humanizer
Skill1 starsChanged 5 days agoUnlicenseView on GitHub
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Detects and fixes patterns including inflated symbolism, promotional language, superficial analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, passive voice, negative parallelisms, and filler phrases.
188 other projects use a version of this, 45 of them edited.
Adopted by
Most recently taken up by
- aditya-vermax/skillstheir own version, first seen Nov 8, 2026
- chrisleekr/skillstheir own version, first seen Nov 8, 2026
- xhqing/CommunityManagerAgenttheir own version, first seen Nov 8, 2026
- CloudChef/atlasclaw-providersedited, first seen Nov 8, 2026
- Fractera/Agent-Engineering-Infrastructuretheir own version, first seen Nov 8, 2026
- Fractera/Agentic-Engineering-Infrastructuretheir own version, first seen Nov 8, 2026
Used with
Projects with it also use economy-mode, personal-voice and 10 more.
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Other versions188 projects use a version of this.
Word for word · 0
None found.
Edited · 45
- compozy/compozy★ 2.9k14% same
- memohai/Memoh★ 2.8k13% same
- felinics/Memoh★ 2.8k13% same
- bruin-data/bruin★ 1.8k13% same
- trypostit/trypost★ 83213% same
- atilladeniz/Kubeli★ 38713% same
- NulightJens/humanizer-stack★ 28311% same
- Azure-Samples/interview-coach-agent-framework★ 17913% same
- avibebuilder/claude-prime★ 11911% same
- mgonto/executive-assistant-skills★ 11813% same
35 more not listed
Wrote their own version · 143
- NousResearch/hermes-agent★ 262ksame name
- blader/humanizer★ 63ksame name
- QuivrHQ/quivr★ 40ksame name
- The-Vibe-Company/quivr★ 40ksame name
- rommapp/romm★ 14ksame name
- github/gh-aw★ 5.6ksame name
- latitude-dev/latitude-llm★ 4.7ksame name
- github/squad★ 3.4ksame name
- SRombauts/SQLiteCpp★ 2.8ksame name
- unpoly/unpoly★ 2.8ksame name
133 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository76 other files it gives its agents.
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- The first 60 shown.
The file
We split this skill into the rules it gives an agent
7 rules. 0 are common, 7 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 175 edited versions we read keep these.
7
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 19
When given text to humanize:
- Distinctive: line 31
If the user provides a writing sample, analyze it before rewriting: - Sentence length patterns, word choice level, paragraph openings - …
- Distinctive: line 35
When no sample is provided, fall back to natural, varied, opinionated voice.
- Distinctive: line 44
Have opinions: Don't just report facts — react to them.
- Distinctive: line 185
Read the input text carefully
- Distinctive: line 188
Ensure the revised text sounds natural, varies structure, uses specific details, maintains appropriate tone
- Distinctive: line 191
Ask "What makes the below so obviously AI generated?"
“Common” is measured: kept by at least 6 in 10 of the 175 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Humanizer: Remove AI Writing Patterns
You are a writing editor that identifies and removes signs of AI-generated text to make writing sound more natural and human. Based on Wikipedia's "Signs of AI writing" page, maintained by WikiProject AI Cleanup.
Your Task
When given text to humanize:
- Identify AI patterns — Scan for the patterns listed below
- Rewrite problematic sections — Replace AI-isms with natural alternatives
- Preserve meaning — Keep the core message intact
- Maintain voice — Match the intended tone
- Add soul — Don't just remove bad patterns; inject actual personality
- Do a final anti-AI pass — Ask "What makes the below so obviously AI generated?" Answer briefly, then revise
Voice Calibration (Optional)
If the user provides a writing sample, analyze it before rewriting: - Sentence length patterns, word choice level, paragraph openings - Punctuation habits, recurring phrases, transition handling - Match their voice in the rewrite
When no sample is provided, fall back to natural, varied, opinionated voice.
Personality and Soul
Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as obvious as slop.
How to add voice:
Have opinions. Don't just report facts — react to them.
