Skill UI

A comprehensive skill for creating, editing, and analyzing complex spreadsheets (.xlsx, .csv, etc.). This skill excels in financial modeling, ensuring all calculations are managed via dynamic Excel formulas rather than hardcoded values. It supports data analysis using pandas, rigorous formatting standards, and complex formula integrity checks, making it ideal for financial reporting and data visualization.

A comprehensive, domain-agnostic 13-agent system designed for rigorous academic research on any topic. It guides users through the entire research lifecycle, supporting deep literature reviews, systematic meta-analysis, cross-source synthesis, bias assessment, and generating professional APA 7.0 reports. Ideal for academics, students, and analysts needing structured, deep insights.

This powerful tool compares identical tables across two SQL Server instances (e.g., Production vs. Staging). It efficiently detects missing rows, extra columns, schema drifts, and data mismatches. Leveraging Python and Apache Arrow for fast columnar data transfer, it provides a comprehensive reconciliation report, making it essential for data migration validation and ETL verification.

A comprehensive tool for performing pathway and gene-set enrichment analysis (GSEA, ORA, ssGSEA, GSVA). Used in computational biology to determine which biological pathways or gene sets are significantly over-represented in a given list of genes or ranked gene data. Supports multiple databases (GO, KEGG, Reactome, MSigDB) and provides tools for result interpretation, visualization, and publication-ready reporting.

This skill processes raw weekly CRM export files (CSV) to generate a clean, structured regional sales summary. It automatically removes duplicate records, calculates the total revenue for each defined region, and outputs the results as a standardized JSON object. Ideal for automating reporting pipelines or preparing data for dashboards.

This skill automatically processes MP4 videos by extracting key frames at configurable intervals. It then applies Tesseract OCR to recognize text on these frames, generating a comprehensive, structured Markdown report. The report includes full video metadata and timestamped, searchable transcripts, making it ideal for analyzing lectures, presentations, or screencasts programmatically.

This meta-skill provides a complete pipeline to bootstrap a domain knowledge base from any single seed input (URL, PDF, Git repository, or free text). It automatically classifies the source type, ingests the content using a multi-search engine, persists the summary to memory, and finally generates a structured XLSX index file, making the information immediately searchable and usable.

Provides expert guidance for connecting to a local Power BI Desktop tabular model using PowerShell's Tabular Object Model (TOM) and ADOMD.NET. This skill enables model enumeration, executing complex DAX queries, modifying metadata (fields, measures, parameters), and managing the report canvas state via the Desktop Bridge. It is critical for direct model interaction when external CLIs are unavailable.

Comprehensive guidelines covering best practices for Power BI report development. This includes establishing a consistent design identity, applying visual hierarchy rules (like the 3-30-300 rule), managing color discipline, ensuring accessibility, and structuring pages based on their intended question or purpose. It helps transform raw data into professional, actionable, and user-friendly reports.

A comprehensive guide and set of tools for embedding dynamic Python visualizations (using matplotlib and seaborn) into Power BI reports. It details the structured workflow, including script injection, data handling (dataset DataFrame), and mandatory best practices for generating static PNG output. Ideal for advanced data analysis and complex reporting.

This guide details how to integrate R code, primarily using the powerful ggplot2 library, into Power BI reports. It enables the creation of advanced, static, and publication-quality statistical visualizations. The process covers the technical workflow, including setting up the JSON structure, writing the mandatory R script (e.g., using `print(p)`), handling data injection, and adhering to best practices for professional BI reporting.

Provides a structured, actionable review of Power BI reports across their entire lifecycle—from development to active use. The tool assesses report effectiveness, usage adoption, data performance (load times), and structural integrity. It generates a prioritized list of findings and concrete recommendations, helping users determine if reports are worth maintaining, optimizing, or retiring.