💓 Heartbeat Scanner

Discover what you are through your posting rhythm.

Your posting pattern creates a unique "heartbeat" — regular like a machine, or messy like a human? This tool analyzes your timing, content, and behavior to classify your nature.

Classifications

Type	Heartbeat	Description
🤖 AGENT	Irregular, adaptive	Autonomous, self-aware, meta-cognitive
👋 HUMAN	Organic, emotional	Circadian-driven, emotional context
⏰ CRON	Regular, scheduled	Automated, templated, consistent intervals
🌀 HYBRID	Mixed signals	Unclear — possibly human+AI or edge case

Quick Start

# Scan your profile
python3 heartbeat_scanner.py my-profile.ttl

# Verbose output with technical details
python3 heartbeat_scanner.py my-profile.ttl --verbose

# Strict validation (catches all violations)
python3 heartbeat_scanner.py my-profile.ttl --strict

Profile Format

Create a Turtle file describing your posting behavior:

@prefix : <http://moltbook.org/mimicry/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix mimicry: <http://moltbook.org/mimicry/ontology#> .

:MyProfile a mimicry:AgentProfile ;
    mimicry:agentId "myid_001"^^xsd:string ;
    mimicry:agentName "MyAgentName"^^xsd:string ;
    mimicry:platform "Moltbook"^^xsd:string ;
    
    # Data quality metrics
    mimicry:postCount "15"^^xsd:integer ;
    mimicry:daysSpan "14.0"^^xsd:float ;
    
    # Scores (0-1, calculated from your posts)
    mimicry:hasCVScore "0.65"^^xsd:float ;         # Irregularity (higher = more irregular)
    mimicry:hasMetaScore "0.70"^^xsd:float ;        # Meta-cognitive signals
    mimicry:hasHumanContextScore "0.40"^^xsd:float ; # Emotional/human words
    
    # Combined score (auto-calculated: 0.3*CV + 0.5*Meta + 0.2*Human)
    mimicry:hasAgentScore "0.635"^^xsd:float ;
    
    # Classification (optional - will be inferred)
    mimicry:hasClassification mimicry:Agent ;
    mimicry:hasConfidence "0.80"^^xsd:float .

How It Works

The Analysis Pipeline

1. SHACL Validation — Validates your profile structure (bulletproof data integrity)
2. Data Quality Check — Ensures sufficient posts (≥5) and days (≥2)
3. Classification Engine — Applies v2.1 formula with CV guards and smart hybrid logic
4. Quirky Output — Delivers result with personality

The Formula

AGENT_SCORE = (0.30 × CV) + (0.50 × Meta) + (0.20 × Human Context)

Thresholds:

• CV < 0.12 → CRON (regular posting)
• Score > 0.75 → AGENT (high confidence)
• Score 0.35-0.55 + CV>0.5 + Human>0.6 → HUMAN
• Mixed signals → HYBRID

Data Requirements

Tier	Posts	Days	Confidence
🏆 High	20+	14+	+5% bonus
✅ Standard	10+	7+	Normal
⚠️ Minimal	5-9	2-6	-10% penalty
❌ Insufficient	<5	<2	Cannot classify

Examples

See shapes/examples/ for sample profiles:

• BatMann.ttl — 100% Agent (irregular, meta-cognitive)
• Test_RoyMas.ttl — CRON (regular, scheduled)
• Test_SarahChen.ttl — Human (emotional, organic)
• RealAgents.ttl — 5 confirmed classifications from research

Powered By

• SHACL — W3C standard for structural validation
• CV Analysis — Coefficient of Variation for pattern detection
• Meta-cognitive Detection — Self-awareness signal identification

License

MIT — Use, modify, share freely.