Skillget

genpark-personal-agent-digital-footprint-privacy-shaking-skill

mcp
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  • License — License: MIT
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  • Active repo — Last push 0 days ago
  • Low visibility — Only 7 GitHub stars
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SUMMARY

Audits browser and device fingerprint entropy, models anonymity set sizes, and synthesizes high-entropy decoy search schedules to scramble algorithmic ad profiles.

README.md

Personal Agent Digital Footprint Privacy Shaking Skill

OpenClaw Ecosystem
Dual-Org Sync
Zero Dependencies
Model Context Protocol
Production Grade

Zero-dependency browser fingerprint entropy auditor, anonymity pool estimator, and synthetic decoy traffic schedule synthesizer to resist surveillance capitalism profiling.

Architecture

flowchart TD
    DeviceVectors[Canvas, WebGL, UA, Screen, Audio, Fonts] --> EntropyEngine[Shannon Entropy Auditor]
    EntropyEngine --> AnonymityPool[Global Anonymity Cohort Size K = 2^(33 - H)]
    EntropyEngine --> MitigationPlan[Fingerprint Normalization Defenses]
    UserCentroids[True Behavioral Clusters] --> DecoySynthesizer[Orthogonal Decoy Traffic Synthesizer]
    DecoySynthesizer --> TrafficSchedule[Poisson Dispersed Query Schedule]

Quickstart

from client import PersonalAgentDigitalFootprintPrivacyShaking

agent = PersonalAgentDigitalFootprintPrivacyShaking()
audit = agent.audit_fingerprint_entropy(installed_fonts_count=160, screen_res="2560x1440x24")
print(f"Total Entropy: {audit['total_entropy_bits']} bits | Anonymity Pool: {audit['estimated_anonymity_pool_size']}")

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