---
id: EliasOulkadi/shokunin/humanize
version: "25d1ed02"
license: MIT
install: manual
updated: 2026-07-27
---

# humanize — humanize transforms machine-generated content into natural-sounding text by identifying and eliminating 16 common AI patterns—from overused buzzwords and mechanical connectors to uniform paragraph structure and excessive passive voice. The skill applies a structured workflow to detect, prune, vary, and personalize text, then verifies results against AI detectors and conversational authenticity.

Publisher: EliasOulkadi · Stars: 110 · Updated: 2026-07-27

Install (manual): `git clone https://github.com/EliasOulkadi/shokunin`

## SKILL.md

# humanize · 人間

**人間 · にんげん** — "human being". Makes AI-generated text sound like a real person wrote it.

Based on research from: Grammarly, MIT Technology Review, GPTZero, QuillBot, Reddit (r/auscorp, r/cybersecurity), Hacker News, Stack Overflow, JustDone, print-css.rocks, BrowserStack, pdf4.dev benchmarks, and professional writing guides (2024–2026).

---

## Core metrics AI detectors measure

| Metric | What it means | Human text | AI text |
|--------|---------------|------------|---------|
| **Perplexity** | How predictable each word is | High — uses unexpected words | Low — always picks the most probable word |
| **Burstiness** | Variance in sentence length | High — mixes short/long sentences | Low — uniform sentence length |
| **Word frequency** | Rate of common vs rare words | Balanced — uses uncommon terms | Skewed — overuses "the", "it", "is" |
| **Repetition** | Recurring patterns | Low — natural variation | High — same structures repeat |

Sources: GPTZero, QuillBot, MIT Technology Review, Google Brain research (Ippolito et al. 2020)

---

## The 16 AI tells (how to spot them)

### 1. Overused buzzwords (Grammarly 2026, Reddit)

| AI word | Human alternative |
|------------|-------------------|
| delve into | analyze, explore, dig into |
| pivotal | key, decisive, critical |
| underscore | highlight, point out, stress |
| multifaceted | complex, with several aspects |
| landscape | ecosystem, context, situation |
| paradigm | model, approach, framework |
| robust | solid, reliable, resilient |
| leverage | use, harness, take advantage of |
| seamless | smooth, frictionless, natural |
| transformative | disruptive, profound, radical |

### 2. Mechanical connectors (GPTZero research)

- "Moreover", "Furthermore", "Nevertheless", "Consequently" → use "Also", "But", "So" or nothing
- "However" every 3 paragraphs → cut half, let it flow
- "Nevertheless", "Therefore", "Consequently" → replace with "So", "Then", "That means"

### 3. Perfect symmetrical structure (MIT Tech Review)

LLMs generate paragraphs of the same length, same structure: intro → point → example → conclusion.

**Fix:** Break the pattern. One-line paragraph. Then a long one. List. Then another short one.

### 4. Low burstiness (QuillBot, pdf4.dev)

AI produces sentences of similar length. Humans alternate:
- Short sentence. Impact.
- Then a longer one that develops the idea with more detail and nuance, adding context.
- Another short one.

### 5. Absolute neutrality (r/auscorp, Reddit)

AI never takes a position. Sounds like a wiki.
**Fix:** Add opinion, judgment, acknowledged bias. "We don't like this", "This is well done", "This is debatable".

### 6. Forced transitions (HN, cybersecurity forums)

"It is important to note that...", "It is worth mentioning that...", "It should be noted that..." → delete all. If the sentence doesn't work without the crutch, rewrite it.

### 7. Numbers and statistics without source

AI invents data that "sounds good". E.g.: "Studies show that 80% of users..."
**Fix:** If there's no real source, don't put a number. Use "many", "most", "it's common".

### 8. Excessive passive voice

"It was carried out", "It has been determined", "It can be observed"
**Fix:** Active. "We carried out", "We determined", "We observe"

### 9. Empty hyperbole (r/cybersecurity)

"Critical", "Massive", "Transformative", "Revolutionary" without backup.
**Fix:** Concrete data or measured language.

### 10. Closing with rhetorical question

"Are you ready for the future?", "Can you imagine a world where...?"
**Fix:** Close with a statement or direct call to action.

### 11. Uniform paragraph length

AI: all paragraphs 3-5 lines.
Human: natural mix of 1 line with 8 lines.

### 12. Lack of colloquialisms

AI doesn't use "well", "look", "you see", "the thing is", "let's see". Real speech has filler words.
**Fix:** Add controlled natural language. Don't overdo it, but loosen up.

### 13. Too formal for the context

An internal report written like an academic paper. An email like a formal letter.
**Fix:** Match the register to the channel and audience.

### 14. No errors or imperfections

AI has no typos, doesn't repeat a word by accident, doesn't rephrase.
**Fix:** Do NOT introduce artificial errors. But allow natural asymmetry.

