD.json→ daily-report 입력
옵션
--auto— 전체 단계 자동 실행--step <plan|write|design|publish|track>— 특정 단계만 실행--topic <주제>— 콘텐츠 주제 지정--skip-review— 각 단계 승인 없이 진행 (위험)
실행 흐름
자동 모드 (--auto)
- seo-content-planner 실행 →
events/seo-plan-YYYY-MM-DD.json생성 - 생성된 키워드/주제로 copywriting 실행 →
events/content-draft-YYYY-MM-DD.json생성 - 원고 기반 cardnews 생성 →
events/cardnews-ready-YYYY-MM-DD.json생성 - 이미지 + 캡션으로 social-publisher 실행 →
events/content-published-YYYY-MM-DD.json생성 - 게시 결과를 daily-report에 자동 포함
단계별 모드 (--step)
각 단계마다 승인 요청:
- 기획안 확인 → 승인 후 다음
- 원고 확인 → 승인 후 다음
- 카드뉴스 미리보기 → 승인 후 게시
예시
포토부스 활용 팁 콘텐츠 생성
content-pipeline --auto --topic "포토부스로 결혼식 추억 남기기"
결과:
- SEO 키워드: "포토부스 결혼식", "웨딩 포토부스" 등
- 블로그 원고 1200자
- 카드뉴스 5장 (1024x1024 정사각형)
- 인스타그램 자동 게시 (협업 계정 태그)
- 일일 리포트에 게시 결과 포함
단계별 수동 확인
# 1. 기획안 먼저 확인
content-pipeline --step plan --topic "대학 축제 포토부스"
# → events/seo-plan-2026-02-14.json 생성
# 2. 기획안 확인 후 원고 작성
content-pipeline --step write
# → events/content-draft-2026-02-14.json 생성
# 3. 원고 확인 후 디자인
content-pipeline --step design
# → 카드뉴스 5장 생성
# 4. 최종 확인 후 게시
content-pipeline --step publish
주의사항
--auto모드는 각 단계를 자동으로 진행하므로, 최종 게시 전 반드시 내용 확인- 이미지는 반드시 JPG 포맷 (PNG는 인스타그램 에러 가능)
- 게시 후
events/content-published-YYYY-MM-DD.json을 daily-report가 자동 수집
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 127 lines · 41 tokens per session scan A 5c284549f44d
content-pipeline is a skill published in the GitHub repository mupengi-bot/mupengism (10 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 1,025 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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