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drinkspillerdrinkspiller/skills/humanizer/SKILL.md

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.

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Projects with it also use economy-mode, personal-voice and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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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
  1. Distinctive:

    When given text to humanize:

    line 19
  2. Distinctive:

    If the user provides a writing sample, analyze it before rewriting: - Sentence length patterns, word choice level, paragraph openings - …

    line 31
  3. Distinctive:

    When no sample is provided, fall back to natural, varied, opinionated voice.

    line 35
  4. Distinctive:

    Have opinions: Don't just report facts — react to them.

    line 44
  5. Distinctive:

    Read the input text carefully

    line 185
  6. Distinctive:

    Ensure the revised text sounds natural, varies structure, uses specific details, maintains appropriate tone

    line 188
  7. Distinctive:

    Ask "What makes the below so obviously AI generated?"

    line 191

“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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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:

  1. Identify AI patterns — Scan for the patterns listed below
  2. Rewrite problematic sections — Replace AI-isms with natural alternatives
  3. Preserve meaning — Keep the core message intact
  4. Maintain voice — Match the intended tone
  5. Add soul — Don't just remove bad patterns; inject actual personality
  6. 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

  1. Read the input text carefully
  2. Identify all instances of the patterns above
  3. Rewrite each problematic section
  4. Ensure the revised text sounds natural, varies structure, uses specific details, maintains appropriate tone
  5. Present a draft humanized version
  6. Ask "What makes the below so obviously AI generated?"
  7. Answer briefly with remaining tells
  8. Revise and present the final version

Output Format

  1. Draft rewrite
  2. "What makes the below so obviously AI generated?" (brief bullets)
  3. Final rewrite
  4. Brief summary of changes made (optional)

Reference

Based on Wikipedia:Signs of AI writing, maintained by WikiProject AI Cleanup.

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