Skill UI

Conducts a comprehensive, structured ethical review for any AI or ML model, feature, or product. It assesses risks related to fairness, bias, transparency, privacy, and societal impact, providing a risk tier score, necessary mitigations, and governance documentation suitable for pre-deployment compliance.

This utility detects and redacts sensitive personally identifiable information (PII) from screenshots and images. It can mask various data types, including IDs, credit card numbers, API keys, phone numbers, and emails. Crucially, all processing is conducted locally and offline, ensuring that sensitive data never leaves the user's machine. It is essential for secure debugging, data sharing, and analysis workflows.

Context Kit is an external framework designed to organize and manage personal, durable context data (like identity details, memories, and domain knowledge) into secure Markdown artifacts. It helps users set up robust knowledge bases for coding agents (e.g., Claude Code), guiding them on best practices for data privacy, local storage, and safe integration, while preventing sensitive data leaks.

This guide details integrating FoundationModels for running Large Language Models (LLMs) directly on the device (iOS 26). It covers advanced patterns including text generation, extracting structured data using @Generable, implementing custom tool calling for domain logic, and streaming responses for real-time UI updates. Key features emphasize strong privacy and offline capability, ensuring no data leaves the device.

Pi-hole is a powerful, network-wide DNS ad blocker that runs on Linux hosts (like Raspberry Pi). It intercepts all DNS queries on your local network, blocking advertisements, trackers, and known malware domains before they reach your devices. This guide covers setup via Docker or bare metal, configuring network DNS, managing blocklists, and enabling secure DNS-over-HTTPS (DoH) for enhanced privacy.

This skill reviews prediction market, basket, oracle, and trading-agent workflows to ensure compliance, safety, data quality, and privacy. It must be run before any workflow handles user portfolio data, venue authentication, API keys, or trade planning to mitigate execution and regulatory risks across multiple domains.

A comprehensive tool for deep marketing performance analysis. This skill guides users in defining robust KPI frameworks, building attribution models, investigating traffic anomalies, and developing advanced measurement strategies. It is essential for modern digital marketing, including handling AI-generated traffic, dark social attribution, and cookieless privacy environments.

A comprehensive guide for preparing scholarly manuscripts involving spatial data. It outlines best practices for documenting data provenance (sources, projections, processing chains), ensuring reproducibility, and adhering to critical ethical standards such as geoprivacy and human-subjects protection. Essential for maintaining research integrity in academic publishing.

This comprehensive guide helps authors strategically position their computer security manuscripts for the ACM Conference on Computer and Communications Security (CCS). It details topic fit, required threat modeling, evidence presentation, and critical comparisons with sister venues (e.g., S&P, USENIX Security). It serves as a high-level 'fit/framing' tool for maximizing submission success in core areas like privacy, cryptography, and systems security.

This comprehensive guide assists authors in evaluating the suitability, framing, and structural requirements for submitting research on wireless, mobile, IoT, sensing, and network security/privacy to the ACM WiSec conference. It provides critical expertise on aligning the paper's contribution type, threat model, and evidence standards with top-tier academic conference expectations, ensuring the work emphasizes the physical or network context.

Provides comprehensive guidelines for researchers packaging and releasing artifacts (data, code, instruments) derived from real communities in CSCW research. It emphasizes ethical constraints, de-identification techniques (such as quote search and join attacks), and best practices for protecting studied communities' privacy, ensuring responsible sharing.

This comprehensive skill guides researchers through the critical ethical framework for anthropological and social science manuscripts. It emphasizes 'do no harm,' continuous informed consent, community accountability, and proper handling of sensitive data, cultural heritage, and human remains. It ensures that all data sharing and knowledge reuse plans prioritize the rights, privacy, and well-being of interlocutors above academic publication needs.