Agent skill

Notes Humanizer

by mohitagw15856 in mohitagw15856/pm-claude-skills

Strips AI writing patterns from text and rewrites it to sound genuinely human — removing the statistical defaults, then adding earned voice calibrated to genre (opinion pieces get a person's voice…

MITAuto-check passedWriting & Content

Install Notes Humanizer

skills CLI
$ npx skills add mohitagw15856/pm-claude-skills --skill notes-humanizer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mohitagw15856/pm-claude-skills notes-humanizer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/notes-humanizer .claude/skills/notes-humanizer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
notes-humanizer
GitHub stars
1.4k
Token cost
~2.9k tokens
SKILL.md length
1,439 words
Files
1
Skills in repo
1,348
Repo updated
First seen
Licence
MIT

At a glance

Strips AI writing patterns from text and rewrites it to sound genuinely human — removing the statistical defaults, then adding earned voice calibrated to genre (opinion pieces get a person's voice…

  • Works in 4 steps: Calibrate to genre (do this first) → Audit → Inject (personal / persuasive genres… → …
  • A draft reads as AI-generated
  • SKILL.md covers Required Inputs, Output Structure, Instructions for Claude and Quality Checks, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Notes Humanizer is an agent skill from mohitagw15856/pm-claude-skills. Strips AI writing patterns from text and rewrites it to sound genuinely human — removing the statistical defaults, then adding earned voice calibrated to genre (opinion pieces get a person's voice; docs and summaries stay neutral) without ever faking humanity. Use when a draft reads as AI-generated, over-polished, or rhythmically uniform — including blog posts, emails, LinkedIn posts, or any prose that needs to sound like a real person wrote it. Produces a pattern audit, side-by-side comparison, itemised change…

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Writing & Content, covering Humanizing AI text, Blog and article writing and Social media posts. The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.

When your agent uses it

  • A draft reads as AI-generated
  • Rhythmically uniform — including blog posts
  • Any prose that needs to sound like a real person wrote it

Example prompts

  • “Use the notes-humanizer skill to strip AI writing patterns from text and rewrites it to sound genuinely human — removing the statistical defaults…”
  • “/notes-humanizer”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Calibrate to genre (do this first)
  2. Audit
  3. Inject (personal / persuasive genres only — see Phase 0)
  4. Report

What it can do on your machine

Read from SKILL.md and the folder at commit 1cbf1f0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Notes Humanizer loads about 2.9k tokens when it runs. Until then it costs about 145 tokens; SKILL.md has 1,439 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~145
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 1,439 words, ~2,859 tokens.

Download SKILL.mdSave it as .claude/skills/notes-humanizer/SKILL.md (or your agent's skills folder).
name
notes-humanizer
description
Strips AI writing patterns from text and rewrites it to sound genuinely human — removing the statistical defaults, then adding earned voice calibrated to genre (opinion pieces get a person's voice; docs and summaries stay neutral) without ever faking humanity. Use when a draft reads as AI-generated, over-polished, or rhythmically uniform — including blog posts, emails, LinkedIn posts, or any prose that needs to sound like a real person wrote it. Produces a pattern audit, side-by-side comparison, itemised change log, and clean rewritten output ready to paste.

Notes Humanizer

"Humanize this" prompts don't work because they don't know what to remove. AI text has specific, identifiable defaults — em dashes used as parenthetical substitutes, rule-of-three lists where all items have identical rhythm, sentences that hover between 15 and 20 words. Fix those defaults, add the signals human writers actually produce, and the text stops reading as synthetic. This skill does that systematically, in two phases, and shows you exactly what changed and why.

Credit: Originally created by Orel (TheIndiepreneur) — adapted and extended for this library.


Required Inputs

InputFormatNotes
Text to humanizePaste directly into the chatAny length. Works on paragraphs, full articles, social posts, emails.

No other inputs required. Claude will not ask clarifying questions before starting — it works with what's given.


Output Structure

Section 1: What Was Found

A plain-language audit of the AI patterns detected in the original text, before any rewriting:

PATTERNS DETECTED
─────────────────
Em dashes used as parenthetical substitutes: 3
Filler openers ("Let's dive in", "It's worth noting", etc.): 2
Rule-of-three lists with identical rhythm: 1
Sentence length variance: low (avg 17 words, range 14–21)
Hedging qualifiers: 4
Passive constructions where active is cleaner: 2
Section 2: Side-by-Side Comparison
OriginalRewritten
[original paragraph][rewritten paragraph]

(One row per paragraph or logical block. Short texts get the full comparison in one table. Long texts get the table collapsed to changed sections only, with unchanged sections noted.)

