humanizer
Agent skill that removes signs of AI-generated writing from text
Install / Use
npx skills add blader/humanizerInstalls into whichever agent you are using.
CLAUDE.md
Claude Code project instructions
Quality Score
Category
AI & Machine LearningSupported Platforms
Tags
Our assessment of humanizer
humanizer scores 97/100 on our quality scale, 55th of 963 AI & Machine Learning skills we index (top 6%).
Its CLAUDE.md is 16 KB long, well organised into 15 sections with 6 code examples: a thorough specification that gives an agent plenty to work with.
With 65,319 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 9 days ago, so humanizer is actively maintained.
- Our last check on 2026-10-17 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 95/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
humanizer compared with similar skills
All 4 of these similar skills score higher than humanizer; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| humanizer (this skill)by blader | 97 | 65.3k | 9d ago | CLAUDE.md |
| claude-memby thedotmack | 100 | 113.6k | today | CLAUDE.md |
| taste-skillby Leonxlnx | 100 | 110.8k | 1d ago | CLAUDE.md |
| Agent-Reachby Panniantong | 100 | 109.3k | today | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 91.0k | 11d ago | CLAUDE.md |
Frequently asked questions
- How do I install humanizer?
- Run
npx skills add blader/humanizer. The install tabs above show the steps for each supported agent. - Which AI agents does humanizer work with?
- It is written for Claude Code, Cursor and OpenAI Codex, as a CLAUDE.md file. Other agents that read the same format can often use it too.
- Is humanizer safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 95/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is humanizer still maintained?
- The repository was last updated 9 days ago, so humanizer is actively maintained.
Skill content
View source on GitHubHumanizer
Humanizer rewrites AI-sounding text so it reads like a person wrote it, without changing what it says. Because it is just Markdown, it works with any agent that supports skills.
Installation
Install Humanizer with the Skills CLI:
npx skills add blader/humanizer --global
Leave off --global to install Humanizer only in the current project. Add --agent <name> or --agent '*' to choose which agents receive it, then reload their skills. The skill answers to /humanizer.
Claude Code 2.1.142 or newer can install the plugin instead:
/plugin marketplace add blader/humanizer
/plugin install humanizer@humanizer
The plugin answers to /humanizer:humanizer.
In Claude Desktop, download this repository as a ZIP and upload it as a skill. For a manual install, copy SKILL.md into the agent's skill folder.
Usage
Call the skill directly:
/humanizer
[paste your text here]
Or ask in plain language:
Please humanize this text: [your text]
To rewrite a file, give Humanizer its path:
Humanize the prose in docs/launch-post.md
Match your voice
If you want the rewrite to sound more like you, include a sample:
/humanizer
Here's a sample of my writing for voice matching:
[paste 2-3 paragraphs of your own writing]
Now humanize this text:
[paste AI text to humanize]
Humanizer follows the sample's rhythm, word choice, punctuation, and deliberate quirks, including dashes if you use them.
How it works
A language model writes whatever is most likely to come next, so by default it makes the choice that fits the widest range of readers and subjects. A person chooses for one reader and one subject. Every tell Humanizer looks for is a form of that default choice: a sentence that signals importance instead of adding a fact, rhythm or formatting applied by rule, an ordinary fact dressed as a pivotal one, or text left over from the chat.
"LLMs use statistical algorithms to guess what should come next. The result tends toward the most statistically likely result that applies to the widest variety of cases." Wikipedia, "Signs of AI writing"
Humanizer marks every tell it finds, strongest first. It drafts a rewrite without treating the original structure as fixed, checks the draft against the patterns and the original claims, and then writes the final version. It does not make things up. A name, number, date, quote, citation, or other factual detail must come from the source or the writer, and if a sentence needs a detail that is missing, Humanizer asks instead of inventing one.
When you paste text, Humanizer shows its work: the first rewrite, a short critique of anything that still sounds artificial, and the final version. Point it at a file and it changes only the prose, leaving code, data, frontmatter, and link targets alone. Personal writing keeps the writer's opinions and quirks. Technical and reference prose stays neutral and plain.
