Skill UI

Expert guidance for the Fabric CLI (fab) and Fabric/Power BI REST APIs: manage workspaces, lakehouses, notebooks, pipelines, semantic models, reports and capacities, and estimate capacity-unit cost before running any operation.

A comprehensive guide and API wrapper for triggering, monitoring, and validating semantic model refreshes in Power BI/Fabric. It supports various refresh types (full, data-only, calculate-only, etc.), enabling granular control over data reloading, recalculation, and performance troubleshooting using the Fabric CLI and Enhanced Refresh API.

This skill generates detailed, structured research protocols for various academic, clinical, or market research studies. It ensures all critical components—such as objectives, study design, participant criteria, methodology, data management, statistical analysis plan, and ethical considerations—are comprehensively documented, providing a robust framework for any scientific investigation.

A comprehensive guide on querying data stored in Fabric's OneLake using DuckDB. This skill supports two operational modes: local command line interface (CLI) for ad-hoc analysis, and in-notebook mode for seamless integration within Fabric notebooks. It can read Delta Lake tables and various raw formats (Parquet, CSV, JSON), making it ideal for data exploration, validation, and schema discovery in a read-only fashion.

This guide details how to deploy OpenCTI, a powerful, open-source threat intelligence platform, and utilize the pycti Python client. It teaches analysts how to model complex cyber threat intelligence, including threat actors, campaigns, and indicators, into a structured STIX 2.1 knowledge graph. Use this for centralized threat-intel correlation, building adversary graphs, and generating STIX bundles for detection engineering.

This skill provides querying capabilities for the 1000 Genomes Project dataset, covering 3,202 whole-genome-sequenced individuals on the GRCh38 assembly. It allows users to identify variants within a region, find specific individuals who carry defined genetic variants, or determine the relatedness between two named individuals. Results include allele frequencies (AF), AlphaMissense scores, and various clinical annotations. Use this tool for advanced genomic cohort analysis.

This skill guides users through the complete lifecycle of data quality incident management using Monte Carlo MCP tools. It performs detailed investigation, including root cause analysis and blast radius assessment. It then coordinates various external tools (APIs, CLI) to propose and execute appropriate remediation actions, ensuring all data incidents are resolved with full context.

This skill utilizes hyperbolic space embedding (Poincare ball model) to represent complex data structures with inherent hierarchy, such as dependency trees, ontologies, or module taxonomies. Unlike standard Euclidean embeddings, hyperbolic space preserves hierarchical distances efficiently, allowing for accurate distance calculations (geodesic distance) that grow logarithmically with tree depth. It is ideal for advanced knowledge graph analysis and code architecture mapping.

A comprehensive skill to extract and transcribe subtitles from any YouTube video URL. It utilizes a two-stage approach: first, attempting fast extraction via the yt-dlp CLI tool; failing that, it falls back to advanced browser automation using Chrome DevTools MCP to scrape the transcript panel content directly from the webpage DOM. The output is always a clean, timestamped plain text file.

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.

Generates comprehensive quality intelligence reports by analyzing historical evaluation scores. This tool tracks content performance over time, identifies improving or declining content types, detects significant quality regressions against baselines, and provides prioritized, actionable recommendations for improving brand quality across various content dimensions.

A comprehensive guide for authors submitting clinical or translational research to the American Journal of Obstetrics and Gynecology (AJOG). It provides detailed criteria on scope fit, required methodologies (e.g., CONSORT, STROBE), ethical considerations (especially pregnancy-research ethics), and house style requirements, ensuring the study meets the journal's high clinical importance standard.