Skill UI

This skill automatically detects all available computational resources, including CPU core counts, GPU support (NVIDIA, AMD, Apple Silicon), memory capacity, and disk space. It generates a detailed JSON report that goes beyond simple metrics by providing strategic, context-aware recommendations. These recommendations guide users on the optimal computational approach—such as choosing between Dask for out-of-core processing, selecting the right GPU backend, or determining the ideal number of workers for parallel processing—before running any intensive scientific or data analysis task.

This skill guides systematic scientific inquiry by helping users develop testable, evidence-based hypotheses from observations and preliminary data. It strictly follows the scientific method, covering literature review, synthesizing evidence, generating multiple competing mechanisms, evaluating hypothesis quality (testability, falsifiability), and designing detailed experimental protocols. Comprehensive reports mandate the use of scientific schematics for visualization.

Automatically generates professional, publication-quality infographics from simple descriptions. This skill integrates advanced AI models (like Gemini 3 Pro and Perplexity Sonar) to perform deep research, ensure data accuracy, and conduct smart, iterative quality reviews against specific document type thresholds (e.g., marketing vs. report). Ideal for visualizing complex data, processes, and statistics for reports, presentations, and social media.

A comprehensive skill for conducting systematic statistical hypothesis testing. It guides users through the entire data analysis lifecycle, including test selection (t-test, ANOVA, correlation, regression), rigorous assumption checking (normality, homogeneity), running advanced models (Bayesian, frequentist), calculating effect sizes, and generating publication-ready, APA-formatted reports. Ideal for academic research and quantitative analysis.

This skill provides a comprehensive workflow for generating professional and structured financial reports. It guides the user through planning, writing, and editing various sections, and can also generate necessary chart configurations using visual tools. Ideal for condensing complex financial analysis into clear, actionable reports.

This internal agent skill processes raw X/Twitter posts into structured bug candidates. It systematically performs parsing, content deduplication, PII redaction, reliability scoring, and classification. Finally, it clusters related reports using deterministic signatures, providing a highly organized output for efficient bug triage and analysis from large-scale social media streams.

Builds a robust, automated workflow to export critical sales data—including forecasts, quota details, adjustments, and CRM totals—from Clari CRM to a designated data warehouse. The pipeline supports multiple targets like Snowflake, BigQuery, and PostgreSQL, ensuring that real-time revenue intelligence is available for advanced analytics and business reporting.

This skill performs a deep, cross-model audit of experimental results to ensure integrity before claiming findings. It systematically checks for common fraud patterns, such as generating fake ground truths, misleading score normalization, or citing phantom results. Use it when evaluating reported experimental outcomes to ensure methodological rigor and trustworthiness.

This skill guides users on automating fundraising workflow analysis using local data methods. Since Finta lacks a public API, it teaches how to export pipeline data (CSV) and use Python (Pandas) scripts to calculate key funnel metrics, conversion rates, and generate detailed weekly reports for investor tracking and reporting.

Implements a robust data pipeline for handling large documents with the Grammarly API. This utility manages text chunking to comply with API character limits (max 100k), processes text in manageable segments, and aggregates multiple scoring metrics (like correctness, clarity, and tone) into a single, comprehensive report. Ideal for large-scale content analysis and data ingestion.

Provides a comprehensive checklist for deploying Hex data analytics integrations into production. It covers critical operational best practices, including API key management, rate limit handling, error resilience (circuit breakers, exponential backoff), and robust monitoring strategies. This guide ensures that data pipelines are deployed reliably, minimizing downtime and guaranteeing consistent, high-quality data reporting for go-live scenarios.

Conduct comprehensive and systematic literature reviews by searching multiple academic databases (e.g., PubMed, arXiv). This skill guides users through the entire research lifecycle, from defining scope (PICO) and developing search strategies to synthesizing findings. It generates professional markdown and PDF reports, complete with verified citations and mandatory AI-generated scientific schematics for maximum clarity and academic rigor. Ideal for meta-analyses and thesis writing.