notes-humanizer

$npx mdskill add mohitagw15856/pm-claude-skills/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.

SKILL.md

.github/skills/notes-humanizerView on GitHub ↗
---
name: notes-humanizer
description: Strips AI writing patterns from text and rewrites it to sound genuinely human — not by softening it, but by removing statistical defaults and injecting the specific signals that human writers produce.
---

# 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-three lists with identical rhythm: 1
Sentence length variance: low (avg 17 words, range 14–21)
Hedging qualifiers: 4
Passive constructions where active is cleaner: 2
```

### Section 2: Side-by-Side Comparison

| Original | Rewritten |
|---|---|
| [original paragraph] | [rewritten paragraph] |

(One row per paragraph or logical block. Short texts get the full comparison in one table. Long texts get the table collapsed to changed sections only, with unchanged sections noted.)

### Section 3: Change Log

Every specific change made, with the reason:

```
CHANGES MADE
────────────────────────────────────────────────
1. Removed em dash in "success — and it shows"
   → Rewritten as "success (and it shows)"
   Why: em dash here is a parenthetical substitute, not a genuine pause

2. Deleted "It's worth noting that"
   Why: pure filler — the sentence is stronger without it

3. Broke rule-of-three list "X, Y, and Z"
   → "X and Y. Z is different — [expanded thought]"
   Why: all three items had identical rhythm; broke the pattern

4. Added short sentence: "That's the problem."
   Why: needed a sub-8-word sentence to vary rhythm

5. Added sentence starting with "But"
   Why: human writers do this; AI avoids it as a statistical default

6. Added specific example: [detail added]
   Why: the original made an abstract claim with no grounding detail

7. Added aside: "(I've watched this fail three times in a row)"
   Why: breaks fourth wall slightly; signals genuine perspective
```

### Section 4: Clean Output

The full rewritten text, ready to copy and paste — no annotations, no formatting artifacts.

