Skill UI

This guide provides comprehensive documentation and best practices for interacting with the Veeva Vault platform. It covers REST API usage, writing effective VQL (Vault Query Language) queries, and utilizing the VAPIL Java SDK. It also details common error handling procedures and addresses rate limit guidance for developers working in life sciences and CRM environments.

This guide provides comprehensive reference architecture for integrating with Veeva Vault, covering REST APIs, VQL query language, and VAPIL Java SDK. It details key concepts like authentication, common data patterns, and error handling, making it essential for developers working on life sciences or CRM solutions built on the Vault platform.

Comprehensive guidance for developers integrating with Veeva Vault. This documentation covers best practices for utilizing the Veeva Vault REST API, executing VQL queries, and leveraging the VAPIL Java SDK. Essential for managing document lifecycles and performing CRUD operations within enterprise life sciences and CRM environments.

This guide provides comprehensive instructions for upgrading and migrating systems within Veeva Vault. It details the use of the REST API, advanced VQL queries (SQL-like), and the VAPIL Java SDK. It is essential for professionals managing document workflows and clinical operations in the life sciences and CRM domains.

A comprehensive resource hub for ML researchers working in scientific domains such as biology, chemistry, genetics, and medicine. It provides a curated catalog of high-signal datasets, pre-trained models, and interactive demos, streamlining the discovery and use of specialized AI/ML resources beyond general search.

This skill provides comprehensive tools and methodologies for working with the Brain Imaging Data Structure (BIDS) standard. It is essential for organizing, validating, querying, and converting complex multi-modal neuroscience and biomedical datasets (including MRI, EEG, MEG, PET, etc.). Use this when setting up BIDS-compliant directory structures, ensuring data integrity before publication, or converting raw DICOM scans into standardized formats.

This skill converts complex, narrative technical documents, research excerpts, or natural language problem descriptions into a highly structured Mathematical Problem Specification (MPS). It systematically extracts variables, constraints, objectives, and uncertainty parameters. By adhering to a strict Zero-Inference Protocol, it ensures all extracted elements are strictly grounded in the source text, making it invaluable for formalizing real-world optimization, data science, and engineering problems.

This meta-skill guides guardians and children through planning educational projects, including science fair entries, DIY kits, and school assignments. It assesses feasibility based on age and budget, generates age-appropriate step-by-step plans, advises on material substitutes, and crucially, surfaces safety considerations and parent-facing learning objectives.

A specialized tool for scientific data visualization, acting as a visualization advisor to analyze data, recommend chart types, prevent common errors, and generate publication-grade figures.