Skill UI

This guide outlines essential security best practices for integrating the Speak API. It covers critical areas like securing API keys using secrets managers, ensuring audio data privacy by deleting local files, and maintaining compliance with major regulations such as COPPA and FERPA. Use this knowledge when building production-ready, secure language learning applications.

Implement comprehensive GDPR and CCPA compliance measures within Supabase. This skill guides developers on setting up Row Level Security (RLS) for tenant isolation, managing PII columns, executing right-to-deletion workflows, auditing sensitive data, and establishing automated data retention policies. Essential for any SaaS application handling regulated user data.

This skill guides the implementation and management of meeting data within the TwinMind platform, ensuring adherence to GDPR compliance. It covers secure transcript storage, memory vault management, data export protocols, and deletion policies. Ideal for developers integrating complex meeting AI operations or managing enterprise-level data governance.

This skill outlines security best practices for the TwinMind AI meeting assistant. It covers crucial aspects like on-device audio processing, encrypted cloud backups, and managing microphone permissions. Use it when setting up new TwinMind instances or managing AI operations to ensure data privacy, compliance, and robust security for sensitive meeting data.

A comprehensive guide for developers on handling sensitive data and ensuring compliance with major privacy regulations like GDPR and CCPA when deploying serverless functions on Vercel. Learn techniques for PII redaction in logs, implementing data subject rights (Right to Access/Erasure), securing session cookies, and configuring data residency to meet global privacy standards.

This skill provides comprehensive configuration for Windsurf deployments, managing data transmission controls, retention policies, and regional compliance settings. It ensures adherence to global privacy standards, such as GDPR, by handling data governance and defining code exclusion patterns.

This comprehensive guide details how to control and audit the scope of code and data accessible by AI tools (like Codeium or Windsurf AI). Learn to implement robust data exclusion patterns, set compliance boundaries (e.g., HIPAA, GDPR), and configure secure deployment modes, ensuring sensitive data and secrets are never processed or retained by the AI model.

Compose comprehensive clinical reports—case studies, diagnostics, trials, and patient notes—while ensuring CARE/ICH-GCP compliance, HIPAA-safe documentation, and mandatory AI-generated scientific schematics for each deliverable.

An expert guide for deploying and optimizing Large Language Models (LLMs) entirely on local hardware. Mastering the entire local AI ecosystem, including inference engines like Ollama, vLLM, and llama.cpp. Provides deep knowledge on quantization formats (GGUF, EXL2, AWQ), VRAM calculation, and ensuring privacy-first, offline deployment for state-of-the-art models.

A comprehensive guide to integrating privacy protections into software architecture from the ground up. This skill ensures compliance with major global regulations like GDPR, CCPA, and LGPD by implementing core principles such as data minimization, purpose limitation, and default privacy settings. Essential for developers building any application that handles personal user data.

Guards borrower interactions by enforcing TRID, RESPA, TILA, ECOA/Fair Lending, licensing, disclosures, and privacy rules whenever rates, fees, qualifications, or data are discussed in mortgage conversations.

This skill implements a simplified version of the Signal Protocol, focusing on robust end-to-end encryption (E2EE) for messaging applications. It covers critical cryptographic components including X3DH key agreement, the Double Ratchet algorithm for continuous key management, and AES-256-GCM for message encryption. The implementation ensures forward secrecy, meaning that compromising a current key does not reveal past messages. Use this when designing, building, or evaluating the security architecture of a messaging service to guarantee that only communicating parties can read the messages.