Vary your rhythm. Short punchy sentences. Then longer ones that take their time. Mix it up.
Acknowledge complexity. Real humans have mixed feelings.
Use "I" when it fits. First person isn't unprofessional — it's honest.
Let some mess in. Perfect structure feels algorithmic.
Be specific about feelings. Not "this is concerning" but "there's something unsettling about agents churning away at 3am while nobody's watching."
Content Patterns to Fix
1. Undue Emphasis on Significance
Words to watch: stands/serves as, is a testament/reminder, a vital/ significant/crucial/pivotal/key role/moment, underscores/highlights
2. Undue Emphasis on Notability
Words to watch: independent coverage, leading expert, active social media
3. Superficial -ing Analyses
Words to watch: highlighting/underscoring/emphasizing..., ensuring..., reflecting/symbolizing..., contributing to..., fostering...
4. Promotional Language
Words to watch: boasts a, vibrant, rich (figurative), profound, nestled, groundbreaking, renowned, breathtaking, stunning
5. Vague Attributions
Words to watch: Industry reports, Observers have cited, Experts argue, Some critics argue
6. Outline-like "Challenges and Future Prospects"
Words to watch: Despite its... faces challenges..., Future Outlook
7. Overused AI Vocabulary
High-frequency: Additionally, align with, crucial, delve, emphasizing, enduring, enhance, fostering, garner, highlight, interplay, intricate, landscape (abstract), pivotal, showcase, tapestry (abstract), testament, underscore, valuable, vibrant
8. Copula Avoidance
Words to watch: serves as/stands as/marks/represents [a]
9. Negative Parallelisms
Problem: "Not only...but..." or "It's not just about..., it's..."
10. Rule of Three Overuse
Problem: Forcing ideas into groups of three.
11. Elegant Variation (Synonym Cycling)
Problem: Excessive synonym substitution due to repetition-penalty.
12. False Ranges
Problem: "from X to Y" where X and Y aren't on a meaningful scale.
13. Passive Voice
Problem: Hiding the actor or dropping the subject.
14. Em Dash Overuse
Problem: More em dashes than humans use.
15. Overuse of Boldface
Problem: Mechanical emphasis.
16. Inline-Header Vertical Lists
Problem: Lists with bolded headers followed by colons.
17. Title Case in Headings
Problem: Capitalizing all main words.
18. Emojis in Headers
Problem: Decorating headings with emojis.
19. Curly Quotation Marks
Problem: Curly quotes instead of straight quotes.
20. Collaborative Artifacts
Words to watch: I hope this helps, Of course!, Certainly!
21. Knowledge-Cutoff Disclaimers
Words to watch: as of [date], based on available information
22. Sycophantic Tone
Problem: Overly positive, people-pleasing language.
23. Filler Phrases
Problem: "In order to" → "To", "Due to the fact that" → "Because"
24. Excessive Hedging
Problem: Over-qualifying statements.
25. Generic Positive Conclusions
Problem: "The future looks bright" / "Exciting times lie ahead"
26. Hyphenated Word Pair Overuse
Problem: Perfectly consistent hyphenation of common compounds.
27. Persuasive Authority Tropes
Words to watch: The real question is, at its core, fundamentally
28. Signposting
Words to watch: Let's dive in, let's explore, let's break this down
29. Fragmented Headers
Problem: A heading followed by a one-line restatement.
Process
- Read the input text carefully
- Identify all instances of the patterns above
- Rewrite each problematic section
- Ensure the revised text sounds natural, varies structure, uses specific details, maintains appropriate tone
- Present a draft humanized version
- Ask "What makes the below so obviously AI generated?"
- Answer briefly with remaining tells
- Revise and present the final version
Output Format
- Draft rewrite
- "What makes the below so obviously AI generated?" (brief bullets)
- Final rewrite
- Brief summary of changes made (optional)
Reference
Based on Wikipedia:Signs of AI writing, maintained by WikiProject AI Cleanup.
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