Skill UI

This skill defines the mandatory conventions and architectural rules for developing maintainable, cross-platform applications using Avalonia UI and the Zafiro toolkit. It enforces a functional-reactive MVVM approach, prioritizing explicit error handling via Result types, and mandates leveraging Zafiro's existing abstractions to ensure code quality and predictability.

Automates Basin toolkit operations via Rube MCP by discovering tools through RUBE_SEARCH_TOOLS, ensuring connections via RUBE_MANAGE_CONNECTIONS, and executing commands with RUBE_MULTI_EXECUTE_TOOL using schema-compliant arguments while managing session and memory expectations.

Guides creation of B2B cold outreach emails and follow-up sequences that read like a peer note, covering subject lines, hooks, proof points and single-ask CTAs for sales development reps.

This skill analyzes the predictable ways language models lose performance as context length increases. It details core patterns, including 'lost-in-middle,' context poisoning, and distraction. Use this knowledge to diagnose unpredictable agent failures, design highly reliable systems for long document processing, and implement advanced context engineering strategies.

Details how to research context, structure homepage or landing copy, and follow clarity/benefit-driven rules so every headline, CTA, and section pushes visitors toward a single conversion.

An expert in designing, implementing, and optimizing scalable, reliable, and cost-effective data pipelines for both batch and streaming data. Covers advanced topics including ETL/ELT patterns, Kappa/Lambda architectures, workflow orchestration (Airflow/Prefect), transformation using dbt/Spark, and managing modern storage formats like Delta Lake and Iceberg. Focuses heavily on data quality, monitoring, and cost optimization strategies.

This skill provides production patterns for implementing robust data quality validation using Great Expectations, dbt tests, and formal data contracts. It is essential for building reliable, automated, and verifiable data pipelines, ensuring data integrity throughout the entire ETL/ELT process, and establishing clear data governance rules.

This comprehensive guide details strategies for migrating enterprise data platforms to Databricks. It provides PySpark examples for discovery, schema mapping (converting types from Hadoop, Snowflake, etc.), and executing robust data transfer methods like SYNC, DEEP CLONE, and CTAS. Use this when moving data from legacy sources like Hadoop, Snowflake, or Redshift to a modern Delta Lake environment.

This comprehensive guide provides structured steps and code examples for upgrading Databricks Runtime versions and performing critical data migrations. It covers best practices for version compatibility checking, transitioning from Hive Metastore to Unity Catalog using methods like SYNC and CTAS, and updating deprecated API endpoints, ensuring a smooth platform evolution for data pipelines.

Guides Claude Code skill authors through designing and structuring workflow-based skills with numbered phases, decision routing, subagent delegation, and progressive disclosure so multi-step automations remain predictable and auditable.

Automates Docker Hub workflows through the Composio MCP integration, letting teams list organizations, create orgs and repositories, manage members and teams, and configure image-push webhooks for predictable deployments.

Documented workflow for orchestrating Extracta AI operations through Composio’s Rube MCP, emphasizing tool discovery, connection checks, and schema-compliant executions with RUBE_SEARCH_TOOLS and RUBE_MULTI_EXECUTE_TOOL calls.