Skill UI

A comprehensive set of programmatic interfaces for RuView's Wi-Fi sensing capabilities, including the CLI binary, REST API, and WebAssembly builds. This toolkit allows developers to integrate sophisticated disaster survivor detection and signal analysis into various environments, such as scripting, web browsers, and edge devices (ESP32-WASM3). Ideal for systems requiring cross-platform, scalable sensing data streams.

This skill guides users through connecting external services, proprietary APIs, or custom tools to the Digital Marketing Pro plugin. It manages the entire integration lifecycle: searching the npm registry for pre-built packages, generating complex MCP JSON configurations, handling environment variables, and executing connectivity tests. Essential for expanding plugin functionality with external data sources like CRM, payment gateways, or specialized analytics platforms.

This utility switches the active operational credential profile to manage different brands within a multi-client agency environment. It performs mandatory, deep validation of API keys, OAuth tokens, and environment variables before switching, ensuring that all subsequent platform operations (e.g., ad spending, reporting) are correctly routed to the target brand's account. It is crucial for preventing cross-client data leakage and maintaining audit integrity.

A comprehensive guide for establishing rigorous causal claims in international macro-finance. This skill addresses complex econometric challenges such as global confounders, policy endogeneity, and high-frequency surprises in open-economy models. It provides methodologies for cross-country panel data, capital control analysis, and advanced inference, ensuring results meet the high standards of top-tier international finance journals.

Provides comprehensive guidelines for ethical handling, data transparency, and documentation in New Media & Society research. It covers crucial issues like informed consent, anonymization best practices, scraping legal constraints (ToS), and methods for making qualitative or computational claims credible, ensuring responsible data sharing and academic rigor.

A comprehensive guide for ensuring the scientific reproducibility of research papers that rely on dynamic web data, such as web crawls, platform APIs, or live system traffic. It defines three reproducibility regimes (Frozen, Decaying, Unreplayable) and provides detailed instructions on documenting data decay, temporal splits, environment configurations, and computational seeds to maintain the rigor of published findings.

gget is a versatile CLI and Python package designed for rapid, reproducible bioinformatics searches across major genomic reference databases (e.g., Ensembl, UniProt). It allows users to quickly query gene metadata, perform initial BLAST/BLAT style alignments, and explore associated pathways, cancer, or disease modules. It is ideal for initial data exploration and generating reproducible evidence logs before building complex, full-scale local pipelines.

This specialized skill is designed for advanced security analysis, tracing the complete trust chain from cloud metadata services to accepted privilege. It is used in penetration testing or CTF environments to meticulously prove how metadata-derived credentials (such as instance identities or tokens) are issued and subsequently accepted by a cloud or control plane API, thereby exposing the decisive trust edge.

This skill facilitates the ingestion of unstructured clinical notes and reports from FHIR R4 EHR APIs (e.g., Epic, Cerner). It handles complex tasks including paginating large search results, decoding base64 attachments (PDF, text), and extracting narrative content. The extracted text is then passed to the OpenMed pipeline for HIPAA-compliant de-identification and subsequent NLP analysis, enabling structured data insights from raw clinical records.

A comprehensive tool designed to help developers compare multiple technical approaches for solving a single problem. It systematically identifies and analyzes the trade-offs, complexity, performance, and learning curves associated with different design patterns (e.g., state management, data fetching, API design). Ideal for architectural reviews and making informed, robust technology stack decisions.

This skill implements an advanced reference pattern for integrating with Monitoring Control Platform (MCP) servers. It ensures accurate data retrieval by first reading a domain-specific 'gotchas' reference file, mitigating query failures caused by complex server behaviors, pagination limits, or subtle API quirks. It analyzes issue data, groups errors by root cause, and generates a structured, actionable markdown report for improved system health visibility.

This skill standardizes free-text medication mentions extracted by OpenMed to RxNorm RxCUIs using the public RxNav API. It resolves complex relationships between brand names, generic ingredients, strengths, and dose forms, providing a stable, canonical code. Ideal for clinical interoperability, data analytics, de-duplication, and building US Core Medication resources.