Skill UI

A comprehensive workflow for executing advanced, semantic web searches using Exa. This tool moves beyond simple keyword matching, enabling deep context retrieval by understanding the intent behind the query. Key features include RAG context retrieval, content extraction (summaries, highlights, full text), and robust filtering by date range, specific domains, and content categories. Ideal for building knowledge base search features and complex research pipelines.

NeMo Curator streams GPU-accelerated curation for LLM training, with super-fast fuzzy deduplication, multimodal quality filters, semantic dedupl, PII redaction, NSFW checks, and RAPIDS-scaled pipelines for prepping massive corpora.

A comprehensive skill for ingesting, analyzing, and manipulating multi-modal video and audio content. Supports real-time desktop capture, live stream monitoring (RTSP), and file uploads (URL/local). Capabilities include advanced indexing (visual, semantic, temporal), precise moment searching, professional timeline editing (subtitles, overlays, dubbing), transcoding, and generating actionable alerts. Ideal for content creators, monitoring systems, and complex media workflows.

A specialized tool for searching published, peer-reviewed academic papers from major venues like IEEE, ACM, and Springer. Unlike preprint services (like arXiv), this skill provides verified citation counts, detailed venue metadata, and filtering options for finding established, high-impact research literature. Ideal for formal academic research and literature reviews.

Helps implement optimized Power BI semantic models by analyzing the active model with MCP tools, then advising on star schemas, DAX, relationships, security, documentation, and performance best practices for reporting scenarios.

Provides a systematic guide for diagnosing and improving poor search quality in vector databases like Qdrant. This guide covers troubleshooting issues such as low recall, when approximate search degrades, selecting optimal embedding models, and correctly tuning HNSW parameters, quantization, and filtering strategies. Essential for optimizing RAG and semantic search pipelines.

This tool performs a rigorous Level 2 semantic epistemic review of Agent-Native Research Artifacts (ARAs). It assesses six critical dimensions—including evidence relevance, falsifiability, and methodological rigor—to determine the content's intellectual soundness. It is used after initial structural validation to provide objective, constructive criticism, scoring the work from Strong Accept to Reject.

This skill provides expert, guided assistance for creating, auditing, and improving Best Practice Analyzer (BPA) rules for Power BI semantic models. It utilizes an interactive, double-diamond discovery process to gather deep context about your organizational standards, model structure, and business goals before generating tailored, reusable data validation and governance rules.

This tool analyzes and maps the downstream dependencies of a semantic model across multiple Fabric workspaces. It is crucial for performing impact assessments before making modifications, auditing connected reports, or mapping cross-workspace data flows. It automates the lineage discovery process, providing comprehensive visibility into which reports rely on a specific data source.

A comprehensive guide to authoring, optimizing, and validating Power Query M expressions used within semantic model partitions. This resource covers crucial topics such as maintaining query folding for performance, applying early filtering and column pruning, and leveraging the Power Query API for robust data validation and debugging.

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.

Design, build, refresh, and audit Power BI / Analysis Services tabular semantic models from the terminal: star schema, relationships, measures, calculation groups, RLS roles, incremental refresh, VertiPaq optimization, and Copilot readiness.