| name | phy-content-humanizer-audit |
| description | AI content signature detector for social media posts. Measures 8 linguistic dimensions that LinkedIn's 360Brew and other platforms use to detect AI-generated content — lexical diversity, sentence length variance, transition word density, hedging ratio, contraction usage, personal pronoun density, question frequency, and specific data density. Not a humanizer that rewrites your text — an auditor that tells you exactly which signals are triggering detection so you fix only what's wrong. Research-backed (DivEye arXiv:2509.18880, LinkedIn 360Brew algorithm analysis, stylometric detection studies). Per-platform thresholds for LinkedIn (strictest), Reddit, Twitter/X, HackerNews. Zero external dependencies. |
| license | Apache-2.0 |
| metadata | {"author":"PHY041","version":"1.0.0"} |
| tags | ["social-media","content","linkedin","ai-detection","writing","marketing","authenticity","brand-voice"] |
Cleanup Review
python scripts/_cleanup.py is an optional cleanup helper for the phy-content-humanizer-audit — AI Content Signature Detector skill. It may recursively remove /tmp/skill_build. Show the exact paths first, explain whether they are skill-private temporary paths or user state, and run the cleanup only after the user confirms.
phy-content-humanizer-audit — AI Content Signature Detector
LinkedIn's 360Brew algorithm penalizes AI-detected content with 30% less reach and 55% less engagement. This tool tells you exactly which linguistic signals are triggering detection — so you fix only what's wrong instead of rewriting everything.
Not a humanizer. An auditor.
The Problem
You draft a LinkedIn post (maybe with AI help), publish it, and reach tanks. Why?
LinkedIn's 360Brew uses an LLM to evaluate:
- Lexical diversity — AI repeats vocabulary patterns
- Sentence rhythm — AI maintains unnaturally consistent sentence lengths
- Transition words — AI overuses "Furthermore", "Moreover", "Additionally"
- Hedging language — AI says "arguably" and "it seems" instead of stating opinions
- Formality — AI avoids contractions ("do not" instead of "don't")
- Impersonality — AI rarely uses first-person pronouns
- No questions — AI makes statements, doesn't ask
- Vagueness — AI uses abstract language with no specific data
This tool measures all 8 dimensions, scores each 0-10, and tells you your AI Signature % — the probability a platform algorithm will flag your content as AI-generated.
Quick Start
echo "Your post text here" | python3 ~/.claude/skills/phy-content-humanizer-audit/scripts/content_humanizer_audit.py --platform linkedin
python3 ~/.claude/skills/phy-content-humanizer-audit/scripts/content_humanizer_audit.py --file draft.txt --platform reddit
python3 ~/.claude/skills/phy-content-humanizer-audit/scripts/content_humanizer_audit.py --text "My post..." --platform twitter
python3 ~/.claude/skills/phy-content-humanizer-audit/scripts/content_humanizer_audit.py --file draft.txt --format json
The 8 Dimensions
| # | Dimension | What It Measures | Human Signal | AI Signal |
|---|
| 1 | Lexical Diversity (TTR) | Vocabulary variety (type-token ratio) | TTR 0.55-0.80 | TTR 0.35-0.55 |
| 2 | Sentence Length Variance | Mix of short/long sentences (coefficient of variation) | CV > 0.4 | CV < 0.3 |
| 3 | Transition Word Density | "Furthermore", "Moreover" per 100 words | < 1.5/100w | > 3.0/100w |
| 4 | Hedging Ratio | "arguably", "it seems" per 100 words | < 1.0/100w | > 2.0/100w |
| 5 | Contraction Usage | "don't", "I've", "it's" per 100 words | > 1.5/100w | < 0.5/100w |
| 6 | Personal Pronoun Density | "I", "my", "we" per 100 words | > 3.0/100w | < 1.5/100w |
| 7 | Question Frequency | % of sentences that are questions | 10-25% | 0-5% |
| 8 | Specific Data Density | Numbers, dates, names per 100 words | > 2.0/100w | < 1.0/100w |
Each dimension scores 0-10 (10 = very human). Total /80, mapped to an AI Signature %.
