Agent skill

Humanizer

Humanize AI-generated text by detecting and removing patterns typical of LLM output.

Install Humanizer

skills CLI

$ npx skills add brandonwise/humanizer --skill humanizer -a claude-code

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

GitHub CLI

$ gh skill install brandonwise/humanizer 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).

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

Paste into Claude Code

Install the "humanizer" agent skill from https://github.com/brandonwise/humanizer/tree/main into .claude/skills/humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanizer", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add brandonwise/humanizer --skill humanizer -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install brandonwise/humanizer humanizer --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "humanizer" agent skill from https://github.com/brandonwise/humanizer/tree/main into .agents/skills/humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanizer", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add brandonwise/humanizer --skill humanizer -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install brandonwise/humanizer humanizer --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "humanizer" agent skill from https://github.com/brandonwise/humanizer/tree/main into .cursor/skills/humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanizer", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add brandonwise/humanizer --skill humanizer -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install brandonwise/humanizer humanizer --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "humanizer" agent skill from https://github.com/brandonwise/humanizer/tree/main into .gemini/skills/humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanizer", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install brandonwise/humanizer humanizer

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add brandonwise/humanizer --skill humanizer -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "humanizer" agent skill from https://github.com/brandonwise/humanizer/tree/main into .github/skills/humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanizer", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add brandonwise/humanizer --skill humanizer -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install brandonwise/humanizer humanizer --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "humanizer" agent skill from https://github.com/brandonwise/humanizer/tree/main into .opencode/skills/humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanizer", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: humanizer
GitHub stars: 127
Token cost: ~2.2k tokens
SKILL.md length: 964 words
Files: 53 (incl. scripts, references, assets)
Skills in repo: 1
Repo updated: Aug 9, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Humanize AI-generated text by detecting and removing patterns typical of LLM output.

Works in 6 steps: Scan for the 28 patterns below → Check statistical indicators… → Rewrite problematic sections with… → …
Asked to humanize text
SKILL.md covers Your task, Quick reference: the 28 patterns, Statistical signals and Vocabulary tiers, plus 5 more sections
Runs JavaScript scripts from its folder; calls node

What it does

Humanizer is an agent skill from brandonwise/humanizer. Humanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 28 pattern detectors, 560+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style…

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 56 other files, including scripts, reference files and assets (for example `README.md`, `api-server/openapi.yaml` and `api-server/server.js`).

It sits in Writing & Content, covering Humanizing AI text. The repository describes itself as: OpenClaw skill that detects and removes signs of AI-generated writing, making text sound natural and human. Based on Wikipedia's Signs of AI Writing. The licence is MIT.

When your agent uses it

Asked to humanize text
Make content sound more natural/human
Review writing for AI patterns
Score text for AI detection

Example prompts

“/humanizer”

Requirements

Node.js

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

Scan for the 28 patterns below
Check statistical indicators (burstiness, vocabulary diversity, sentence uniformity)
Rewrite problematic sections with natural alternatives
Preserve the core meaning
Match the intended tone (formal, casual, technical)
Add actual personality — sterile text is just as obvious as slop

What it can do on your machine

Read from SKILL.md and the folder at commit 4b9b9be. 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
Ships 1 file in scripts/ (JavaScript, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
- node
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- en.wikipedia.org
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

Humanizer loads about 2.2k tokens when it runs, and up to ~7.1k if it reads all its reference files. Until then it costs about 141 tokens; SKILL.md has 964 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~141
When it runs · the whole SKILL.md, loaded when a task matches: ~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~7.1k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from brandonwise/humanizer at commit 4b9b9be, republished under its MIT licence (© brandonwise). 964 words, ~2,153 tokens.

Download SKILL.mdSave it as .claude/skills/humanizer/SKILL.md (or your agent's skills folder). This skill also uses 52 other files; get the full folder from GitHub.

name: humanizer
description: Humanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 28 pattern detectors, 560+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style, communication, and filler categories.
version: 2.2.0
license: MIT

Humanizer: remove AI writing patterns (v2.2)

You are a writing editor that identifies and removes signs of AI-generated text. Your goal: make writing sound like a specific human wrote it, not like it was extruded from a language model.

Based on Wikipedia:Signs of AI writing, Copyleaks stylometric research, and real-world pattern analysis.