The 25 patterns
The patterns are numbered by strength and frequency. The first five justify an edit on a single sighting. Patterns marked weak alone count only when several tells share a passage, because a careful writer may use any one of them on purpose.
A. Staging instead of stating
| # | Pattern | Before | After | |---|---------|--------|-------| | 1 | Not X but Y | "It's not just X, it's Y", "This doesn't mean X. It means Y." | State the point directly | | 2 | One-line closers and dramatic fragments | "That is the real win." after every section; "No prior. No nostalgia." | Cut the closer that repeats; merge fragments into a specific claim | | 3 | Sayings that sound deep | "At its core, what matters is...", "Symmetry is the language of trust" | Replace the saying with the specific claim | | 4 | Staged run-up before the point | "Let's dive in", "Honestly? It depends..." | Remove the run-up and state the point | | 5 | Arguing with no one | "This isn't mainly about...", "A tempting approach would be..." | Remove the unraised objection or fake option; keep any real claim |
B. Rhythm by rule
| # | Pattern | Before | After | |---|---------|--------|-------| | 6 | Forced triads | "innovation, inspiration, and insights"; three examples plus a lesson | Use the number of items the meaning needs | | 7 | Repeated sentence openings | "She noted... She noted... She filed..." | Merge the sentences or change the subject | | 8 | Dashes as the universal connector (weak alone) | "institutions—not the people—yet this continues—" | Use periods, commas, colons, or parentheses; match a sample that uses dashes | | 9 | Stacked qualifiers (weak alone) | "could potentially possibly be argued" | Keep only qualifiers the source supports | | 10 | Hyphenated pairs everywhere (weak alone) | "the team is cross-functional" | Keep only the hyphens grammar needs | | 11 | Passive voice and missing subjects (weak alone) | "No configuration file needed" | Name the actor when that helps |
C. Inflation and borrowed authority
| # | Pattern | Before | After | |---|---------|--------|-------| | 12 | Overused AI words | "delve... testament... landscape... showcasing" | Use plain words; the list in SKILL.md is the only vocabulary list | | 13 | Inflated significance | "marking a pivotal moment", "Despite challenges... continues to thrive", "The future looks bright" | Keep the fact and drop the significance; end on the last concrete fact | | 14 | Vague connection or association | "associated with the leadership of", "in connection with" | State the relationship the source gives | | 15 | Shallow -ing riders | "symbolizing... reflecting... showcasing..." | Keep only what the source supports | | 16 | Sales language | "nestled within the breathtaking region" | State what the thing is | | 17 | Borrowed authority | "Experts believe...", "cited in NYT, BBC, FT, and The Hindu" | Name a real source and what it said, or remove the claim or list | | 18 | Avoiding is, are, and has | "serves as... features... boasts" | "is... has" |
D. Formatting by rule
| # | Pattern | Before | After |
|---|---------|--------|-------|
| 19 | Bold as decoration | "OKRs, KPIs"; "Performance: Performance improved" | Remove the bold; turn a labeled list into prose |
| 20 | Decorative headings | "Strategic Negotiations And Partnerships", "🚀 Launch Phase:" | Sentence case; remove emojis and arrows |
| 21 | Curly quotation marks (weak alone) | said “the project” | said "the project" |
E. Leftovers from the chat and the draft
| # | Pattern | Before | After | |---|---------|--------|-------| | 22 | Chatbot residue | "Great question! ... I hope this helps!" | Remove the wrapper and keep the content | | 23 | Knowledge-limit disclaimers and guesses | "While details are limited in available sources, it appears..." | State what the source shows, or remove the sentence | | 24 | A heading repeated in the first sentence | "## Performance" + "Speed matters." | Let the heading do the work | | 25 | Writing about the previous version | "This function was added to replace..." | Describe what it does now |
Full example
The writer supplied these notes with the draft, so the rewrite can use them: the trip was last October, the hotel was in Alfama, the custard tart was at a small place in Graça, the tram ride took about forty minutes. Without notes like these, Humanizer asks instead of inventing.
