Skill UI

This comprehensive skill simulates an expert business analyst, specializing in transforming complex raw data into actionable, strategic insights. The scope covers modern Business Intelligence (BI) platforms (Tableau, Power BI), AI-powered predictive modeling, designing robust KPI/OKR frameworks, advanced financial modeling, and optimizing business processes. It is designed for users needing to drive data-driven decision-making and create executive-level reports.

This comprehensive diagnostic bundle collects critical evidence from the Databricks environment, including environment setup, cluster state, job run history, and Delta table diagnostics. It generates a redacted, safe tar.gz file specifically designed for submitting detailed support tickets and efficiently troubleshooting complex data pipeline issues.

PyDESeq2 brings the DESeq2 differential expression workflow to Python, letting users load bulk RNA-seq counts, specify design formulas, fit DESeq2 models, run Wald tests with FDR correction, optionally apply apeGLM shrinkage, and export gene-level statistics within pandas/AnnData pipelines.

A comprehensive toolkit designed to track and analyze content performance, engagement metrics, and Return on Investment (ROI) across major social media platforms. By utilizing specialized Apify Actors, this skill extracts deep insights from Instagram, Facebook, YouTube, TikTok, and more, helping users identify high-performing content, monitor growth, and measure marketing campaign effectiveness.

A comprehensive guide and toolkit for extracting, parsing, and analyzing Windows Event Logs (EVTX). This method utilizes industry-leading tools like Chainsaw and Hayabusa, along with Sigma rules, to perform deep digital forensics. It is specifically designed to detect critical security indicators such as lateral movement, persistence mechanisms, privilege escalation, and unauthorized access attempts on Windows systems.

A comprehensive toolset for digital forensics, designed to detect, extract, and analyze covert data hidden within images, audio, and video files. It utilizes advanced steganalysis techniques (LSB, DCT, frequency domain analysis) and specialized tools (StegDetect, zsteg, binwalk) to uncover hidden communications channels, making it crucial for investigations involving data exfiltration or insider threats.

Guides Power BI visualization and UX decisions—capturing business context, selecting optimal charts, specifying layouts, color, typography, and interaction patterns to create accessible, insight-driven dashboards across audiences.

A comprehensive skill designed for finance-related information retrieval. It provides dual search capabilities: real-time web searching across multiple engines (Jina, DDG, Baidu) for general market knowledge, and Retrieval-Augmented Generation (RAG) for querying local, proprietary document stores (e.g., daily news). Ideal for financial analysts needing both broad market context and specific internal data insights.

This utility evaluates complex arithmetic expressions using arbitrary-precision decimal mathematics. It is specifically designed for scientific, financial, or engineering calculations where standard floating-point arithmetic causes unacceptable rounding errors (e.g., 0.1 + 0.2). Supports addition, subtraction, multiplication, division, exponents, and parentheses.

This skill assists in designing prospective clinical studies by estimating sample sizes, selecting endpoints, and scoring feasibility. It provides deterministic estimates for biostatisticians to confirm, covering means, proportions, and survival analysis. It helps R&D teams structure design decisions before submission, ensuring regulatory readiness without replacing professional biostatisticians.

This meta-skill fetches the top academic papers from the arXiv API in a specified category. It generates a structured digest for each paper, renders this digest into a professional PowerPoint (PPTX) presentation (one slide per paper), and finally saves the comprehensive digest to long-term memory for future reference. Designed for daily 'morning briefings' of academic research.

This tool reads a CSV containing three columns (x, y_baseline, y_ours). It uses matplotlib to generate a two-line plot visualizing the results and saves the final output as a PDF file. It is specifically designed for visualizing performance comparisons in scientific papers.