linkedin-humanizer
Skill9 starsChanged 4 months agoMITView on GitHub
Strip the AI fingerprints out of any draft (a post, a DM, a comment) so it reads like a real person wrote it. Use before publishing anything written or edited with AI.
7 other projects use a version of this.
Adopted by
Most recently taken up by
- uplika/uplika-plugintheir own version, first seen Nov 8, 2026
- 07001ec010shnk-svg/linkedin-agent-skillstheir own version, first seen Oct 25, 2026
- CodesbyFebin/linkedin-managertheir own version, first seen Oct 20, 2026
- AIProUK/linkedin-claude-skillstheir own version, first seen Oct 20, 2026
- sylvan-io/linkedin-skillstheir own version, first seen Oct 11, 2026
- subu53/linkedin_exponentialtheir own version, first seen Oct 8, 2026
Other versions7 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 7
- sergebulaev/linkedin-skills★ 5.4ksame name
- uplika/uplika-plugin★ 3same name
- AIProUK/linkedin-claude-skills★ 1same name
- sylvan-io/linkedin-skills★ 1same name
- 07001ec010shnk-svg/linkedin-agent-skills★ 0same name
- CodesbyFebin/linkedin-manager★ 0same name
- subu53/linkedin_exponential★ 0same name
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 repository28 other files it gives its agents.
- linkedin-booking-closerSkill
- linkedin-carousel-writerSkill
- linkedin-cold-reviverSkill
- linkedin-comment-engineSkill
- linkedin-comment-warmerSkill
- linkedin-connection-noteSkill
- linkedin-content-calendarSkill
- linkedin-engage-planSkill
- linkedin-engager-analyticsSkill
- linkedin-first-dmSkill
- linkedin-followup-adapterSkill
- linkedin-hook-labSkill
- linkedin-icp-definerSkill
- linkedin-objection-handlerSkill
- linkedin-onboardSkill
- linkedin-outreachSkill
- linkedin-post-autopsySkill
- linkedin-post-writerSkill
- linkedin-profile-auditorSkill
- linkedin-reply-triagerSkill
- linkedin-repurposerSkill
- linkedin-sell-by-chatSkill
- linkedin-signal-stackSkill
- linkedin-story-minerSkill
- linkedin-strategistSkill
- linkedin-voice-profilerSkill
- linkedin-warm-list-builderSkill
- linkedin-warm-trackerSkill
The file
We split this skill into the rules it gives an agent
7 rules. 0 are common, 7 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 7 edited versions we read keep these.
7
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 16
Remove every em-dash. Replace with a comma, a period, or " - ".
- Distinctive: line 19
Delete fake-candid openers: "Let me be honest", "Here's the thing", "I'll be the first to admit".
- Distinctive: line 21
Put the human back: one casual run-on with a comma splice, plain low-reading-level words, one direct un-hedged opinion, and a flat …
- Distinctive: line 22
Keep "I" not "we" in the hook.
- Distinctive: line 28
Never change the meaning or the claims.
- Distinctive: line 30
If anything still reads like AI after the pass, flag the specific phrase, do not silently let it through.
- Distinctive: line 31
No em-dashes in the output.
“Common” is measured: kept by at least 6 in 10 of the 7 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
LinkedIn Humanizer
The draft that reads like a machine wrote it gets ignored. This skill removes the tells and puts the human voice back in, without touching the meaning.
Inputs
- Any draft (a post, a DM, a comment): $ARGUMENTS
- The brief (persona voice, pains, offer) loads automatically, so use it to match the operator's real register.
Do this
- Remove every em-dash. Replace with a comma, a period, or " - ".
- Strip banned AI vocabulary: leverage, delve, landscape, navigate, utilize, foster, robust, supercharge, seamless, unlock, elevate, harness, empower, streamline, "game-changer", and any thesaurus word a person would not say out loud.
- Break up rule-of-three symmetric lists. Real people do not write in perfect triplets.
- Delete fake-candid openers: "Let me be honest", "Here's the thing", "I'll be the first to admit". Cut straight to the point.
- Vary the sentence length. Uniform rhythm is the loudest AI tell. Put a short one next to a long one.
- Put the human back: one casual run-on with a comma splice, plain low-reading-level words, one direct un-hedged opinion, and a flat statement (not a question) to end on.
- Keep "I" not "we" in the hook. The operator is one person, not a brand.
Output
The cleaned draft first. Then a short bullet diff: what was changed and why. Then a one-line verdict: PUBLISH, or STILL READS AI - fix these (name the exact phrases).
Rules
- Never change the meaning or the claims. Keep all numbers exactly as written.
- This is a polish pass, not a rewrite. If a line is already human, leave it.
- If anything still reads like AI after the pass, flag the specific phrase, do not silently let it through.
- No em-dashes in the output. Obviously.
- This skill only cleans drafts. It does not publish. The operator approves and posts.
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.

