linkedin-humanizer

A LinkedIn editing tool that removes wording and formatting patterns often associated with machine-written text while keeping the original meaning. It adjusts vocabulary, sentence rhythm, lists, and tone to sound more like an individual writer.

In plain words
What is it for?
Use it before publishing or sending an AI-assisted LinkedIn post, message, or comment. It removes specified words and punctuation habits, varies sentence lengths, and makes the wording more conversational.
Why use it?
It helps prevent a draft from sounding artificial, repetitive, or overly polished. It is useful when an AI-assisted post, direct message, or comment does not match the writer's normal voice.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/styfinity/linkedin-engine/linkedin-humanizer
Any agent
npx skills add styfinity/linkedin-engine --skill linkedin-humanizer
Clone the repo
git clone --depth 1 https://github.com/styfinity/linkedin-engine

Made for: Claude Code, Codex.

Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 501 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00042 $0.00501
Opus 5 $0.00021 $0.00251
Sonnet 5 $0.00008 $0.00100
Haiku 4.5 $0.00004 $0.00050

Measured 2d ago against content hash 8d192b63b71d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

linkedin-humanizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/linkedin-humanizer/SKILL.md · 33 lines

What it actually says

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

  1. Remove every em-dash. Replace with a comma, a period, or " - ".
  2. 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.
  3. Break up rule-of-three symmetric lists. Real people do not write in perfect triplets.
  4. Delete fake-candid openers: "Let me be honest", "Here's the thing", "I'll be the first to admit". Cut straight to the point.
  5. Vary the sentence length. Uniform rhythm is the loudest AI tell. Put a short one next to a long one.
  6. 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.
  7. 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.
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 33 lines · 42 tokens per session scan A 8d192b63b71d

Subscribe to this mod's changes

linkedin-humanizer is a skill published in the GitHub repository styfinity/linkedin-engine (7 stars, last pushed 2mo ago), licensed MIT. It adds 42 tokens to every session and 501 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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