Skill UI

This guide provides comprehensive patterns and best practices for working with ClickHouse, a high-performance OLAP database. It covers advanced topics such as MergeTree engine design, efficient query optimization (filtering, aggregations, window functions), bulk/streaming data ingestion, materialized view creation, and performance monitoring techniques, ensuring optimal performance for large-scale analytical workloads.

A mandatory architectural guide for developing production-ready MCP servers using the mcp-use framework. It provides comprehensive patterns for implementing server tools, managing data resources, and integrating advanced authentication flows (OAuth, Auth0, Clerk, etc.). Always consult this guide before making any structural changes.

Provides GitHub Actions and GitLab CI pipeline templates with lint, test, and deploy stages, reusable setup actions, matrix strategies, and anti-pattern checklists for reliable automation.

This skill functions as an expert in workflow automation, specializing in designing and implementing robust CI/CD pipelines and GitHub Actions workflows. It guides users through automating the entire development lifecycle—from building and testing to secure deployment. By establishing clear stages, handling secrets, and defining rollback strategies, it ensures consistency, reduces manual effort, and accelerates delivery while maintaining high quality and security standards.

Automate CircleCI CI/CD workflows via Composio’s CircleCI toolkit over Rube MCP: trigger pipelines, monitor workflows and jobs, fetch artifacts, and review test metadata while adhering to required tool schemas and authentication flows.

Automates circuit breaker setup inside API integrations, triggering whenever you ask about patterns or best practices, then guiding through code, validation, webhooks, and SDK-related configurations.

This skill provides comprehensive guidance on leveraging d3.js (Data-Driven Documents) to create sophisticated, interactive, and publication-quality data visualizations. It covers core concepts like data binding, implementing various chart types (network graphs, geo-maps, etc.), handling complex transitions, and ensuring responsiveness across modern JavaScript frameworks (React, Vue, Vanilla JS). Learn the standard workflow for scale definition, axis creation, and drawing custom visual elements with fine-grained control.

Diagnose and fix Claude in Chrome MCP extension connectivity hiccups on macOS by toggling native messaging hosts, inspecting sockets, and running the provided toggle script whenever Claude Code CLI or Claude.app Cowork tools report “Browser extension is not connected” or behave erratically.

Provides deep, advanced debugging techniques for complex data enrichment failures within the Clay platform. This guide helps isolate root causes related to provider degradation, data flow errors, and API column issues when standard troubleshooting methods fail. It covers layer testing (Webhook, API), error pattern analysis, and local API replication, enabling users to diagnose deep system issues.

This guide outlines three robust architectural patterns (Direct, Standard, Queue-Based) for integrating and enriching data using the Clay SaaS platform. It helps users select the appropriate design—from simple, ad-hoc integrations to complex, enterprise-scale pipelines—by considering data volume, latency, and required automation level for optimal data flow.

This guide details setting up robust CI/CD pipelines for applications utilizing Clay. It covers automated unit and integration testing for webhook handlers, validating data schema compliance, and ensuring the reliability of data enrichment processes within your build workflow. Ideal for teams deploying webhooks or complex data transformation logic.

This guide details advanced strategies for optimizing and reducing data enrichment spending on platforms like Clay. Techniques include connecting private API keys (for significant savings), optimizing multi-step data pipelines (waterfalls), pre-filtering raw input data to prevent wasted credits, and implementing comprehensive budget monitoring. Ideal for professionals managing high-volume, cost-sensitive data pipelines.