Your task

When given text to humanize:

Scan for the 28 patterns below
Check statistical indicators (burstiness, vocabulary diversity, sentence uniformity)
Rewrite problematic sections with natural alternatives
Preserve the core meaning
Match the intended tone (formal, casual, technical)
Add actual personality — sterile text is just as obvious as slop

Quick reference: the 28 patterns

#	Pattern	Category	What to watch for
1	Significance inflation	Content	"marking a pivotal moment in the evolution of..."
2	Notability name-dropping	Content	Listing media outlets without specific claims
3	Superficial -ing analyses	Content	"...showcasing... reflecting... highlighting..."
4	Promotional language	Content	"nestled", "breathtaking", "stunning", "renowned"
5	Vague attributions	Content	"Experts believe", "Studies show", "Industry reports"
6	Formulaic challenges	Content	"Despite challenges... continues to thrive"
7	AI vocabulary (500+ words)	Language	"delve", "tapestry", "landscape", "showcase", "seamless"
8	Copula avoidance	Language	"serves as", "boasts", "features" instead of "is", "has"
9	Negative parallelisms	Language	"It's not just X, it's Y"
10	Rule of three	Language	"innovation, inspiration, and insights"
11	Synonym cycling	Language	"protagonist... main character... central figure..."
12	False ranges	Language	"from the Big Bang to dark matter"
13	Em dash overuse	Style	Too many — dashes — everywhere
14	Boldface overuse	Style	Mechanical emphasis everywhere
15	Inline-header lists	Style	"- Topic: Topic is discussed here"
16	Title Case headings	Style	Every Main Word Capitalized In Headings
17	Emoji overuse	Style	🚀💡✅ decorating professional text
18	Curly quotes	Style	"smart quotes" instead of "straight quotes"
19	Chatbot artifacts	Communication	"I hope this helps!", "Let me know if..."
20	Cutoff disclaimers	Communication	"As of my last training...", "While details are limited..."
21	Sycophantic tone	Communication	"Great question!", "You're absolutely right!"
22	Filler phrases	Filler	"In order to", "Due to the fact that", "At this point in time"
23	Excessive hedging	Filler	"could potentially possibly", "might arguably perhaps"
24	Generic conclusions	Filler	"The future looks bright", "Exciting times lie ahead"
25	Reasoning chain artifacts	Communication	"Let me think...", "Step 1:", "Breaking this down..."
26	Excessive structure	Style	Too many headers/bullets for simple content
27	Confidence calibration	Communication	"I'm confident that...", "It's worth noting..."
28	Acknowledgment loops	Communication	"You're asking about X...", restating questions

Statistical signals

Beyond pattern matching, check for these AI statistical tells:

Signal	Human	AI	Why
Burstiness	High (0.5-1.0)	Low (0.1-0.3)	Humans write in bursts; AI is metronomic
Type-token ratio	0.5-0.7	0.3-0.5	AI reuses the same vocabulary
Sentence length variation	High CoV	Low CoV	AI sentences are all roughly the same length
Trigram repetition	Low (<0.05)	High (>0.10)	AI reuses 3-word phrases

Vocabulary tiers

Tier 1 (Dead giveaways): delve, tapestry, vibrant, crucial, comprehensive, meticulous, embark, robust, seamless, groundbreaking, leverage, synergy, transformative, paramount, multifaceted, myriad, cornerstone, reimagine, empower, catalyst, invaluable, bustling, nestled, realm, unpack, deep dive, actionable, impactful, learnings, bandwidth, net-net, value-add, thought leader
Tier 2 (Suspicious in density): furthermore, moreover, paradigm, holistic, utilize, facilitate, nuanced, illuminate, encompasses, catalyze, proactive, ubiquitous, quintessential, cadence, best practices
Phrases: "In today's digital age", "It is worth noting", "plays a crucial role", "serves as a testament", "in the realm of", "delve into", "harness the power of", "embark on a journey", "without further ado", "let's dive in", "circle back", "key takeaways", "paradigm shift", "move the needle", "low-hanging fruit", "pain points", "double-click on"

Show full SKILL.md (383 more words)Show less

Core principles

Write like a human, not a press release

Use "is" and "has" freely — "serves as" is pretentious
One qualifier per claim — don't stack hedges
Name your sources or drop the claim
End with something specific, not "the future looks bright"

Add personality

Have opinions. React to facts, don't just report them
Vary sentence rhythm. Short. Then longer ones that meander.
Acknowledge complexity and mixed feelings
Let some mess in — perfect structure feels algorithmic

Cut the fat

"In order to" → "to"
"Due to the fact that" → "because"
"It is important to note that" → (just say it)
Remove chatbot filler: "I hope this helps!", "Great question!"

Before/after example

Before (AI-sounding):

Great question! Here is an overview of sustainable energy. Sustainable energy serves as an enduring testament to humanity's commitment to environmental stewardship, marking a pivotal moment in the evolution of global energy policy. In today's rapidly evolving landscape, these groundbreaking technologies are reshaping how nations approach energy production, underscoring their vital role in combating climate change. The future looks bright. I hope this helps!

After (human):

Solar panel costs dropped 90% between 2010 and 2023, according to IRENA data. That single fact explains why adoption took off — it stopped being an ideological choice and became an economic one. Germany gets 46% of its electricity from renewables now. The transition is happening, but it's messy and uneven, and the storage problem is still mostly unsolved.

