humanize
Use whenever the user asks to "humanize", "make this sound more human", "rewrite to avoid AI detection", "make this less AI-sounding", "add a human voice", or "write like a person". Also use when the user pastes text and asks why it reads as robotic, generic, flat, or AI-like, or when generating new text in a register where AI tells (em dashes, semicolons, hedges, banned vocabulary like "delve", "leverage", "robust") would damage credibility.
npx skills add harshaneel/humanize --skill humanize --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Humanize Text Skill Transforms AI-generated or flat text into output that mirrors the statistical and stylistic fingerprint of human writing. Grounded in the published detection literature; sources live in `references/research.md` (background only, not needed during a rewrite). --- ## Hard rules (read first, enforce last) These seven fail more often than everything else combined, because the model that wrote the draft is the model checking it. You systematically overproduce these patterns; your draft contains em dashes even when you don't remember writing them. Treat "my draft is probably clean" as false by default. 1. **Em dashes:** at most one per 300 words of output. Under 300 words, zero. 2. **Semicolons:** none, unless a list item itself contains commas or the register is explicitly formal/academic (Lever 8). 3. **Straight quotes and apostrophes only.** Never curly. Sole exception: publishing contexts where typographic quotes are house style (Lever 8). 4. **Banned vocabulary** (full list at end of this skill). Highest-frequency offenders: delve, leverage, utilize, robust, comprehensive, streamline, furthermore, moreover, "it is important to note". 5. **No negation framing:**
- Hard rules (read first, enforce last)
- Mental model: what detectors actually measure
- Nine humanization levers, apply all of them
- Lever 1: Perplexity injection (word-level)
- Lever 2: Burstiness injection (sentence-level)
- Lever 3: Hedge surgery
- Lever 4: Structural flattening
- Lever 5: Specificity insertion
- Lever 6: Voice and register
- Lever 7: Discourse coherence (non-AI transitions)
- Lever 8: Punctuation normalization
- Lever 9: Strip RLHF / instruction-tuning voice
- Advanced techniques (optional, when stakes are high)
- Rewrite protocol
What does the humanize skill do?
Use whenever the user asks to "humanize", "make this sound more human", "rewrite to avoid AI detection", "make this less AI-sounding", "add a human voice", or "write like a person". Also use when the user pastes text and asks why it reads as robotic, generic, flat, or AI-like, or when generating new text in a register where AI tells (em dashes, semicolons, hedges, banned vocabulary like "delve", "leverage", "robust") would damage credibility.
How do I install it?
Run `npx skills add harshaneel/humanize --skill humanize --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From harshaneel/humanize, a repository with 330 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.