### 15. No contractions or contracted forms

AI: "do not", "cannot", "will not", "it is", "I am", "they are"
Human: "don't", "can't", "won't", "it's", "I'm", "they're" (in English)

### 16. Em dash (—) as universal connector

AI abuses the em dash `—` as a universal connector. Typical pattern:

```
❌ AI:   Black Box — no previous credentials
❌ AI:   WordPress — updated to latest version
❌ AI:   Admin panel — accessible without restrictions
```

A human normally uses:

```
✅ Real: Black Box (no previous credentials)
✅ Real: WordPress updated to latest version
✅ Real: Admin panel accessible without restrictions
```

The real em dash is used for asides or tone shifts, not as glue between label and value. If you see multiple lines with `—` in a row, it's AI.

**Fix:** replace `—` with parentheses, comma, colon, or simply nothing. If the `—` separates a label from its value, the label or the dash is probably unnecessary.

---

## Workflow

### Step 1: Detect

Read the full text. Mark every instance of:
- Buzzwords (list above)
- Mechanical connectors
- Identical-length paragraphs
- Chained passive voice
- Unsupported hyperbole
- Absolute neutrality
- Transition crutches

### Step 2: Prune

Delete everything that is filler:
- "It is important to note that" → [delete]
- "It is worth mentioning that" → [delete]
- "It should be pointed out that" → [delete]
- "As previously mentioned" → [delete]
- "In today's world" → [delete]

### Step 3: Vary

Rewrite to break symmetry:
- One short line
- Long paragraph with data
- Another short line
- List or table
- Closing paragraph with opinion

### Step 4: Personalize

Add a layer of judgment/perspective:
- "This is debatable because..."
- "In our experience..."
- "The data that concerns us most is..."
- "Frankly, this solution doesn't convince"

### Step 5: Verify

Run the result through:
- An AI detector (GPTZero, Originality)
- A read-aloud test (if it sounds like a robot, it failed)
- The test: "would a human say this in a conversation?"

---

## Anti-patterns checklist

Use this checklist before delivering any humanized text:

| Signal | Present | Fixed |
|-------|----------|-----------|
| Delve / dive / deep dive | | |
| "In today's world / nowadays" | | |
| All paragraphs same length | | |
| More than 1 "however" per page | | |
| "It is important to note" | | |
| Rhetorical question at the end | | |
| 0 opinions or judgments | | |
| Language more formal than the context | | |
| Connector "moreover / on the other hand" repeated | | |
| Passive voice in more than 30% of verbs | | |
| Numbers without source | | |
| "Nevertheless / nonetheless" | | |
| Em dash `—` separating repeated label/value | | |
| Claims without attributed source | | |

---

## Error Handling

| Cause | Fix |
|-------|-----|
| Text still reads as AI after one pass | Run through AI detector (GPTZero, Originality). Identify remaining tells. Apply second pass focusing on burstiness (vary sentence length). |
| Over-correction: text became too informal | Match register to the channel and audience. Internal email: casual-direct. Client report: professional. Academic: formal. |
| Removing all connectors made text choppy | Keep natural connectors ("but", "so", "and", "then"). Only remove mechanical ones ("Moreover", "Nevertheless", "Consequently"). |
| Added filler words now sound forced | Use colloquialisms sparingly. "Well", "look", "the thing is" — max 1-2 per page. Overuse sounds fake. |
| Passive-to-active conversion reads awkwardly | Not all passives are bad. Keep passive when the actor is unknown or irrelevant. Target < 30% passive voice, not 0%. |
| Text lost important nuance when simplifying | Preserve technical precision. Humanize the wrapper, not the substance. Facts, data, and specific claims stay intact. |
| Em dash removal broke sentence flow | Replace `—` with parentheses, comma, colon, or restructure sentence. Don't just delete — find the right natural alternative. |
| AI detector still flags the text | Check burstiness distribution. Ensure paragraph lengths vary (1-line to 8-line mix). Add one genuine opinion/judgment. Verify no rhetorical question closers. |

## Sources

- Grammarly (2026): "Common Words and Phrases in AI-Generated Text"
- MIT Technology Review (2025): "How to spot AI-generated text"
- GPTZero (2025–2026): "AI Detection Benchmarking", "Perplexity and Burstiness Explained"
- QuillBot: article "Burstiness and Perplexity Explained"
- Reddit r/auscorp: "What's the most obvious tell that someone has used AI"
- Reddit r/cybersecurity, Hacker News discussions
- Ippolito et al., Google Brain (2020): "Automatic Detection of Generated Text"
- JustDone / AHelp: Spanish AI detection guides
- print-css.rocks, BrowserStack, pdf4.dev (document formatting research)

## Checklist

- [ ] Skill loads without errors in the AI agent
- [ ] YAML frontmatter is valid (description, compatibility, audience)
- [ ] Workflow section provides clear step-by-step instructions
- [ ] Error handling section covers common failure modes
- [ ] All referenced files (references/, scripts/, assets/) exist
- [ ] Skill triggers correctly for intended use cases
- [ ] No broken links or missing resources


[View on SkillFed](https://skillfed.io/EliasOulkadi/shokunin/humanize) · [View on GitHub](https://github.com/EliasOulkadi/shokunin)