Skill UI

Automates Customgpt tasks through Rube MCP by discovering tool schemas with RUBE_SEARCH_TOOLS, managing toolkit connections, and executing workflows via RUBE_MULTI_EXECUTE_TOOL.

Guide for automating Customjs tasks through Composio’s toolkit using the Rube MCP interface, covering connection checks, tool discovery, execution calls, and schema compliance while emphasizing repeated tool searches.

Automates Cutt Ly operations by orchestrating Composio toolkits through the Rube MCP interface, ensuring you always discover current schemas, manage connections, and execute compliant workflows for bulk or single tasks.

Defines how to automate Dadata Ru operations through Composio’s Rube MCP, covering prerequisite connection checks, schema-aware tool discovery, execution patterns, and common pitfalls so agents can run reliable workflows with updated tool interfaces.

Guides you through building Dagster data pipelines with best-practice advice, ready-to-use configurations, and validation checks for ETL, transformation, orchestration, and streaming workflows whenever the Dagster pipeline creator skill is activated.

Automates guidance for data catalog updater tasks, covering ETL, transformation, orchestration, and streaming workflows to keep pipeline metadata accurate.

A comprehensive, end-to-end workflow for building product features guided by rigorous data insights. This skill guides users through the entire lifecycle, encompassing exploratory data analysis, forming measurable business hypotheses, designing statistical A/B tests, architecting data pipelines, and implementing robust backend/frontend instrumentation. It ensures that every feature iteration is validated by data and measured for impact.

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.

Guides engineers through data partitioner setups within ETL workflows, offering best practice advice, ready-to-run code, and validation for streaming and batch pipelines.

Automates the data story outlining process for analytic workflows, offering guidance on SQL, visualization, statistics, and BI so teams can structure insights consistently.

This comprehensive workflow guides the entire database lifecycle, from initial architecture design (covering both SQL and NoSQL) to advanced implementation, optimization, and maintenance. It covers crucial stages like schema design, implementing migrations, optimizing query performance, developing robust data pipelines (using tools like Airflow and dbt), and managing data quality and operations. Ideal for engineers building complex, production-grade data systems.

A comprehensive, expert-level skill for designing, analyzing, and optimizing robust database schemas. It covers normalization, index tuning, choosing between SQL/NoSQL, and implementing zero-downtime data migrations. Provides systematic workflows for schema analysis, performance modeling, and advanced SQL pattern generation.