humanizer-enhanced

# Humanizer enhanced: remove AI writing patterns

Identify and remove signs of AI-generated text. This enhanced version includes crypto/Web3 patterns and adds personality to make content sound genuinely human-written.

## Quick start

```text
/humanizer                    # Humanize current file or selection
/humanizer path/to/file.md    # Humanize specific file
/humanizer --scan             # Scan only, don't edit (show issues)
/humanizer --batch drafts/    # Process all .md files in directory
```

---

## Process

### Step 1: Scan for patterns

Identify all AI patterns in the text, categorize by severity:

- **HIGH** — Obvious AI tells, must fix (negative parallelism, chatbot artifacts, em dash overuse, vague attributions, copula avoidance)
- **MEDIUM** — Common AI patterns, should fix (rule of three, significance inflation, synonym cycling)
- **LOW** — Minor tells, fix if time permits (title case headings, excessive bold)

### Step 2: Report findings

Show user a summary:

```text
## Humanizer scan results

HIGH (3 issues)
- Line 45: Negative parallelism "isn't X. It's Y"
- Line 89: Em dash overuse (5 instances)
- Line 120: "Research shows" without attribution

MEDIUM (5 issues)
- Line 23: Rule of three pattern
- Line 67: Copula avoidance "serves as"
...

LOW (2 issues)
- Line 12: Title case heading
...

Total: 10 issues found
Estimated humanization: ~15 edits needed
```

### Step 3: Fix (with user approval)

Ask user: "Fix all issues? Or review one by one?"

### Step 4: Add soul

After fixing patterns, review for personality. Sterile writing is still obvious AI. See `references/communication-crypto-soul-patterns.md` for the full soul/personality guide.

### Step 5: Readability check

Check Flesch-Kincaid readability. Target grade 10-12 for developer content, grade 8-10 for general audience. If score is too high (too complex), simplify longest sentences and replace jargon.

### Step 6: Em dash regression scan

After all other fixes, run a final check for em dashe...