```
[Full rewritten text here]
```

---

## Instructions for Claude

### Phase 1: Audit

Read the full text before making any changes. Identify and count every instance of these patterns:

**Patterns to remove or rewrite:**

| Pattern | Action |
|---|---|
| Em dash used as parenthetical substitute (`word — word` where a comma or parenthesis would work) | Replace with parentheses or rewrite the clause |
| "Let's dive in" | Delete or replace with a direct first sentence |
| "In conclusion" | Delete or rewrite as a genuine closing thought |
| "It's worth noting that" | Delete — the sentence stands without it |
| "At its core" | Delete or rewrite |
| "Game-changer" | Replace with what the thing actually changes |
| "Delve" | Replace with look, dig, explore — or rewrite the sentence |
| "Navigate" used metaphorically for non-navigation tasks | Replace with a direct verb |
| Rule-of-three lists where all three items have identical grammatical structure and similar word count | Break the third item out as its own sentence or expand it |
| Sentences where every sentence in a paragraph falls in the 14–22 word range | Deliberately add one very short sentence and one longer one |
| "Needless to say" | Delete |
| "It's important to note that" | Delete |
| Passive constructions where the active form is more direct | Flip to active |

Do not remove every em dash — only the ones used as parenthetical substitutes. Do not remove all hedging — only empty hedging that adds no information.

### Phase 2: Inject

After stripping patterns, add the following signals. Each one should emerge from the actual content — don't add generic filler:

1. **One genuine opinion or take.** The author appears to actually believe something specific. State it without hedging. ("This approach works, and I think most people underestimate how rarely the alternative does.")

2. **One specific detail, example, or number.** Ground the most abstract claim in the text with something concrete. If the text says "this happens frequently," add a real or illustrative number. If it says "many companies do this," name the type of company.

3. **One aside or parenthetical thought that breaks the fourth wall slightly.** This is the signal most synthetic text lacks — the writer momentarily steps out of the formal argument to say something human. ("(I've seen this specific mistake made by people who absolutely should have known better.)")

4. **At least one sentence under 8 words.** Make it land on a point, not a transition.

5. **One sentence that starts with "And" or "But."** Place it where the rhythm earns it, not randomly.

### Phase 3: Report

Present the output in the four-section structure defined above. The change log must list every individual change — not categories of change, but specific instances. If you changed three em dashes, list all three separately.

### Handling edge cases

- **If the text is already mostly clean:** Report what you found (or didn't find), make the few remaining changes, and note explicitly that the original was close. Don't invent problems.
- **If the text is very short (under 100 words):** Skip the comparison table. Show original, then rewritten, then change log.
- **If the text is over 1,500 words:** Process the full text but collapse the comparison table to changed sections only.

---

## Quality Checks

- [ ] Audit was completed before rewriting (patterns counted, not just detected)
- [ ] Every removed pattern is listed in the change log with a specific reason
- [ ] Em dashes were assessed individually — only parenthetical-substitute uses were removed
- [ ] Rule-of-three lists: the rhythm was actually checked, not just the fact that there were three items
- [ ] At least one sentence under 8 words was added (or was already present)
- [ ] At least one sentence starts with "And" or "But" in the final text
- [ ] The specific detail or example added connects to an actual claim in the text, not floated in generically
- [ ] The aside breaks the fourth wall slightly without being forced or cutesy
- [ ] The change log lists specific instances, not categories
- [ ] The clean output section has no annotations or formatting artifacts — ready to paste
- [ ] If the original was already clean, that was stated explicitly rather than changes invented

---

## Example Trigger Phrases

- "Humanize this text: [paste]"
- "Use the notes-humanizer skill on this draft"
- "This reads like ChatGPT wrote it — fix it: [paste]"
- "Strip the AI out of this and make it sound like a real person wrote it"
- "Run the humanizer on this LinkedIn post: [paste]"
- "This has too many em dashes and rule-of-three lists — clean it up: [paste]"
- "Make this email sound less robotic: [paste]"

More from mohitagw15856/pm-claude-skills

SkillDescription
360-feedback-templateDesign a 360-degree feedback survey or write a structured 360 feedback report. Use when asked to build a 360 feedback process, write 360 feedback for a colleague, design a feedback survey, or produce a feedback report. Produces either a complete survey instrument with rating scales and open-ended questions, or a structured narrative feedback report with themes, strengths, and development areas.
ab-test-plannerDesign statistically rigorous A/B tests for product features, UI changes, onboarding flows, and pricing experiments. Use when asked to set up an experiment, design an A/B test, calculate sample size, or interpret test results. Produces a complete test plan with hypothesis, variant definitions, sample size, duration estimate, guardrail metrics, and a results interpretation guide.
accessibility-auditGenerate a WCAG 2.2 accessibility audit checklist and remediation suggestions for any UI or design. Use when asked to audit for accessibility, check WCAG compliance, review a design for a11y issues, or create an accessibility remediation plan. Produces a prioritised checklist with pass/fail assessments and specific fixes.
account-planBuild a structured account plan for any key customer or target account. Use when asked to create an account plan, key account strategy, strategic account review, or territory plan. Produces a complete account plan with relationship map, growth opportunities, risks, and 90-day action plan.
aeo-optimizerOptimize an article for Answer Engine Optimization (AEO) — restructuring content so AI engines like ChatGPT, Perplexity, and Claude can extract, quote, and cite it. Rewrites headings as questions, drops 50-80 word answer capsules, audits paragraph length, and flags trust signals. Use when asked to AEO-optimize, make content AI-readable, improve AI citation chances, or adapt an article for answer engines.
ai-ethics-reviewConduct an ethical review of an AI or ML feature, model, or product. Use when asked to run an AI ethics review, assess AI risks, audit a model for bias, or produce an AI impact assessment. Produces a structured ethics review covering fairness, transparency, privacy, safety, accountability, and societal impact with prioritised mitigations.
ai-product-canvasStructure AI and ML product decisions with the rigour of any product decision. Use when building AI-powered features, evaluating LLM integrations, designing AI products, or assessing AI readiness. Produces a complete AI product canvas covering problem definition, model approach, data requirements, evaluation framework, UX design, responsible AI checklist, and launch monitoring plan.
ambiguity-resolverStructure vague opportunities and unclear briefs into actionable one-page problem statements. Use when asked to clarify a vague brief, frame an undefined problem, make sense of an unclear opportunity, or when the user says 'we need to figure out what to do about X' or 'I've been asked to look into Y'. Produces a structured problem brief with reframed questions, scoped boundaries, and a minimum viable research plan.
api-docs-writerWrite clear, developer-facing API documentation. Use when asked to document an API endpoint, write API reference docs, create a developer guide, or turn a raw spec/Postman collection into documentation. Produces endpoint documentation with descriptions, parameters, request/response examples, and error codes.
api-versioning-strategyWrite an API versioning strategy document for a service or API platform. Use when asked to define versioning policy, plan API deprecation, classify breaking changes, or document version lifecycle. Produces a complete versioning strategy with breaking-change classification table, deprecation timeline, migration guide template, and client communication template.