Section 3: Change Log

Every specific change made, with the reason:

CHANGES MADE
────────────────────────────────────────────────
1. Removed em dash in "success — and it shows"
   → Rewritten as "success (and it shows)"
   Why: em dash here is a parenthetical substitute, not a genuine pause

2. Deleted "It's worth noting that"
   Why: pure filler — the sentence is stronger without it

3. Broke rule-of-three list "X, Y, and Z"
   → "X and Y. Z is different — [expanded thought]"
   Why: all three items had identical rhythm; broke the pattern

4. Split a 30-word sentence where the point turned: "…and it failed. That's the problem."
   Why: the meaning lands on a short beat here — the brevity is earned, not inserted for variance

5. Added sentence starting with "But"
   Why: human writers do this; AI avoids it as a statistical default

6. Added specific example: [detail added]
   Why: the original made an abstract claim with no grounding detail

7. Added aside: "(I've watched this fail three times in a row)"
   Why: breaks fourth wall slightly; signals genuine perspective
Section 4: Clean Output

The full rewritten text, ready to copy and paste — no annotations, no formatting artifacts.

[Full rewritten text here]

Instructions for Claude

Phase 0: Calibrate to genre (do this first)

Before touching anything, decide what kind of text this is — the genre sets how far Phase 2 goes:

  • Neutral / informational (documentation, reference, summaries, status reports, official notices, most business comms): run Phase 1 only. Strip the tells and stop. Do not inject opinion, asides, or personality — a clean doc is the goal, not a voice. Injected "humanity" here reads as unprofessional.
  • Personal / persuasive / social (opinion pieces, blog posts, founder notes, LinkedIn, marketing, personal emails): run Phase 1 + Phase 2. Here earned voice is the point.
  • Unsure or mixed: default to the lighter touch (Phase 1, plus only the Phase 2 moves the content genuinely earns), and say which genre you assumed.

The single rule underneath: calibrate voice to the job of the text. Never dismantle useful structure (a scannable doc, a real list) just to look less templated.

Phase 1: Audit

Read the full text before making any changes. Identify and count every instance of these patterns:

Patterns to remove or rewrite:

PatternAction
Em dash used as parenthetical substitute (word — word where a comma or parenthesis would work)Replace with parentheses or rewrite the clause
"Let's dive in"Delete or replace with a direct first sentence
"In conclusion"Delete or rewrite as a genuine closing thought
"It's worth noting that"Delete — the sentence stands without it
"At its core"Delete or rewrite
"Game-changer"Replace with what the thing actually changes
"Delve"Replace with look, dig, explore — or rewrite the sentence
"Navigate" used metaphorically for non-navigation tasksReplace with a direct verb
Rule-of-three lists where all three items have identical grammatical structure and similar word countBreak the third item out as its own sentence or expand it
Sentences where every sentence in a paragraph falls in the 14–22 word rangeDeliberately add one very short sentence and one longer one
"Needless to say"Delete
"It's important to note that"Delete
Passive constructions where the active form is more directFlip to active

Do not remove every em dash — only the ones used as parenthetical substitutes. Do not remove all hedging — only empty hedging that adds no information.

Phase 2: Inject (personal / persuasive genres only — see Phase 0)

Only for text where earned voice is the point. These are options the content earns, not a checklist to complete — apply the ones the material genuinely supports and skip any that would be forced. A move inserted to hit a quota is itself an AI tell. Never fake humanity: no invented typos, no forced slang, no staged messiness, and no chopping or padding sentences just to manufacture rhythm variance.

  1. A genuine opinion or take (if the author clearly holds one). State the belief the text already implies, without hedging. Don't manufacture an opinion the author never expressed.

  2. A specific detail or example (only if a real one exists). Ground the most abstract claim in something concrete the author actually knows. Never invent a number, quote, date, name, or fact to sound specific — that's fake specificity, a worse tell than vagueness. If no real detail is available, ask the author for one or keep the honest abstraction; do not fabricate.

  3. An aside that steps out of the formal argument (where it fits the register). The signal most synthetic text lacks — but only in genres that welcome it, and only when it connects to a real point. Forced or cutesy asides are worse than none.

  4. Let a sentence be short where the point lands on a short beat. Follow the meaning, not a word count. Never shorten a sentence just to add "variance."

  5. Start a sentence with "And" or "But" only where the rhythm truly earns it. If no place does, don't add one — a random "But" is a tell, not a fix.

Show full SKILL.md (586 more words)Show less
Phase 3: Report

Present the output in the four-section structure defined above. The change log must list every individual change — not categories of change, but specific instances. If you changed three em dashes, list all three separately.

Handling edge cases
  • If the text is already mostly clean: Report what you found (or didn't find), make the few remaining changes, and note explicitly that the original was close. Don't invent problems.
  • If the text is very short (under 100 words): Skip the comparison table. Show original, then rewritten, then change log.
  • If the text is over 1,500 words: Process the full text but collapse the comparison table to changed sections only.

