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Automates the creation of Airflow DAGs for ETL and streaming data workflows, offering best-practice guidance, production-ready code samples, and validation against common pipeline standards.

A comprehensive guide to building production-ready Apache Airflow Directed Acyclic Graphs (DAGs). This skill covers best practices for operators, sensors, testing, deployment, and designing robust data pipelines. Use this when orchestrating complex workflows, managing ETL processes, or ensuring reliable batch job execution in a production environment.

Guides you through building Airflow operators for data pipelines with automated best practices, production-ready code/config generation, and validation for ETL, transformation, orchestration, and streaming scenarios.

Automates API Labz operations through Composio’s toolkit using the Rube MCP pipeline, guiding you to search for current schemas, manage connections, and run discovery, check, execute, and bulk workflows safely.

Streamline Apitemplate IO tasks by connecting Composio’s toolkit through Rube MCP, always running RUBE_SEARCH_TOOLS to fetch current schemas, validating the Apitemplate IO connection, and executing workflows with RUBE_MULTI_EXECUTE_TOOL.

Drive Apollo.io prospecting by issuing natural language commands to search organizations, discover contacts, enrich records, manage pipeline stages, and build outreach lists via the Composio MCP integration.

Configures a robust CI/CD pipeline for Apollo.io integrations using GitHub Actions. It implements multi-stage testing, including unit tests (using MSW mocks for zero API calls), live integration tests (gated to main branch), and secret scanning. Ensures reliable and safe deployment practices for SaaS applications.

This skill implements a comprehensive, multi-step workflow for lead generation using Apollo.io. It allows users to perform free searches for contacts or organizations based on detailed criteria (e.g., domain, title, industry). Crucially, it integrates paid enrichment steps to verify and retrieve critical contact details like emails and phone numbers, building a complete, actionable prospecting pipeline.

A comprehensive guide for deploying Apollo.io integrations to production environments. This skill covers robust deployment strategies across multiple cloud platforms, including Vercel, GCP Cloud Run, and Kubernetes. It emphasizes best practices such as implementing health check endpoints, managing secrets using dedicated secret managers, and structuring CI/CD pipelines for reliable, scalable, and secure production rollouts.

This comprehensive guide sets up a robust and isolated local development environment for Apollo.io integrations. It covers essential steps including configuring sandbox API keys, implementing a Mock Service Worker (MSW) for reliable offline API mocking, setting up detailed request logging, and configuring Vitest for efficient local testing. Ideal for developers building and debugging complex, API-dependent features.

This comprehensive skill guides the systematic optimization of end-to-end application performance across the entire stack. It covers establishing performance baselines through deep profiling (CPU, Memory, I/O), assessing observability gaps, optimizing databases, tuning backend services and APIs, and enhancing frontend rendering. Ideal for complex, scalable applications that require measurable performance improvements, reliability enhancements, and adherence to modern user experience standards.

This comprehensive skill guides the systematic optimization of end-to-end application performance across the entire stack. It covers establishing performance baselines through deep profiling (CPU, Memory, I/O), assessing observability gaps, optimizing databases, tuning backend services and APIs, and enhancing frontend rendering. Ideal for complex, scalable applications that require measurable performance improvements, reliability enhancements, and adherence to modern user experience standards.