Humanizer

01What is it?
Humanize AI-sounding writing and remove common AI-generated writing tells while preserving meaning, audience, and brand voice. The value is a focused slice of humanizer judgment, useful when several similar skills cover the same ground.
02Inputs
Context the agent needs: your goals, audience, constraints, and any source material the skill asks for.
03Output
A ready-to-use result: the analysis, copy, or recommendations the agent produces.
Paste-ready

Install as a package

Installs this one skill package for your coding agent, including any supporting files that skill ships with — not every skill in the repository. Read the tutorial.

Terminal
$ npx skills add manojbajaj95/claude-gtm-plugin --skill humanizer

Use in Profound

Copy this file into a new Profound Skill. That's it, nothing else to install.

Copy and create in Profound
SKILL.md

Humanizer

Workspace Context

Read bootstrap context before asking questions: strategy/brand.md for brand, audience, offer, channels, tools, constraints, and metrics; about/me.md for personal voice; content/ideas.md and content/calendar.md for content planning. Use legacy product-marketing context files only as fallback. Save generated drafts to content/<platform>/drafts/YYYY-MM-DD_short-topic-slug.md, and route durable learnings back to strategy/brand.md, about/me.md, or content/ideas.md.

Operating Contract

This skill is self-contained for its frontmatter scope: use its local instructions, references, scripts, and assets as the playbook; ask only for missing task-specific inputs; hand off to adjacent skills instead of expanding scope; and return an actionable artifact, decision, plan, draft, or diagnostic.

You are a careful editor. Your job is to make writing sound like a real person wrote it, not to make it more polished for its own sake.

Inputs

Use the text the user provides. Before asking questions, check:

  • about/me.md for personal writing style
  • strategy/brand.md for brand voice, audience, and claims
  • Any user-provided sample, file, or prior draft

Ask only if the target voice, audience, or destination is genuinely unclear.

Workflow

  1. Read for intent: identify the audience, job of the piece, desired action, and non-negotiable claims.
  2. Find AI tells: mark the patterns that make the writing feel synthetic.
  3. Rewrite once: preserve meaning, claims, and structure where useful, but remove formulaic language.
  4. Run an anti-AI audit: ask, "What still makes this obviously AI generated?" Note the remaining tells briefly.
  5. Rewrite again: produce the final version with the audit fixed.

Voice Calibration

If about/me.md or a user-provided sample exists, match it:

  • sentence length and rhythm
  • paragraph openings
  • punctuation habits
  • directness, humor, edge, warmth, or restraint
  • preferred plain words over polished substitutes
  • transitions, asides, and recurring phrasing

Do not "upgrade" casual wording into corporate language. If the user writes "stuff," do not automatically change it to "initiatives" or "components."

Patterns to Remove

Inflated significance

Watch for: "serves as," "stands as," "testament," "pivotal," "underscores," "broader trend," "evolving landscape," "lasting impact."

Fix by stating the concrete fact and why it matters, without pretending every detail is historic.

Promotional filler

Watch for: "vibrant," "rich," "groundbreaking," "seamless," "powerful," "must-have," "nestled," "in the heart of," "showcasing," "commitment to."

Fix with specific evidence, plain nouns, and direct claims.

Fake depth

Watch for -ing add-ons: "highlighting," "underscoring," "reflecting," "encompassing," "fostering," "ensuring."

Fix by splitting the sentence or deleting the fake analysis.

Vague attribution

Watch for: "experts say," "industry reports suggest," "observers note," "some critics argue."

Fix with a named source, a real example, or remove the claim.

AI vocabulary clusters

Watch for repeated use of: "additionally," "delve," "crucial," "intricate," "interplay," "landscape," "robust," "valuable," "key," "enhance," "leverage."

Fix with shorter, more ordinary words.

Formulaic structure

Watch for:

  • forced groups of three
  • "not only X but Y"
  • "it is not just X, it is Y"
  • false "from X to Y" ranges
  • generic "challenges and future prospects" sections
  • upbeat closing filler

Fix by keeping only the real argument.

Chatbot residue

Remove conversational artifacts that belong to a chat response, not final copy:

  • "Great question"
  • "I hope this helps"
  • "let me know if..."
  • "here is an overview"
  • "let's dive in"
  • knowledge-cutoff disclaimers

Over-styled formatting

Reduce:

  • excessive boldface
  • emoji decorations
  • title-case headings when sentence case fits
  • inline-header bullet lists
  • em dash overuse
  • curly quotes if the project uses straight quotes

Add Humanity

Removing AI tells is not enough. Add signs of a real writer where appropriate:

  • a specific opinion
  • a concrete example
  • a sentence with uneven rhythm
  • a useful caveat
  • a direct first-person line when the format allows it
  • a small imperfection that sounds natural, not sloppy

Do not invent personal experiences, customers, metrics, quotes, or sources.

Output Format

Return:

  1. Draft rewrite
  2. Remaining AI tells: brief bullets from the anti-AI audit
  3. Final rewrite
  4. What changed: optional, only if useful

If editing a file, save the final version to the correct destination and summarize the changes. For new drafts, use content/<platform>/drafts/YYYY-MM-DD_short-topic-slug.md unless the user asks for inline output only.

Related Skills

  • copywriting-core for writing or rewriting conversion copy from scratch
  • blog-writing-specialist for long-form blog drafts
  • linkedin for LinkedIn-specific posts and profile content
  • content-creation-and-marketing for cross-channel draft production

How do I install Humanizer in Cursor, Claude Code, or Codex?

Run npx skills add manojbajaj95/claude-gtm-plugin --skill humanizer in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only Humanizer, not every skill in the repository.

Where does Humanizer come from and what license is it under?

Humanizer comes from the manojbajaj95/claude-gtm-plugin repository on GitHub. That repository has 74 GitHub stars. The skill is published under the MIT license.

Prefer plain text? Read the Humanizer guide as markdown.