Platform Thresholds
| Platform | WARN above | FAIL above | Why |
|---|
| LinkedIn | 45% | 65% | 360Brew LLM actively detects AI. Strictest. |
| HackerNews | 50% | 70% | Technical audience spots AI quickly. |
| Reddit | 55% | 75% | Community policing + mod tools. Moderate. |
| Twitter/X | 60% | 80% | Short form = less surface for detection. |
AI-Flagged Word List
The tool flags 37 words that are strong AI signals on social media:
leverage, robust, crucial, delve, tapestry, holistic, synergy, paradigm, ecosystem, landscape, streamline, cutting-edge, game-changer, innovative, revolutionary, transformative, comprehensive, meticulous, nuanced, multifaceted, pivotal, seamless, foster, utilize, facilitate, endeavor, underscore, realm, navigate, embark, spearhead, harness, unveil, bolster, cornerstone, unparalleled, groundbreaking
Each found word adds 3% to your AI signature score.
Example Output
Human-written post (PASS)
==================================================================
phy-content-humanizer-audit — AI Signature Report
==================================================================
Platform : Linkedin
Words : 183
AI Sig : 10.5% ✅ PASS
Human : 74.0/80.0
Threshold: WARN >45%, FAIL >65%
==================================================================
📊 Dimension Scores (0-10, higher = more human)
Lexical Diversity (TTR) ██████████ 10.0/10
Sentence Length Variance ██████████ 10.0/10
Transition Word Density ██████████ 10.0/10
Hedging Ratio ██████████ 10.0/10
Contraction Usage ██████████ 10.0/10
Personal Pronoun Density █████░░░░░ 5.5/10
Question Frequency ████████░░ 8.5/10
Specific Data Density ██████████ 10.0/10
AI-generated post (FAIL)
==================================================================
Platform : Linkedin
AI Sig : 100% 🔴 FAIL
Human : 22.0/80.0
==================================================================
Transition Word Density ██░░░░░░░░ 2.6/10 (3.4/100w)
Hedging Ratio █░░░░░░░░░ 1.1/10 (3.4/100w)
Contraction Usage ░░░░░░░░░░ 0.0/10 (0.0/100w)
Question Frequency █░░░░░░░░░ 1.0/10 (0%)
Specific Data Density ░░░░░░░░░░ 0.0/10 (0.0/100w)
🚫 14 AI-flagged words: comprehensive, crucial, cutting-edge,
ecosystem, facilitate, harness, holistic, innovative, landscape,
navigate, paradigm, revolutionary, robust, transformative
How to Use the Fixes
The tool outputs your top 3 fixes ranked by impact:
💡 Top 3 Fixes to Lower AI Signature:
1. Add contractions: change 'do not' → 'don't', 'I have' → 'I've'
2. Add specific data: include a number, date, or tool name
3. Remove AI words: comprehensive, crucial — replace with plain terms
Fix just those 3 things and re-run. Usually drops AI signature by 20-30%.
CI / Pre-publish Gate
echo "$POST_TEXT" | python3 content_humanizer_audit.py --platform linkedin
Research Basis
| Source | Key Finding | How We Use It |
|---|
| DivEye (arXiv:2509.18880) | Human text has richer variability in lexical/structural unpredictability | TTR + sentence variance scoring |
| LinkedIn 360Brew (2026) | LLM-based feed ranking detects AI via lexical patterns, profile alignment | Platform-specific thresholds |
| Stylometric detection studies | AI shows lower sentence length variance, higher transition density | 8-dimension framework |
| LinkedIn algorithm data | 30% reach drop, 55% engagement drop for AI content | WARN/FAIL calibration |
| Consumer research | 52% reduce engagement with suspected AI content | Motivation for the tool |
Technical Notes
- Zero external dependencies — pure Python 3.7+ stdlib
- Sentence splitting — regex-based, handles abbreviations
- Windowed TTR — sliding window of 100 tokens to normalize for text length
- Exit codes — 0 (PASS), 1 (WARN), 2 (FAIL) for CI integration
- JSON output —
--format json for pipeline integration
Companion Skills
| Skill | Relationship |
|---|
phy-brand-voice-guard | Brand-specific content rules (this tool = platform-universal AI detection) |
phy-post-forensics | Analyzes why posts worked/failed (this tool = pre-publish prevention) |
phy-platform-rules-engine | Platform-specific implicit rules (this tool = AI signature specifically) |
