Skill UI

Utilizes the idc-index package to query and download large-scale, public cancer imaging datasets from the NCI Imaging Data Commons. This skill allows users to select image subsets based on diverse metadata (e.g., cancer type, modality, anatomical site) and download raw DICOM files for advanced AI training, medical research, and visualization. No authentication is required for data access.

This skill guides the systematic process of conducting comprehensive literature reviews across multiple academic databases (e.g., PubMed, arXiv, Semantic Scholar). It supports meta-analyses, scoping reviews, and state-of-the-art investigations. The rigorous workflow includes structured searching, data extraction, citation verification, thematic synthesis, and generating publication-quality reports (PDF/Markdown) complete with mandatory scientific schematics (like PRISMA flow diagrams) to ensure academic rigor and reproducibility.

This skill provides comprehensive patterns for extracting and transforming Navan booking and transaction data. It addresses complex data pipeline challenges such as API pagination, date range chunking, and UUID-based deduplication. It supports both direct REST API implementation (via code examples) and configuration for managed connectors like Fivetran and Airbyte. Ideal for populating data warehouses, building robust analytics dashboards, or ensuring data quality from Navan sources.

A comprehensive guide for migrating data to, from, and between Notion workspaces. This skill covers complex data pipelines, including rate-limited bulk imports (CSV/JSON), full database exports with pagination, cross-database syncing, and data transformation patterns for integrating content from sources like Confluence and Google Docs. Essential for building robust Notion ETL workflows.

This guide provides comprehensive technical instructions for optimizing Palantir Foundry costs. Learn to use incremental transforms to drastically reduce compute rebuilds, right-size Spark profiles based on data volume, and migrate from expensive API polling to efficient, event-driven webhooks, ensuring both cost efficiency and system stability.

This comprehensive guide details the process of implementing a secure and robust system for handling Palantir Foundry webhook events. It covers key steps including API-based webhook registration, mandatory signature verification with replay protection, sophisticated event routing for various object lifecycles (create, update, delete), and ensuring idempotent processing using caching mechanisms like Redis. Use this when external microservices must react reliably and immediately to changes within the Foundry Ontology or data assets.

A comprehensive toolkit for advanced web intelligence workflows. It facilitates deep research, structured data enrichment, URL extraction, entity discovery, and continuous web monitoring. Ideal for scientific topics, academic source discovery, and generating exhaustive, evidence-based reports.

Provides a systematic guide for diagnosing and improving poor search quality in vector databases like Qdrant. This guide covers troubleshooting issues such as low recall, when approximate search degrades, selecting optimal embedding models, and correctly tuning HNSW parameters, quantization, and filtering strategies. Essential for optimizing RAG and semantic search pipelines.

A comprehensive guide detailing the process of migrating data warehouses to Snowflake from major sources like Amazon Redshift, Google BigQuery, or on-premise databases. This resource covers critical steps including schema conversion (handling dialect differences like STRUCT/ARRAY to VARIANT), robust data transfer methods (S3/Cloud Storage, Python/Pandas), data validation techniques (checksums, row counts), and essential SQL syntax translation patterns.

A comprehensive guide to implementing production-grade reliability patterns for Snowflake environments. Covers advanced techniques like Time Travel for point-in-time recovery, cross-region database replication, account failover groups for disaster recovery, and application-level resilience coding (e.g., connection failover logic). Essential for building fault-tolerant, highly available data pipelines.

This skill performs a structured Systematic Literature Review (SLR) by analyzing multiple academic papers on a given topic. It searches academic databases (like arXiv), extracts structured metadata (research questions, methodologies, key findings, limitations) from the entire set of papers, and synthesizes overarching themes and research trends. It is ideal for creating comprehensive literature surveys, annotated bibliographies, and cross-paper comparisons, outputting reports in professional citation formats like APA, IEEE, or BibTeX.

TileDB-VCF is a high-performance library for scalable storage and retrieval of genomic variant-call data (VCF/BCF). Built on TileDB's sparse array technology, it enables efficient ingestion of large datasets, supports incremental sample additions, and allows for highly optimized parallel queries across genomic regions and multiple samples. Ideal for building population genomics databases, cohort studies, and conducting large-scale association studies.