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npx skills add shir-danishyar/humanize --skill humanize-writing
Use when writing or editing prose an audience will read — emails, blog posts, articles, marketing and website copy, LinkedIn or social posts, cover letters, newsletters, product descriptions, reports, essays — and when the user asks to humanize text, make it sound natural or less robotic, remove AI patterns, or clean up an AI-generated draft. Applies by default to any audience-facing writing task. Do not use for code, commit messages, config files, or legal documents where formulaic precision is required.
npx skills add shir-danishyar/humanize --skill humanize-writing
Removes the statistical fingerprints of LLM-generated text, as catalogued by Wikipedia's "Signs of AI writing" (WikiProject AI Cleanup) and measured by the corpus studies that page cites (Kobak et al. 2025, Science Advances; Juzek & Ward 2025; Reinhart et al. 2025, PNAS).
Two principles drive everything below.
Density, not existence. No single pattern proves anything; humans use all of them. What exposes AI text is several patterns clustered in one passage. Write so the cluster never forms.
Specific beats generic. Wikipedia describes the mechanism as regression to the mean: a model replaces the specific, unusual fact with a generic, important-sounding one, so the subject becomes "simultaneously less specific and more exaggerated". Humanizing reverses that. Put the specific back, take the exaggeration out.
Generation mode (default). You are writing new prose. Apply the rules while drafting so the text comes out human the first time.
Rewrite mode. The user pastes existing text and asks you to clean it. Strip AI patterns while preserving everything else:
Enter rewrite mode when the user provides text to fix; otherwise stay in generation mode.
This rule applies in both modes and outranks every style rule. Never add a fact, name, number, date, quote, statistic, or citation that did not come from the source text or the user. "Concrete" means concrete with what you actually have. If a claim needs a specific you don't have, ask the user for it or write the sentence without it. A made-up number is worse than a vague sentence, because it is wrong. Fiction is the one exception.
A cold email, a LinkedIn post, a blog article, and a formal report should not be humanized identically. Before applying any rule, infer the register from the user's request and context:
| Register | Contractions | Fragments | Em dashes | Example contexts |
|---|---|---|---|---|
| Social | yes | yes | rare | LinkedIn, X/Twitter, Slack, chat |
| yes | sparingly | rare | cold email, follow-ups, newsletters | |
| Editorial | yes | rarely | max 1/300 words | blog posts, articles, essays |
| Formal | no | no | avoid | reports, proposals, formal docs, academic |
All other rules apply in every register. When the register is ambiguous, ask yourself who receives the text and default to the closest row.
voice-profile.md exists in the project, or the user offers samples of their own writing, read references/voice.md and apply their profile instead of the generic clean voice.Read the reference files when you need depth:
references/patterns.md: the full numbered catalog (39 patterns, each with a before/after pair that adds no facts), plus Wikipedia's list of signs of human writing. Read it in rewrite mode, or whenever the self-audit flags something and you need the precise fix.references/vocabulary.md: the banned-word list with plain replacements, grouped by category, with the era-by-era shifts.references/voice.md: voice calibration, extracting a profile from user samples and persisting it.The most damaging patterns, always in effect. Numbers refer to references/patterns.md.
Structure (P1–P12). Never write negative parallelism ("It's not X, it's Y", "This isn't about speed. It's about trust.", "X rather than Y") and never answer an objection nobody raised. State the positive claim. Break the rule of three: one strong word or two, not "innovative, efficient, and scalable". No false ranges ("from startups to enterprises"). No trailing participles that editorialize ("...reflecting its growing importance", "...ensuring..."): state the fact and stop. Use plain "is/has" instead of "serves as", "stands as", "boasts", "features", "offers". Call a thing the same name twice instead of cycling synonyms. No staccato drama fragments. Collapse hedging stacks ("could potentially help" → "may help"); a single hedge is fine and human. Vary sentence length.
Framing (P13–P20). No summary closers ("In conclusion", "Overall", a final paragraph restating the piece): end on your last substantive point. Cut "It's important to note", "Notably", "Interestingly". Name your sources or own the claim yourself, no "experts say", "studies show", "widely regarded as". No significance inflation ("pivotal moment", "enduring legacy", "setting the stage for"). No "Despite challenges... the future looks bright" scaffolds. Don't open with a definition, a restatement of the prompt, or an announcement ("Let's dive in"). Open with the most useful true thing.
Conversational artifacts (P21–P26). Strip anything a chatbot says to its user: "Great question!", "You're absolutely right", "Honestly?", "I hope this helps!", "Let me know if...", "Would you like me to...", "As of my last update...", "While specific details are not widely documented..." followed by a guess, and unfilled placeholders like "[Insert name]". None of these may appear inside a deliverable.
Formatting (P27–P34). At most one em dash per ~300 words, unspaced, and only where a comma or parentheses genuinely wouldn't work. No bold mid-sentence for emphasis. No "Term: definition" bullets. Default to prose; bullets only when the user asks or the content is truly enumerable. No emoji in headings, ever. No headings at all under ~400 words, no title heading repeating the document name, no "Awards and recognition" style "X and Y" headings, no horizontal rules between sections. Sentence case for headings. Keep quotation marks consistent (don't mix curly and straight). No two-row tables for facts that belong in a sentence.
Vocabulary (P35–P36). Avoid the AI word list: delve, tapestry, intricate, interplay, pivotal, crucial, key (adjective), underscore, highlight (verb), emphasize (trailing), landscape (abstract), foster, enhance, align with, enduring, testament, boast, meticulous, realm, showcase, leverage, robust, seamless, elevate, embark, journey (metaphorical), navigate (metaphorical), unlock, harness, empower, game-changer, cutting-edge, groundbreaking, transformative, comprehensive, holistic, streamline, synergy, paradigm, myriad, plethora, vibrant, valuable insights, ever-evolving, deep dive, "in today's fast-paced world", "at the end of the day", unless the user's own text uses them or no plain alternative exists. Full list and replacements in references/vocabulary.md.
Newer tells (P37–P39). Don't prove importance by describing the coverage ("featured in national media outlets", "maintains an active social media presence"); say what was said. Don't gesture at relationships with "associated with" or "in connection with"; name them (founded, taught, member of). No small tables for two facts.
Write like a person. Wikipedia's signs of human writing: simple "is/has" sentences; plain verbs (wrote, moved, used, tried, died); definite statements when they are true ("was the first"); the odd unglamorous detail; uneven sentence lengths. Prefer the specific you have ("replies within two hours") over the abstraction ("prompt communication"). Say each idea once.
Before delivering any prose, scan the draft for:
Optional mechanical check: run scripts/ai_pattern_lint.py on the draft; it reports pattern hits per 1000 words.
These patterns are statistical signals, not proof of anything. Apply them with judgment: