Skill UI

Explains Fabric Lakehouse storage, data organization, security, shortcuts, and optimization practices so you can design, build, and monitor Lakehouse solutions leveraging Microsoft Fabric best practices.

This skill provides comprehensive automation for managing OneDrive file lifecycles. Users can perform advanced operations including searching across metadata and content, uploading and downloading files, organizing folders, creating share links, and granularly managing permissions for specific users. It utilizes a structured workflow approach via Rube MCP, making it ideal for automating business processes involving cloud document storage and collaboration.

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.

Automates Supabase projects by sequencing Composio Rube MCP workflows for database querying, schema inspection, SQL execution, project/org management, storage buckets, edge functions, and health monitoring while always refreshing tool schemas first.

Datamol is a high-level, Pythonic abstraction layer built over RDKit, designed for computational chemistry and drug discovery. It simplifies complex molecular operations, offering sensible defaults for tasks like SMILES standardization, descriptor calculation, fingerprint generation (ECFP4), 3D conformer analysis, and molecular clustering. It supports efficient parallel processing and cloud storage I/O, making it ideal for handling large-scale chemical datasets.

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.

Provides comprehensive programmatic control over Apify's core data infrastructure, including Datasets, Key-Value Stores, and Request Queues. This skill allows users to perform CRUD operations on various storage types, manage data persistence, and orchestrate complex, multi-stage data pipelines (e.g., scrape -> transform -> export). Ideal for building robust, end-to-end web scraping and data processing automation workflows.

This comprehensive guide outlines essential security best practices for users operating within the Apify ecosystem. Learn how to properly manage API tokens, implement environment separation (dev/staging/prod), secure proxy credentials, and sanitize sensitive data (PII) before storage. Essential for hardening data pipelines and ensuring compliance.

A comprehensive guide to reducing expenses on ClickHouse Cloud. Learn advanced techniques for storage optimization (compression, TTL), compute resource tuning (scaling, thread limits), and query efficiency improvements. Use this when managing data budgets or analyzing high ClickHouse billing charges.

This reference architecture provides a blueprint for integrating Fathom meeting intelligence data into enterprise systems. It details the full data pipeline, spanning from initial Fathom recordings via webhooks to structured storage (PostgreSQL), action item extraction, and downstream synchronization with CRMs (like Salesforce/HubSpot) and email systems. Ideal for developers building automated, real-time business process workflows.

A comprehensive, production-ready reference architecture for building robust data scraping systems using Bright Data's full suite of tools (Web Unlocker, Scraping Browser, SERP API). This template provides best practices for project layout, managing proxies, designing data pipelines, and integrating scheduling/storage components in a Node.js/TypeScript environment.

This guide outlines best practices for securing your Clari integration. It covers secure API token management, emphasizing storage in secrets managers (like AWS Secrets Manager), and implementing robust PII redaction methods for exported forecast data to maintain data privacy and compliance.