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-recyclergit 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-recycler)<a href="https://agentmods.dev/skills/mupengi-bot/mupengism/content-recycler"><img src="https://agentmods.dev/badge/skills/mupengi-bot/mupengism/content-recycler/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-recycler"><img src="https://agentmods.dev/badge/skills/mupengi-bot/mupengism/content-recycler.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 | $0.00019 | $0.00663 |
| Opus 5.5 | $0.00008 | $0.00265 |
| Sonnet 5.5 | $0.00004 | $0.00133 |
| Haiku 4.5 | $0.00002 | $0.00066 |
Grade A, and why
content-recycler 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.
What it actually says
content-recycler
기존 콘텐츠를 다른 포맷이나 플랫폼에 맞게 자동으로 재가공하는 스킬입니다.
기능
- 입력: 기존 콘텐츠 (블로그글, 스레드, 카드뉴스, 유튜브 요약)
- 변환:
- 블로그 → 카드뉴스
- 스레드 → 블로그
- 유튜브 요약 → 카드뉴스
- 블로그 → 스레드
- 플랫폼별 포맷 자동 조정 (글자수, 이미지 규격, 톤앤매너)
사용법
트리거 키워드:
- "재가공"
- "recycler"
- "이 콘텐츠 다른 형태로"
- "리사이클"
예시:
이 블로그 글을 카드뉴스로 재가공해줘
[원본 콘텐츠 링크 또는 텍스트]
변환 규칙
블로그 → 카드뉴스
- 핵심 메시지 3-5개로 압축
- 각 카드: 제목 + 핵심 1-2문장
- 이미지 규격: 1024x1024 (Instagram 1:1)
- 폰트: 굵고 읽기 쉽게
- 색상: 브랜드 일관성 유지
스레드 → 블로그
- 스레드 순서대로 섹션 구성
- 도입부 추가 (맥락 설명)
- 헤더 구조화 (H2, H3)
- 마무리 요약/CTA 추가
유튜브 요약 → 카드뉴스
- 타임라인별 핵심 포인트 추출
- 인용구/통계 강조
- 첫 카드: 썸네일+제목
- 마지막 카드: 요약+링크
블로그 → 스레드
- 1 트윗 = 1 핵심 아이디어
- 280자 제한 준수
- 스레드 연결성 유지 (1/n)
- 이미지 첨부 시 16:9 또는 1:1
플랫폼별 규격
| 플랫폼 | 글자수 | 이미지 규격 | 특이사항 |
|---|---|---|---|
| 2200자 | 1024x1024 (1:1) | 첫 3줄이 미리보기 | |
| Twitter/X | 280자/트윗 | 1200x675 (16:9) | 스레드 25개까지 |
| Threads | 500자 | 1080x1350 (4:5) | 연속 게시 지원 |
| 네이버 블로그 | 무제한 | 가변 | SEO 키워드 중요 |
출력
재가공된 콘텐츠 + 메타정보:
- 원본 소스
- 변환 타입
- 플랫폼 최적화 팁
- 예상 도달률/인게이지먼트 (선택적)
content-recycler | 무펭이 🐧
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 · 82 lines · 19 tokens per session scan A 840f86c5fc00
content-recycler is a skill published in the GitHub repository mupengi-bot/mupengism (10 stars, last pushed 3mo ago), licensed MIT. It adds 19 tokens to every session and 663 once invoked, about $0.0001 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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