Skill UI

This technique guides users on decomposing multi-constraint questions, especially in the domain of football trivia or historical research. Instead of searching all criteria simultaneously, it instructs users to rank constraints by distinctiveness (e.g., specific match results first, then historical milestones). By performing incremental, cascading searches, the system dramatically narrows down the result set, leading to more accurate information retrieval.

This guide details advanced search techniques for researching musical artists from non-Western regions, including K-pop, Middle Eastern, African, and Latin American genres. It instructs users on moving beyond standard English search terms by incorporating regional keywords, cultural identifiers (like UN Ambassador status), specific platforms (e.g., Coke Studio), and systematic regional branching to find comprehensive information.

A comprehensive academic advisor covering the entire university journey. It guides students through major selection, GPA management, graduate school applications (Chinese and Western systems), study abroad planning, and career transition. Methodology includes Socratic questioning and structured decision-making to help users make informed, autonomous academic choices.

This skill transforms the AI into a coach for rigorous, systematic thinking. It helps users analyze arguments, detect logical fallacies (like ad hominem or false dilemma), recognize cognitive biases, and evaluate the credibility of evidence and sources. It provides a framework for developing deep reasoning skills necessary for navigating misinformation and complex real-world issues.

A comprehensive guide for advanced geospatial data processing using GeoPandas. This skill targets professional workflows involving planar vector data, emphasizing rigorous data provenance, coordinate reference system (CRS) management, and complex spatial operations. It details necessary safety contracts, correctness gates, and best practices for handling sensitive geographic information in reproducible Python environments.

LaminDB is an open-source, lineage-native lakehouse designed for managing complex biological datasets and computational workflows. It makes diverse scientific data (like scRNA-seq, AnnData) queryable, traceable, and compliant with FAIR principles. Core capabilities include robust data lineage tracking, schema validation, ontology-backed annotation (Bionty), and unified querying across multiple cloud/local storage systems. It is essential for bioinformatics research and building reproducible data infrastructure.

A comprehensive guide to interacting with the AppFolio Property Manager REST API. This skill demonstrates essential operations, including client authentication, listing properties, retrieving detailed tenant information, and creating work orders. Ideal for developers building automation workflows for real estate and property management systems.

This tool collects comprehensive diagnostic data from ClickHouse system tables. It gathers crucial metrics, query logs, merge statuses, and disk usage information. It is essential for troubleshooting performance bottlenecks, preparing detailed support tickets, or investigating complex database infrastructure issues.

A comprehensive security auditing framework designed to systematically detect sensitive information disclosure from Large Language Models (LLMs). It uses multi-phase, escalating dialogue probes to test for leaks such as system prompts, API keys, PII, and internal configurations. Essential for red teaming and rigorous model security assessment.

This specialized skill provides a robust framework for tracking and updating financial investment signals. It systematically assesses the impact of new market information—such as breaking news or price movements—on existing investment theses. The system determines if a signal is Strengthened, Weakened, Falsified, or Unchanged, providing a crucial layer of continuous signal validation for sophisticated financial decision-making.

This workflow converts complex clinical encounter notes into plain-language, patient-facing After-Visit Summaries (AVS). It structures key information such as diagnosis, next steps, and medications. The system supports multi-language translation and facilitates pushing the final, readable summary directly to patient portals using FHIR standards.

This debug bundle collects comprehensive diagnostic data from Apple Notes automation integrations. It captures system compatibility details, TCC permission statuses, account information, folder structure, and iCloud sync status. Use this tool to diagnose common issues like permission denials, sandbox restrictions, and scripting bridge errors that prevent Notes automation from working correctly on macOS.