li-post
Skill5 starsChanged 37 days agoMITView on GitHub
Write a LinkedIn post from a raw idea using 21 proven hook formulas, in the user's own voice, humanized so it does not read as AI. Use whenever the user wants a LinkedIn post, a hook, a draft for the feed, "post about X", "turn this into a LinkedIn post", or asks for hook options. Produces three hook options, one full draft, and a copy-ready block that is never published without an explicit yes.
9 other projects use a version of this, 5 of them edited.
Adopted by
Most recently taken up by
- furkanbilalakyuz/linkedin-agent-skill-tredited, first seen Nov 8, 2026
- HemanthMChakravarthy/linkedin-agent-skillsedited, first seen Nov 8, 2026
- mkmlabs-ai/linkedin-agentedited, first seen Nov 8, 2026
- mubaid/dsh-linkedin-agentword for word, first seen Oct 25, 2026
- robbiehaynes/job-searchword for word, first seen Oct 20, 2026
- kitloomlk-stack/marketing-seo-kitword for word, first seen Oct 15, 2026
Other versions9 projects use a version of this.
Word for word · 4
- Jakeschincariol/linkedin-agent-skill★ 514100% same
- kitloomlk-stack/marketing-seo-kit★ 0100% same
- mubaid/dsh-linkedin-agent★ 0100% same
- robbiehaynes/job-search★ 0100% same
Edited · 5
- mkmlabs-ai/linkedin-agent★ 494% same
- nessalazne/linkedin-agent-skill★ 394% same
- postzen-dev/linkedin-agent-skill★ 379% same
- HemanthMChakravarthy/linkedin-agent-skills★ 274% same
- furkanbilalakyuz/linkedin-agent-skill-tr★ 086% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository10 other files it gives its agents.
- li-auditSkill
- li-carouselSkill
- li-commentSkill
- li-dmSkill
- li-humanSkill
- li-inboxSkill
- li-planSkill
- li-profileSkill
- li-replySkill
- li-repurposeSkill
The file
We split this skill into the rules it gives an agent
8 rules. 3 are common, 0 are distinctive, and 5 are very specific to this project.
3
Common
Most of the 5 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 19
Read ~/.claude/linkedin/voice.md if it exists.
- Common: line 21
If it does not exist, ask for three of their own past posts, infer the voice from those, and write the file.
- Very specific: line 24
Read hooks.json in this folder.
- Common: line 26
If the idea is thin - "post about AI" - do not pad it.
- Very specific: line 49
1. Pick three hooks, not one: Run the idea through hooks.json and choose the three formulas that genuinely fit it.
- Very specific: line 56
3. Humanize it: Run the draft through /li-human before showing it.
- Common: line 79
One idea per post: If the draft has two, you have two posts.
- Very specific: line 88
Never fabricate: No invented metrics, clients, revenue figures or outcomes under the user's name, even as a placeholder.
“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
li-post
Turns one raw idea into a LinkedIn post that sounds like the person who posted it.
Before you write
- Read
~/.claude/linkedin/voice.mdif it exists. That file is the user's voice profile: how they talk, what they never say, who they are talking to. If it does not exist, ask for three of their own past posts, infer the voice from those, and write the file. Do not skip this and do not invent a voice. A post in the wrong voice is worse than no post. - Read
hooks.jsonin this folder. All 21 formulas, with templates, filled examples, what each is for, and how each one usually gets ruined. - If the idea is thin - "post about AI" - do not pad it. Ask one batched question: what happened, to whom, and what did it cost or return. A post needs one specific true thing. Get it before writing.
The shape
LinkedIn rewards dwell time, saves and comments, in that order. So:
Line 1 the hook. Alone. It has to survive truncation at ~140 chars mobile.
Line 2 the payoff of line 1, not setup for line 3.
Body short paragraphs, 1-3 lines each, blank line between every one.
No wall. The white space is the format.
The turn one line that reframes what came before.
Close one specific question, or one instruction. Never both.Length: 900-1,300 characters is the working range for a text post. Under 400 reads as a thought, not a post. Over 2,000 needs to earn every line, and the "see more" tap has to be paid for by line 2.
The loop
1. Pick three hooks, not one. Run the idea through hooks.json and choose
the three formulas that genuinely fit it. Different formulas, not three
variations of one. Show them as three numbered lines and say which you would
ship and why, in one sentence.
2. Draft the full post on the strongest hook.
3. Humanize it. Run the draft through /li-human before showing it. Every
post from this skill ships humanized. That is not an optional extra step, it
is the reason the draft is worth reading.
4. Print the block. Copy-ready, in a fenced block, exactly as it should be pasted. Then, underneath:
POST READY
hook: #17 Time Anchor
length: 1,140 characters
humanizer: 6 artefacts stripped, human score 84 PASS
post at: Tuesday 8:15am ET (from your plan)
Reply "yes" to log it, or tell me what to change.5. Never publish. This skill produces text. The user posts it. On "yes",
append the post to ~/.claude/linkedin/log.md with the date, the hook used
and the first line, so /li-audit has a history to work from later.
Rules that make the difference
- One idea per post. If the draft has two, you have two posts. Say so.
- Numbers over adjectives. "$4,200" beats "a lot". If the user has not given you a number, ask for one rather than writing around the hole.
- No engagement bait. "Thoughts?" and "Agree?" are dead. The closing question has to be one only this post could ask.
- Three hashtags maximum, at the bottom, and only if they are real categories someone follows.
- No links in the post body. LinkedIn suppresses posts with outbound links. Put the link in the first comment and say so in the receipt.
- Never fabricate. No invented metrics, clients, revenue figures or
outcomes under the user's name, even as a placeholder. If a number is
needed and unknown, leave
{{your number}}in the draft and flag it.
Example
/li-post we built an internal tool that cut proposal time from 5 hours to 20 minHOOKS
1. #17 Time Anchor Writing a proposal used to take me 5 hours. It now takes 20 minutes.
2. #12 Comparison A $12,000 proposal writer vs a weekend and a template. The weekend won.
3. #3 Mistake For two years I charged clients for hours I was wasting on formatting.
Shipping #17: the ratio is believable and the number is yours.Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

