DEDUPED Hot AI repos, turned into use cases Get 5 a day

What you can do with Linkedin Agent Skill

A set of eleven free Claude skills that write LinkedIn posts, comments, replies, profile edits, weekly plans and audits, with a local humanizer that cleans and scores drafts before you post them by hand.

Trended earlier

Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk.

5 use cases

  • Turn one idea into a LinkedIn post you approve

    Write a full post from a single idea, with three hook options and a humanized draft.

    View prompt
    Install the skills from https://github.com/Jakeschincariol/linkedin-agent-skill, fill in voice.md from the three posts at <path to your posts>, then run /li-post on the idea: <your idea>. Expected output: three hook options and one full draft with no em dashes and no invented numbers. Verify that any figure you did not supply appears as {{your number}}.
  • Strip AI tells from a draft and score it before posting

    Clean invisible characters and stock phrases from any draft, then get a five-check human score.

    View prompt
    Use the li-human scripts in https://github.com/Jakeschincariol/linkedin-agent-skill on <path to draft file>. Run humanize.py with --report, then detect.py, and return the cleaned text, the change report and the HUMAN SCORE. Verify that the score is shown for both the original and the cleaned file.
  • Score your LinkedIn profile and fix the weakest parts first

    Get a 100-point profile score and a rewrite ordered by what loses the most points.

    View prompt
    Using the li-profile skill from https://github.com/Jakeschincariol/linkedin-agent-skill, score the profile text I paste from <path or paste of profile> and return the total out of 100 plus rewrites in fix-first order. Verify that no metric, client or outcome appears unless I supplied it.
  • Plan a week of LinkedIn posts and 10 engagement targets

    Get a weekly plan of what to post, when to post it, and who to comment on.

    View prompt
    Run the li-plan skill from https://github.com/Jakeschincariol/linkedin-agent-skill for the week of <date>, using my voice file and the topics: <topics>. Expect a plan written to ~/.claude/linkedin/plan.md with posts, timing and 10 engagement targets. Verify that the file exists and that no target was invented without my input.
  • Find which of your past posts actually worked

    Rank your published posts by engagement rate and reach multiple, not raw impressions.

    View prompt
    Use the li-audit skill from https://github.com/Jakeschincariol/linkedin-agent-skill on the post data I paste from <source of post data>. Expect a ranking by engagement rate and reach multiple, with a short note on each. Verify that every number in the output comes from the data I supplied.

How to use Linkedin Agent Skill

  1. Check you have what it needs: Claude access, either Claude Code for installing the skills or a chat where you can paste a SKILL.md; A LinkedIn account you will post from yourself, since the skills never post for you; Python 3 for the humanizer scripts, which need no extra dependencies.
  2. Open Jakeschincariol/linkedin-agent-skill on GitHub and read the README and license.
  3. Run git clone https://github.com/Jakeschincariol/linkedin-agent-skill.git in a terminal.
  4. Run cp -r linkedin-agent-skill/skills/li-* ~/.claude/skills/ to install the skills globally.
  5. Run cp templates/voice.md ~/.claude/linkedin/voice.md from inside the cloned repo, then fill in the file or ask Claude to write it from three of your posts. (inferred, check the README)
  6. In Claude Code, type /li-post and give it one idea in a sentence or two.

These steps come from our top use case, Turn one idea into a LinkedIn post you approve, which also has a copy-paste agent prompt.

Linkedin Agent Skill alternatives · Best AI repos for Sales and marketing

About this repo

Requirements

  • Claude access, either Claude Code for installing the skills or a chat where you can paste a SKILL.md
  • A LinkedIn account you will post from yourself, since the skills never post for you
  • Python 3 for the humanizer scripts, which need no extra dependencies
  • Three of your own past posts, or a filled-in templates/voice.md, so drafts match your voice
Maintain Linkedin Agent Skill? Add the Featured on Deduped badge

Paste this into your README:

[![Featured on Deduped](https://dedupedai.com/badge/jakeschincariol-linkedin-agent-skill.svg)](https://dedupedai.com/use-cases/jakeschincariol-linkedin-agent-skill/?ref=badge)

More badge styles and HTML

Questions about Linkedin Agent Skill

What is Linkedin Agent Skill?

A set of eleven free Claude skills that write LinkedIn posts, comments, replies, profile edits, weekly plans and audits, with a local humanizer that cleans and scores drafts before you post them by hand. It is an open-source project on GitHub: https://github.com/Jakeschincariol/linkedin-agent-skill.

Who is Linkedin Agent Skill for?

Solo founders, creators and job seekers who run their own LinkedIn profile and want drafts that sound like them, not like a model.

What can I do with Linkedin Agent Skill?

5 use cases so far, for example: Turn one idea into a LinkedIn post you approve; Strip AI tells from a draft and score it before posting; Score your LinkedIn profile and fix the weakest parts first. Each has steps and a copy-paste agent prompt.

What do I need to run Linkedin Agent Skill?

Claude access, either Claude Code for installing the skills or a chat where you can paste a SKILL.md; A LinkedIn account you will post from yourself, since the skills never post for you; Python 3 for the humanizer scripts, which need no extra dependencies; Three of your own past posts, or a filled-in templates/voice.md, so drafts match your voice.

What are alternatives to Linkedin Agent Skill?

Other hot AI repos in Sales and marketing: GTM Cofounder, Geolook, Agentic Product Demo, Growth Engineer, Founder Skill.

Is Linkedin Agent Skill safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.