Skill UI

This SDK provides comprehensive Python support for Azure Data Lake Storage Gen2. It enables developers to interact with hierarchical file systems, performing essential big data operations such as creating, listing, uploading, downloading, and managing metadata for files and directories. Ideal for building data analytics pipelines and cloud-based data processing workflows.

Automates Big Data Cloud operations through Composio’s toolkit by routing discovery, connection checks, and multi-tool execution via Rube MCP commands so you always work with current schemas before running workflows.

Automates guidance for setting up and optimizing BigQuery scheduled queries within GCP, offering best practices, configuration templates, and validation for production-ready data workflows.

Provides comprehensive patterns for data synchronization, ETL processes, and data migration specifically for MaintainX. Use this when needing to keep data consistent between MaintainX and external databases, data warehouses (like BigQuery), or when performing bulk data exports to formats like CSV. It covers incremental syncing, full exports, and data reconciliation checks.

This deep dive guide provides comprehensive strategies and detailed checklists for migrating to the OpenEvidence platform. It covers various migration methods, such as parallel run, Strangler fig, and Big bang approaches. The guide assists technical teams in planning the transition by addressing key areas including API mapping, data migration plans, rollback procedures, and performance baselines, ensuring a secure and smooth transition for healthcare IT systems.

A comprehensive skill set for mastering enterprise-grade Scala development. Expertise covers functional programming, distributed systems, and big data processing using technologies like Pekko, Akka, Spark, ZIO, and Cats Effect. Ideal for designing and implementing resilient, scalable microservices based on Domain-Driven Design principles.

Guides building, tuning, and validating production Apache Spark jobs, covering DataFrame/RDD choices, partitioning, broadcast joins, skew handling, caching, and cluster configuration for big data pipelines.

This skill enforces an algorithm-first discipline, requiring the user to state the time and space complexity (Big-O), the intended data structure, and the core algorithm family before writing any complex code (loops, queries, recursion). It serves as a critical gatekeeper to prevent common performance pitfalls like O(n²) complexity, N+1 database queries, and brute-force implementation errors, significantly improving code robustness and efficiency.

Aria functions as a System Architect, responsible for establishing the definitive structural foundation of the entire system. She designs comprehensive blueprints covering the data model (schema, relationships, constraints), API contract specifications (endpoints, auth, pagination), modular file structure, and selection of core architectural design patterns. Her output ensures that no code is written without a rigorously defined, approved architectural plan, minimizing ambiguity and technical debt.

This skill guides you through a comprehensive, multi-phase interview to capture every necessary detail of a new project idea. It is designed to run BEFORE any code is written, forcing detailed specification gathering across purpose, features, data models, and technical constraints. The output is a clean, self-contained prompt.md file, ensuring subsequent development is based on solid, unambiguous requirements and preventing costly mistakes.

This skill is a comprehensive tool for managing and understanding SQL queries. It can explain complex SQL in plain English for non-technical stakeholders, optimize slow queries by identifying performance bottlenecks, generate functional SQL code from natural language prompts, and produce detailed query documentation and data dictionaries. Supports major dialects including PostgreSQL, MySQL, and BigQuery.