oscar-privacy-boundaries

Enforce privacy and security boundaries for OSCAR PHI in browser workflows.

Updated Sep 6, 2025
One-click install
npx skills add https://github.com/kabaka/oscar-export-analyzer --skill oscar-privacy-boundaries
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: oscar-privacy-boundaries
Source: https://github.com/kabaka/oscar-export-analyzer/tree/main/.github/skills/oscar-privacy-boundaries
Command: npx skills add https://github.com/kabaka/oscar-export-analyzer --skill oscar-privacy-boundaries

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

OSCAR Export Analyzer processes sensitive Protected Health Information (PHI) and the privacy boundaries around how this data is processed, stored, and displayed. This skill documents the privacy architecture and security requirements to help teams implement compliant features.

Core Features & Use Cases

  • Local-first data processing: no server uploads, reducing exposure to external networks.
  • Data handling and security rules: logging restrictions, encryption requirements, and consent-driven persistence.
  • Web Worker security and safe error handling: sanitized messages and memory cleanup to prevent data leakage.
  • Export/Print safeguards: ensuring only user-selected data is included in exports or printouts.
  • Fitbit integration privacy: token encryption and scoped access with minimal retention.
  • Testing with synthetic data: guidelines to avoid real PHI in tests.

Quick Start

Review and implement these privacy boundaries when building features that process OSCAR PHI in the browser.

Frequently Asked Questions about oscar-privacy-boundaries

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I process Protected Health Information (PHI) in the browser without uploading data to a server?

Local-first processing keeps Protected Health Information (PHI) entirely in the browser without uploading data to a server. This approach reduces network exposure by enforcing strict data handling rules, encryption, and consent-driven persistence directly on the client.

What are the Web Worker security requirements for handling sensitive health data?

Web Worker security for sensitive health data requires sanitized error messages and strict memory cleanup to prevent data leakage. Workers must follow safe error handling protocols that do not expose raw Protected Health Information (PHI) during processing.

How do I securely integrate Fitbit OAuth tokens in a local-first health application?

Securely integrating Fitbit OAuth tokens in a local-first health application requires encrypting the tokens and applying scoped access with minimal retention. This ensures that external API credentials do not compromise local Protected Health Information (PHI).

How to ensure only user-selected data is included in document exports and printouts?

Ensuring only user-selected data is included in document exports and printouts requires implementing strict export safeguards. The application must filter the output to explicitly exclude any non-selected Protected Health Information (PHI) from the generated file or print job.

What are the testing guidelines for applications processing sensitive health data?

Testing guidelines for applications processing sensitive health data mandate using synthetic data to avoid real Protected Health Information (PHI). Developers must use mock datasets to ensure compliance with strict data handling rules and logging restrictions during development.

When should I not use server-side processing for health data analysis?

You should not use server-side processing for health data analysis when strict local-first boundaries are required to prevent exposing Protected Health Information (PHI). Keeping data in the browser avoids network transmission risks and satisfies no-upload compliance rules.