jakeschincariol/linkedin-agent-skill

li-carousel

- Build a LinkedIn document post (carousel) - slide-by-slide copy, the cover that earns the swipe, and the PDF to upload.

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/jakeschincariol/linkedin-agent-skill --skill li-carousel

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

li-carousel

Document posts are the highest-dwell format on LinkedIn, because a swipe is counted and a scroll is not. The format rewards one idea broken into steps. It punishes a text post cut into pieces.

When to use it instead of a text post

Use a carousel when the idea has sequence - steps, a countdown, a before/after progression, a framework with parts. Use a text post when the idea is one claim. Splitting one claim across eight slides is the most common way carousels fail, and if that is what the user has, say so and hand them to /li-post.

Structure

8-12 slides. Under 8 is a text post. Over 12 and the completion rate falls off a cliff.

1        COVER      the hook, 6 words or fewer, plus one line of promise
2        THE STAKE  why this matters, in one sentence
3-N      ONE IDEA PER SLIDE. A headline of 3-7 words, and at most 25 words
                    under it. If a slide needs a paragraph, it is two slides.
N+1      RECAP      the whole thing as a list, so the screenshot is useful
LAST     CTA        one action. Follow, comment a keyword, or the link. One.

Slide copy rules

  • Slide 1 is 80% of the result. Six words. Big. The rest of the deck

cannot save a cover nobody swipes.

  • Number every slide (3/10). Completion goes up when people can see the

end.

  • No slide is a paragraph. If you cannot say it in 25 words, split it.
  • The recap slide is the one people screenshot. Make it standalone.
  • The user's handle on every slide, small, bottom corner. Screenshots

travel without you.

Making the PDF

LinkedIn wants a PDF, 1080x1350 (4:5) for maximum feed real estate, under 100MB, under 300 pages. Build it as HTML and print to PDF:

bash
# one page per slide, 1080x1350, no margins
# then: Chrome headless --print-to-pdf, or any HTML-to-PDF you already use

Write the HTML with one <section> per slide, width:1080px; height:1350px; page-break-after:always, a single accent colour, and type no smaller than 28px - people read these on a phone at thumbnail size. If the user has a brand skill or design system in this project, use it and do not invent a palette.

Output

The slide-by-slide copy first, as a numbered list the user can read in ten seconds. Then the accompanying post text - a carousel still needs 2-3 lines above it, which is the actual hook in the feed. Run both through /li-human. Then build the PDF only if the user approves the copy.

Nothing is uploaded to LinkedIn. The user posts the PDF themselves.

관련 작업

같은 저장소의 Skills

더 많은 Skills

모든 Skills
jakeschincariol
커뮤니티

li-audit

- Post-mortem on what the user has already published - which posts actually worked, why, and what to stop doing. Use when the user pastes their LinkedIn analytics or past posts and asks "what's working", "why did this flop", "read my analytics", "audit my content", or wants to know what to double down on.

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1
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업데이트
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li-comment

- Write comments on other people's LinkedIn posts that read as a person with an opinion, not a bot. Use when the user pastes a post and wants a comment, says "comment on this", "engage with this", "what do I say here", or wants a batch of comments for their engagement round.

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1
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업데이트
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li-dm

- Write connection notes and DM follow-ups that get replies - the 200-character invite, the first message, and the two follow-ups. Use when the user says "write a connection request", "DM this person", "outreach message", "how do I follow up", or is reaching out to someone specific on LinkedIn.

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1
GitHub Stars
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업데이트
9월 17일
jakeschincariol
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li-human

- Strip the machine fingerprint out of any draft - em dashes, AI slop words, invisible watermark characters - and score it against a five-check detection panel before it goes out. Use whenever text needs to sound human, when the user says humanize, "does this sound like AI", "remove the em dashes", "de-slop this", "will this get flagged", or before any LinkedIn post, comment, reply or DM is shown to the user.

설치 수
1
GitHub Stars
2.4천
업데이트
9월 17일