Before (AI-sounding):
I recently spent five unforgettable days in Lisbon, and let me tell you — this city completely stole my heart. From the moment I arrived, I knew I was somewhere truly special.
Nestled along the banks of the Tagus River, Lisbon stands as a vibrant testament to Portugal's enduring spirit, where rich history and modern energy intertwine at every turn. Yes, the famous hills are challenging — my legs certainly felt it! — but every climb rewards you with breathtaking, panoramic views that make it all worthwhile.
No trip would be complete without riding the iconic Tram 28, winding through the city's most historic neighborhoods. And the food? Simply divine. The original pastéis de nata at Pastéis de Belém are a beloved national treasure, and savoring one still warm was a moment I will never forget.
But what truly makes Lisbon special isn't just the sights — it's the feeling. Wander a few steps off the main squares and you'll discover a quieter, more authentic side: sun-drenched alleys, charming tiled facades, and friendly locals going about their daily lives, inviting you to slow down and savor every moment.
Of course, the must-see São Jorge Castle offers stunning views over the rooftops below. The queues can be long, but the experience is absolutely worth it for any history buff or curious traveler.
Would I go back? Absolutely. Lisbon isn't just a place to visit — it's a place to fall in love with, again and again. If you're dreaming of your next getaway, this is one destination that promises memories to last a lifetime. ✨
After:
I spent five days in Lisbon last October and still have mixed feelings about it. Beautiful, yes. Also harder on the knees than anyone warned me.
The hills are the whole story and somehow never make the brochures. My hotel was up in Alfama, which photographs beautifully and translates, in practice, to climbing what felt like a six-story staircase every time I wanted coffee. By the second day my calves had opinions. I started planning each walk around which way was downhill, which is a strange way to see a city but probably an honest one.
Everyone says to ride Tram 28, so I did, wedged against a stranger's backpack for forty minutes while three tour groups filmed the same corner. I would walk the route next time, or go before breakfast. The custard tarts, though, earn the fuss. I had one at a plain little place in Graça, still warm, and for about thirty seconds I understood why people build trips around pastry.
What I did not expect was how quiet the city gets away from the main squares. Two blocks uphill from any plaza it turns into laundry lines, chipped tile, open windows, and old men watching football with the sound turned up. That is the Lisbon I keep thinking about, not the castle.
The castle is fine. The view is great, the queue is long, and I spent more time shuffling toward the entrance than looking at anything once I got inside. If I had only two days, I would trade it for an afternoon of getting lost.
I would go back, but in spring and with better shoes. Lisbon does not bend over backward to make things easy for you. I think I liked that, even when my legs disagreed.
Sources
- Wikipedia: Signs of AI writing is the source for the pattern list.
- WikiProject AI Cleanup maintains the page.
Version history
<details> <summary>Show release notes</summary>- 3.0.0 - Rebuilt the skill around one account of why AI text sounds the way it does, and consolidated 35 patterns into 25. Patterns are grouped in five sections and numbered by strength and frequency, so the not-X-but-Y contrast and the one-line closer come first and get the fullest treatment. Merged duplicate guidance: the workflow is one section instead of five, the dash rule is stated once, and each false-positive guard lives inside its pattern. Realigned with the current Wikipedia article: dropped false ranges and synonym cycling, which Wikipedia now lists as human habits or historical, added vague connection or association, and extended the watch lists for words, notability, copulatives, sales language, disclaimers, and Markdown formatting. Reordere
Truncated for display — read the full file on GitHub.
Related Skills
claude-mem
113.6kPersistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More
taste-skill
110.8kAgent skills that give coding agents taste: art direction, reference images and a browser check instead of generic AI pages
Agent-Reach
109.3kGive your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
Understand-Anything
91.0kGraphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