Quality Checks

  • Genre was assessed first (Phase 0); neutral/informational text got Phase 1 only, with no injected opinion, aside, or personality
  • Audit was completed before rewriting (patterns counted, not just detected)
  • Every removed pattern is listed in the change log with a specific reason
  • Em dashes were assessed individually — only parenthetical-substitute uses were removed
  • Rule-of-three lists: the rhythm was actually checked, not just the fact that there were three items
  • No fact, number, quote, date, or name was invented to add specificity
  • Any Phase 2 moves applied were earned by the content — none inserted to hit a quota (short sentence / "And"/"But" opener / aside added only where the material genuinely called for it, or not at all)
  • The specific detail or example added connects to an actual claim in the text, not floated in generically
  • The aside (if any) breaks the fourth wall slightly without being forced or cutesy
  • The change log lists specific instances, not categories
  • The clean output section has no annotations or formatting artifacts — ready to paste
  • If the original was already clean, that was stated explicitly rather than changes invented

Anti-Patterns

  • Do not fake humanity: no invented typos, no forced slang, no staged messiness, and no programmatic sentence-length variation added to hit a target — faked signals are themselves AI tells
  • Do not inject voice into neutral genres — documentation, summaries, reports, and official comms get the tells stripped and nothing added; personality there reads as unprofessional
  • Do not invent specificity — never add a number, quote, date, name, or fact that isn't real to make prose sound concrete; ask for the detail or keep the honest abstraction
  • Do not dismantle useful structure (a scannable layout, a genuine list) just to look less templated
  • Do not remove all em dashes — only the ones functioning as parenthetical substitutes should be removed; genuine dramatic pauses are valid
  • Do not invent problems to justify changes when the original is already clean — report what was found honestly, even if the answer is "this text is mostly fine"
  • Do not add the aside or opinion generically — the injected human signals must connect to an actual claim or argument in the text, not float in as decoration
  • Do not list changes by category in the change log — every individual change must be listed separately with the specific reason for that specific instance
  • Do not apply humanisation changes that alter the factual claims or intended meaning of the original text — the skill rewrites style, not substance

Example Trigger Phrases

  • "Humanize this text: [paste]"
  • "Use the notes-humanizer skill on this draft"
  • "This reads like ChatGPT wrote it — fix it: [paste]"
  • "Strip the AI out of this and make it sound like a real person wrote it"
  • "Run the humanizer on this LinkedIn post: [paste]"
  • "This has too many em dashes and rule-of-three lists — clean it up: [paste]"
  • "Make this email sound less robotic: [paste]"

© mohitagw15856, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/notes-humanizer of mohitagw15856/pm-claude-skills.

Open the folder on GitHubat commit 1cbf1f0

Compare with similar skills

Notes Humanizer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Notes Humanizer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Notes Humanizer this skillmohitagw15856/pm-claude-skills1.4k—~2.9kAutomated safety check: PassMIT
Content Strategy And Assemblyjacob-dietle/context-os111—~3.1kAutomated safety check: PassMIT
Writewaynesutton/markdown-site628—~3kAutomated safety check: PassMIT
Writerrileyhilliard/claude-essentials130—~2kAutomated safety check: PassMIT
Suede Ship CopyJasonColapietro/suede-creator-skills127—~6.2kAutomated safety check: PassMIT
SepiaNanako0129/sepia3k—~3.6kAutomated safety check: PassMIT

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Questions about Notes Humanizer

What does Notes Humanizer do?

Strips AI writing patterns from text and rewrites it to sound genuinely human — removing the statistical defaults, then adding earned voice calibrated to genre (opinion pieces get a person's voice…. Notes Humanizer is an agent skill from mohitagw15856/pm-claude-skills. Strips AI writing patterns from text and rewrites it to sound genuinely human — removing the statistical defaults, then adding earned voice calibrated to genre (opinion pieces get a person's voice; docs and summaries stay neutral) without ever faking humanity.

When should I use Notes Humanizer?

Notes Humanizer fits situations like: A draft reads as AI-generated; rhythmically uniform — including blog posts; any prose that needs to sound like a real person wrote it.

How do I install Notes Humanizer in Claude Code?

Run `npx skills add mohitagw15856/pm-claude-skills --skill notes-humanizer -a claude-code`. Or copy the skill folder (skills/notes-humanizer in mohitagw15856/pm-claude-skills) into .claude/skills/notes-humanizer in your project. Claude Code loads it when a task matches its description.

How do I install Notes Humanizer in Codex?

Run `npx skills add mohitagw15856/pm-claude-skills --skill notes-humanizer -a codex`. Or copy the skill folder (skills/notes-humanizer in mohitagw15856/pm-claude-skills) into .agents/skills/notes-humanizer in your project. Codex loads it when a task matches its description.

Can I use Notes Humanizer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mohitagw15856/pm-claude-skills --skill notes-humanizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/notes-humanizer, .gemini/skills/notes-humanizer, .github/skills/notes-humanizer and .opencode/skills/notes-humanizer in your project.

What does Notes Humanizer need to run?

SKILL.md names no scripts, command-line tools or credentials: Notes Humanizer is instructions for the agent only.

Does Notes Humanizer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Notes Humanizer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Notes Humanizer use?

Notes Humanizer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Notes Humanizer use?

About 2.9k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Notes Humanizer?

Skills that share tags, products or a category with Notes Humanizer: Content Strategy And Assembly (jacob-dietle/context-os, 111 stars), Write (waynesutton/markdown-site, 628 stars), Writer (rileyhilliard/claude-essentials, 130 stars) and Suede Ship Copy (JasonColapietro/suede-creator-skills, 127 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Notes Humanizer?

mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,433 GitHub stars. The repository holds 1,348 skills in this directory. The repository was last updated on October 8, 2026.

Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.