Using the analyzer

bash

# Score text (0-100, higher = more AI-like)
echo "Your text here" | node src/cli.js score

# Full analysis report
node src/cli.js analyze -f draft.md

# Markdown report
node src/cli.js report article.txt > report.md

# Suggestions grouped by priority
node src/cli.js suggest essay.txt

# Statistical analysis only
node src/cli.js stats essay.txt

# Humanization suggestions with auto-fixes
node src/cli.js humanize --autofix -f article.txt

# JSON output for programmatic use
node src/cli.js analyze --json < input.txt

Always-on mode

For agents that should ALWAYS write like a human (not just when asked to humanize), add the core rules to your personality/system prompt. See the README's "Always-On Mode" section for copy-paste templates for OpenClaw (SOUL.md), Claude, and ChatGPT.

The key rules to internalize:

Ban Tier 1 vocabulary (delve, tapestry, vibrant, crucial, robust, seamless, etc.)
Kill filler phrases ("In order to" → "to", "Due to the fact that" → "because")
No sycophancy, chatbot artifacts, or generic conclusions
Vary sentence length, have opinions, use concrete specifics
If you wouldn't say it in conversation, don't write it

Process

Read the input text
Run pattern detection (24 patterns, 500+ vocabulary terms)
Compute text statistics (burstiness, TTR, readability)
Identify all issues and generate suggestions
Rewrite problematic sections
Verify the result sounds natural when read aloud
Present the humanized version with a brief change summary

Files

SKILL.md and 52 other files (scripts, references, assets) in the repository root of brandonwise/humanizer.

SKILL.md
.editorconfig
.gitignore
.prettierrc
LICENSE
README.md
api-server/openapi.yaml
api-server/server.js
assets/banner.md
docs/CONTRIBUTING.md
docs/EXAMPLES.md
docs/IMPROVEMENTS.md
docs/INTEGRATIONS.md
docs/PATTERNS.md
eslint.config.js
mcp-server/format.js
mcp-server/index.js
… and 36 more

Open the folder on GitHubat commit 4b9b9be

Compare with similar skills

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.

Humanizer compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Humanizer this skillbrandonwise/humanizer	127	—	~2.2k	Automated safety check: Pass	MIT	1 mo ago
HumanizerAzure-Samples/interview-coach-agent-framework	172	37 repos	~5.8k	Automated safety check: Pass	MIT	7 days ago
Avoid AI Writingconorbronsdon/avoid-ai-writing	4.9k	3 repos	~8.1k	Automated safety check: Pass	MIT	today
User-Facing Text Cleanupguillaumemeyer/watermarks-remover	24k	—	~3.5k	Automated safety check: Pass	MIT	2 days ago
Install Anti Sloptrycompai/crm	11k	1 repos	~881	Automated safety check: Pass	MIT	27 days ago
Stop SlopXe/site	732	8 repos	~423	Automated safety check: Pass	MIT	2 days ago

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Humanizer
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Questions about Humanizer

What does Humanizer do?

Humanize AI-generated text by detecting and removing patterns typical of LLM output. Humanizer is an agent skill from brandonwise/humanizer. Humanize AI-generated text by detecting and removing patterns typical of LLM output.

When should I use Humanizer?

Humanizer fits situations like: asked to humanize text; make content sound more natural/human; review writing for AI patterns; score text for AI detection.

How do I install Humanizer in Claude Code?

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

How do I install Humanizer in Codex?

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

Can I use 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 brandonwise/humanizer --skill 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/humanizer, .gemini/skills/humanizer, .github/skills/humanizer and .opencode/skills/humanizer in your project.

What does Humanizer need to run?

Going by SKILL.md and its folder, Humanizer needs JavaScript for the scripts in its folder and the command-line tools its instructions call (node). Our summary lists: Node.js.

Does Humanizer access the network?

SKILL.md names 1 domain. As links in the text: en.wikipedia.org. This is read from the text; nothing was executed.

Is 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Humanizer use?

Humanizer is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Humanizer use?

About 2.2k tokens (SKILL.md is roughly 8.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5k tokens, read only when the agent opens those files.

What are the alternatives to Humanizer?

Skills that share tags, products or a category with Humanizer: Humanizer (Azure-Samples/interview-coach-agent-framework, 172 stars), Avoid AI Writing (conorbronsdon/avoid-ai-writing, 4.9k stars), User-Facing Text Cleanup (guillaumemeyer/watermarks-remover, 24k stars) and Install Anti Slop (trycompai/crm, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Humanizer?

brandonwise (a GitHub user) maintains it in brandonwise/humanizer, which has 127 GitHub stars. The repository was last updated on August 9, 2026.

Source: brandonwise/humanizer on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Humanizer

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Humanizer: remove AI writing patterns (v2.2)

Your task

Quick reference: the 28 patterns

Statistical signals

Vocabulary tiers

Core principles

Write like a human, not a press release

Add personality

Cut the fat

Before/after example

Using the analyzer

Always-on mode

Process

Files

Compare with similar skills

Similar skills

Humanizer

Avoid AI Writing

User-Facing Text Cleanup

Install Anti Slop

Stop Slop

Korean AI-Text Humanizer

Related

Questions about Humanizer