Turn one long asset - a YouTube video, podcast, newsletter, blog post, transcript or client call - into a week of LinkedIn posts. Use when the user says "repurpose this", "turn this into posts", "I have a video/newsletter/ transcript", or pastes a long piece of content and wants it on LinkedIn.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
One good long asset contains four to six posts. Most people extract one and throw the rest away.
A transcript, an article, a newsletter, a script, a call summary. If the user gives a YouTube URL and there is a transcript tool available in the session, use it; otherwise ask them to paste the text. Read the whole thing before extracting anything.
A summary of a video is not a post. Nobody wants the summary. Go through the asset and pull out the things that stand alone:
| pull | what it is |
|---|---|
| Claims | every sentence that would start an argument |
| Numbers | every figure, cost, duration, percentage |
| Stories | every moment with a person, a scene and a cost |
| Mechanisms | every "the way this works is..." explanation |
| Mistakes | every admission of something that went wrong |
| Lines | every sentence that is already quotable as-is |
List what you found, with counts, before writing anything. If the asset yields fewer than four items, it is thin, and four posts squeezed out of it will be thin too. Say that.
Each extract becomes one post, and each post has to stand completely on its own - the reader has not seen the video and never will. Never write "as I mentioned in my latest video". The post is the thing.
Assign a hook formula from li-post/hooks.json to each, and vary them: five
posts from one source with the same hook shape reads as a content mill.
Order them across the week so the strongest claim goes first, the story goes midweek, and the mechanism post goes last, when people who liked the earlier ones are watching for it.
SOURCE: "Why we killed discovery calls" (18 min, 3,400 words)
FOUND 4 claims, 6 numbers, 2 stories, 3 mechanisms, 1 mistake, 5 quotable lines
WEEK
TUE #1 Contrarian Discovery calls are a tax you pay for a bad website
WED #17 Time Anchor We got 6 hours a week back by deleting one calendar link
THU #9 Cold Open "Can we just hop on a quick call?"
FRI #21 Direct Value The 4-question form that replaced the call. Steal it.
Say "write Tuesday" and I will draft it.
Then draft on request, one at a time, each through /li-post and /li-human.
Do not dump four finished posts at once - they will all sound the same, and
the user will edit none of them.
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build a LinkedIn document post (carousel) - slide-by-slide copy, the cover that earns the swipe, and the PDF to upload. Use when the user says "carousel", "document post", "slides for LinkedIn", "turn this into a carousel", or has a list-shaped idea that would die as a text post.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Triage the LinkedIn inbox - sort connection requests and DMs into leads, recruiters, peers and spam, and draft the replies worth sending. Use when the user says "my inbox is a mess", "triage my DMs", "should I reply to this", pastes a batch of LinkedIn messages, or is drowning in connection requests.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.