Install
openclaw skills install @dennisrongo/humanizerRewrite text so it does not read like an LLM wrote it. Strips AI-writing patterns (significance inflation, "delve"/"tapestry" vocabulary, rule-of-three lists, em-dash sales rhythm, sycophancy, hedge filler, tidy cadence) without inventing facts or putting a narrator into engineering prose. Use this skill whenever the user says "humanize", "de-AI", "de-slop", "un-ChatGPT", "review this for AI tells", or asks to make a draft sound less like ChatGPT — even if they never say "humanizer". Do not use it to derive a voice profile (that is creator-voice-profile) and do not apply it to your own output unless the user asked for a humanize pass.
openclaw skills install @dennisrongo/humanizerStrip AI-writing tells so the text sounds like a person wrote it. Preserve every fact. Match the genre: engineering prose stays plain; essays may have a voice.
Wikipedia's "Signs of AI writing" is a detection field guide, not a style manual. Isolated tells are not evidence. Clusters are.
Do not auto-trigger when:
creator-voice-profilePick one. The loop is the same; the delivery is not.
| Mode | When | Deliver |
|---|---|---|
| Review-only | "review for AI tells", "is this slop" | List hits (pattern N: quote). Do not rewrite until asked. Zero findings is valid. |
| Embedded | "just fix it", a short paragraph, or another skill asked for prose | Final text only. No draft, no audit, no ceremony. |
| File | user points at a file | Read it. Rewrite in place (prose only: leave code, frontmatter, data, link targets). Report a short summary of what changed. |
| Longform pasted | user pastes a long essay/post | Draft → audit bullets → final rewrite. |
Repo-wide sweep ("de-slop the docs"): find candidate files, grep tell words from references/word-tiers.md, then File mode one file at a time.
Name the genre in one line before touching the text.
Never invent facts. The rewrite must not contain any fact, name, number, date, quote, or citation that is not in the source text or the user's message. Opinions and reactions are voice, not facts — and only in essay register. If a sentence needs a specific to work and the source does not have one, write the plain version or leave a [placeholder]. A fabricated specific is a worse tell than a flat one.
Do not sprinkle "human markers." Do not insert contractions, $43, named people, And/But openers, "honestly," complaints, or questions in order to seem human. That is a formula. Formulas are the problem.
Clusters, not isolated words. A tell is reportable only when it clusters with others, or it is a high-confidence wrapper (chatbot leftover, cutoff disclaimer, emoji-header list). See references/patterns.md § What not to flag.
Rhythm is conditional. If the draft is uniformly mid-length, vary it. Do not force a ≤6-word sentence or a 25-word sentence into a short artifact. Do not drop Oxford commas on purpose. End on the last concrete point; cut uplift closers.
Before each step, restate in one line: genre, mode, "no new facts."
Only when the user provides a sample of their writing in this turn (inline or a file path). Read the sample first. Note sentence length, word-choice level, paragraph openings, punctuation (including em-dash frequency), recurring phrases, and transitions. Match those habits. Do not upgrade "stuff" to "elements." The sample outranks the em-dash rule and Personality.
No sample → do not invent a persona. Use the genre gate default.
Do not derive a voice profile from videos or transcripts. Hand that to creator-voice-profile.
Skip this section for engineering / reference.
Sterile, voiceless essay prose is its own tell. When the content and the author's voice call for it: have opinions, allow mixed feelings, vary rhythm, use "I" if the author already would. Do not add factual claims to create personality. Do not add fragments for showmanship (pattern 31).
Source: The experiment produced 3 million lines of code. Some developers were impressed while others were skeptical.
❌ Invented scene to add soul:
3 million lines of code, generated while the humans presumably slept.
✅ Essay — stance on facts that are already there:
I don't know how to feel about 3 million lines of code. Some developers were impressed; others were skeptical.
✅ Engineering — slop stripped, no narrator:
The experiment produced 3 million lines of code. Some developers were impressed; others were skeptical.
Source (AI-sounding): chatbot wrapper + significance inflation + "serves as" / "testament" / em dashes + "it's not just about" + vague "industry observers" + NYT/Wired/The Verge named in the source + emoji list (speed / quality / adoption) + cutoff hedge + "the future looks bright."
❌ Illegal draft — slop is gone, but facts were invented:
In a 2024 Google study, Codex users finished simple functions 55% faster. Mira, an engineer I interviewed, reviews every Copilot line.
✅ Legal rewrite — only claims that were in the source:
AI coding assistants are used for documentation, tests, and refactors, and for autocomplete. Coverage in The New York Times, Wired, and The Verge is often cited. Adoption is described as moving from hobby experiments to company-wide rollouts.
The usual pitch is speed, quality, and wider use. The recurring problems named alongside that pitch are hallucinations, bias, and accountability. Suggestion-acceptance is not the same as a correct or useful change.
User: "Review this README for AI tells. Don't rewrite yet."
Claude: reads the file → lists pattern 1: "marking a pivotal moment…" and pattern 18: emoji headers → stops. Zero extra commentary, no rewrite.
User: "Humanize this PR description."
Claude: names genre engineering → embedded mode → strips "serves as a testament" / rule-of-three / uplift closer → returns plain prose, no first person, no invented ticket numbers.
User: "Humanize draft.md. Match the voice in notes/voice-sample.md."
Claude: reads the sample first → File mode on draft.md → matches the sample's sentence length and dash habit → writes the file → reports what changed. Does not invent names to add texture.
[placeholder].a high-quality report. ✅ Keep attributive hyphens; drop them only after the noun (the report is high quality). See pattern 26.framework in a design doc as a finding. ✅ Clusters, or high-confidence wrappers. Zero findings is valid.creator-voice-profile, or ask for a sample.