notes-humanizer
Strips AI writing patterns from text and rewrites it to sound genuinely human — removing the statistical defaults, then adding earned voice calibrated to genre (opinion pieces get a person's voice; docs and summaries stay neutral) without ever faking humanity. Use when a draft reads as AI-generated, over-polished, or rhythmically uniform — including blog posts, emails, LinkedIn posts, or any prose that needs to sound like a real person wrote it. Produces a pattern audit, side-by-side comparison, itemised change log, and clean rewritten output ready to paste.
npx skills add mohitagw15856/pm-claude-skills --skill notes-humanizer --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.
# Notes Humanizer "Humanize this" prompts don't work because they don't know what to remove. AI text has specific, identifiable defaults — em dashes used as parenthetical substitutes, rule-of-three lists where all items have identical rhythm, sentences that hover between 15 and 20 words. Fix those defaults, add the signals human writers actually produce, and the text stops reading as synthetic. This skill does that systematically, in two phases, and shows you exactly what changed and why. > Credit: Originally created by Orel (TheIndiepreneur) — adapted and extended for this library. --- ## Required Inputs | Input | Format | Notes | |---|---|---| | Text to humanize | Paste directly into the chat | Any length. Works on paragraphs, full articles, social posts, emails. | No other inputs required. Claude will not ask clarifying questions before starting — it works with what's given. --- ## Output Structure ### Section 1: What Was Found A plain-language audit of the AI patterns detected in the original text, before any rewriting: ``` PATTERNS DETECTED ───────────────── Em dashes used as parenthetical substitutes: 3 Filler openers ("Let's dive in", "It's worth noting", etc.): 2 Rule-of-th
- Required Inputs
- Output Structure
- Section 1: What Was Found
- Section 2: Side-by-Side Comparison
- Section 3: Change Log
- Section 4: Clean Output
- Instructions for Claude
- Phase 0: Calibrate to genre (do this first)
- Phase 1: Audit
- Phase 2: Inject (personal / persuasive genres only — see Phase 0)
- Phase 3: Report
- Handling edge cases
- Quality Checks
- Anti-Patterns
What does the notes-humanizer skill do?
Strips AI writing patterns from text and rewrites it to sound genuinely human — removing the statistical defaults, then adding earned voice calibrated to genre (opinion pieces get a person's voice; docs and summaries stay neutral) without ever faking humanity. Use when a draft reads as AI-generated, over-polished, or rhythmically uniform — including blog posts, emails, LinkedIn posts, or any prose that needs to sound like a real person wrote it. Produces a pattern audit, side-by-side comparison, itemised change log, and clean rewritten output ready to paste.
How do I install it?
Run `npx skills add mohitagw15856/pm-claude-skills --skill notes-humanizer --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 mohitagw15856/pm-claude-skills, a repository with 1,255 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.