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 crealwork/ai-marketing-kit --skill content-repurposegit clone --depth 1 https://github.com/crealwork/ai-marketing-kitWrote 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/crealwork/ai-marketing-kit/content-repurpose)<a href="https://agentmods.dev/skills/crealwork/ai-marketing-kit/content-repurpose"><img src="https://agentmods.dev/badge/skills/crealwork/ai-marketing-kit/content-repurpose.svg" alt="Measured on agentmods" 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 | $0.00129 | $0.00915 |
| Opus 5 | $0.00064 | $0.00458 |
| Sonnet 5 | $0.00026 | $0.00183 |
| Haiku 4.5 | $0.00013 | $0.00092 |
Grade A, and why
content-repurpose 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 8d 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 Repurpose
플랫폼 간 콘텐츠 변환. 원칙: 번역이 아니라 재구성 — 같은 핵심 주장을 타깃 플랫폼의 네이티브 문법으로 다시 쓴다. 복붙 크로스포스팅은 두 플랫폼 모두에서 성과가 죽는다.
Process
- 원문 수집 — 유저가 준 텍스트/링크. 링크면 본문을 긁어온다.
- 코어 추출 — 핵심 주장 1개, 근거/사례, 훅으로 쓸 수 있는 문장, 숫자.
- 타깃 문법으로 재작성 (아래 표) + humanizer 룰 적용 (AI 티 제거).
- 유저 승인 — 변환본을 보여주고 확인. 발행/예약은 organic-social로.
플랫폼 문법 (2026 기준)
| Threads | ||
|---|---|---|
| 길이 | 포스트당 500자 — 길면 체인으로 분할 | 첫 화면(~210자)이 승부, 전체 1,300자 내외 |
| 훅 | 첫 문장이 전부 — 스크롤 중 낚아채는 한 줄 | 첫 3줄이 "...더보기" 위에 노출 — 여기서 클릭을 만든다 |
| 톤 | 캐주얼, 반말/구어체 허용, 개인 경험 | 전문적이되 인간적 — 스토리 → 인사이트 → 교훈 구조 |
| 포맷 | 짧은 문단, 이모지 절제 | 한 줄 단위 줄바꿈 넉넉히, 리스트/화살표 활용 |
| 해시태그 | 안 쓰거나 1개 | 3–5개, 본문 끝 |
| 링크 | 본문에 가능 | 본문 링크는 도달 패널티 — 첫 댓글에 |
| CTA | 가볍게 ("여러분은?") | 명확하게 (팔로우/댓글/저장 유도) |
방향별 변환 규칙
Threads → LinkedIn: 체인 여러 개를 하나의 서사로 합친다. 구어체 훅은 유지하되 반말 → 존댓말/professional 톤. 개인 경험을 앞세우고 마지막에 업무적 교훈 1개. 숫자/성과가 있으면 첫 3줄 안으로 끌어올린다.
LinkedIn → Threads: 긴 글을 해체한다 — 가장 센 주장 1개만 남기고 나머지는 버리거나 체인 2–3개로. 존댓말 유지하되 문장을 반으로 자르고, "결론부터" 순서로 뒤집는다. 해시태그 제거.
공통 금지: 플랫폼 이름 흔적 남기기("스레드에서 쓴 글인데"), 원문에 없는 주장 추가, 남의 원문 무단 리퍼포즈 (본인/브랜드 콘텐츠만).
시리즈 운영
원문 1개 → 변환 N개가 아니라, 원문 풀에서 주장 단위로 쪼개 플랫폼별 캘린더에 배치한다 (긴 글 1개 = Threads 체인 1 + LinkedIn 포스트 1 + 후속 짧은 포스트 2–3). 같은 주장을 두 플랫폼에 올릴 땐 24시간 이상 간격. 캘린더 확정 후 발행은 organic-social의 배치 스케줄로.
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.
- 8d ago First seen · 50 lines · 129 tokens per session scan A 02e9ea151278
content-repurpose is a skill published in the GitHub repository crealwork/ai-marketing-kit (18 stars, last pushed 1mo ago), licensed MIT. It adds 129 tokens to every session and 915 once invoked, about $0.0006 per session on Opus 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 2026-08-30.
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