Skill UI

This skill finds and compares decentralized finance (DeFi) yield opportunities across various protocols. It aggregates crucial data, including APY/APR calculations, Total Value Locked (TVL), and comprehensive risk assessments. Use it when researching yield farming strategies, comparing cross-chain protocols, or optimizing crypto investment returns.

This skill acts as an expert risk manager, providing comprehensive guidance on monitoring portfolio risk, calculating R-multiples, and optimizing position limits. It covers advanced quantitative finance topics such as Value at Risk (VaR), correlation analysis, and stress testing using Monte Carlo simulations. Use it for systematic risk assessment, developing hedging strategies (options/futures), and implementing rigorous risk controls in trading workflows.

Provides GraphQL queries to the Open Targets Platform for target-disease associations, tractability, safety, drugs, and multi-omics evidence to guide therapeutic target identification, safety assessment, and repurposing research workflows.

This comprehensive tool helps users set, track, and optimize personal health goals using deep data analysis. It validates goals against the SMART criteria (Specific, Measurable, Achievable, Relevant, Time-bound) and tracks progress by correlating diverse health data, including nutrition, exercise, and sleep patterns. Key features include habit formation analysis, motivation assessment, identifying roadblocks, and generating interactive reports with ECharts visualizations, providing a holistic view of wellness journeys.

A comprehensive tool for analyzing long-term health data, tracking trends across multiple dimensions such as weight, vital signs, symptoms, medication adherence, lab results, and mood. It identifies significant changes, correlations between lifestyle factors and health metrics, and provides data-driven insights, risk assessments, and predictive recommendations for proactive health management.

Systematically evaluates cyber-campaign evidence to attribute a cyber operation to a specific threat actor. This skill utilizes advanced analytical frameworks like the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh multiple indicators, including infrastructure overlaps, TTP consistency, malware similarity, and operational patterns, providing confidence-weighted attribution assessments for incident response.

This skill guides the creation of high-quality, finished cyber threat intelligence reports. It tails content for specific audiences—from C-suite executives (strategic risk) to SOC analysts (tactical IOCs). Use it when synthesizing raw data into actionable intelligence products, generating threat briefings, or conducting post-incident assessments, ensuring adherence to industry standards like TLP and NIST.

This tool provides comprehensive network traffic analysis capabilities by querying the Arkime API. Users can search sessions, download PCAPs for forensics, detect sophisticated threats like C2 beaconing (via jitter/interval analysis), spot DNS tunneling patterns, and flag connections to known-bad TLS certificate issuers. Ideal for security assessment and incident investigation.

Conducts comprehensive, sector-specific threat landscape assessments by profiling key threat actors, mapping attack vectors, and detailing associated MITRE ATT&CK TTPs (covering financial, healthcare, energy, etc.). Utilizing sophisticated data analysis via Python stacks and integrating real-time threat intelligence feeds (ISAC, CVEs), this tool generates highly actionable intelligence for risk management, security investment prioritization, and high-level board-level reporting on industry exposure.

A comprehensive expert prompt for evaluating Power BI data models. It guides the assessment of model architecture (Star Schema, relationships), storage optimization (Import, DirectQuery, Dual), data quality, performance scalability, and governance best practices. Use this when reviewing an existing BI model to ensure it is robust, maintainable, and highly performant.

Provide qualitative, evidence-traceable developmental review of scholarly works and audit low-stakes research-assessment rubrics with local quality controls. Not for ranking people or high-stakes decisions.

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.