Skill UI

This expert skill guides advanced integration with Atlassian products (Jira and Confluence) using the MCP protocol. It covers full lifecycle management, including setting up OAuth/API token authentication, designing complex JQL/CQL queries, automating sprint workflows, syncing documentation, and robust debugging of API calls. Ideal for system architects and developers building cohesive enterprise workflows.

This expert skill guides advanced integration with Atlassian products (Jira and Confluence) using the MCP protocol. It covers full lifecycle management, including setting up OAuth/API token authentication, designing complex JQL/CQL queries, automating sprint workflows, syncing documentation, and robust debugging of API calls. Ideal for system architects and developers building cohesive enterprise workflows.

A comprehensive template for developing modern, full-stack applications. This guide covers architecture overview, file structure, and best-practice code patterns for advanced technology stacks including Next.js, FastAPI, Supabase, and structured AI integration using Claude API. It serves as a robust blueprint for professional development teams.

This skill details the architecture and implementation of a robust API Gateway, serving as the single entry point for multiple backend microservices. It centrally manages critical cross-cutting concerns, including path-based and header-based routing, JWT/OAuth2 authentication, rate limiting, load balancing, and circuit breaker protection. This pattern is essential for building resilient, scalable, and maintainable microservices architectures, significantly simplifying client integration and request management.

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 guide details the complete setup process for integrating with the Clay data enrichment platform. It covers obtaining the Enterprise API key, configuring webhook endpoints for data ingestion, and connecting third-party data providers (like Apollo or Clearbit). Use this when onboarding, setting up automated data pipelines, or maximizing credit savings through programmatic integration.

This guide provides production-ready patterns for building robust integrations with the Clay platform. It covers interacting with Clay via webhooks (inbound data), HTTP API enrichment columns (outbound data), and the Enterprise API. Implementation examples are provided in TypeScript and Python, ensuring reliable, reusable, and scalable data pipeline construction.

This guide details security best practices for integrating with Clay. It covers securing API keys, validating webhook signatures, isolating provider credentials, and redacting sensitive PII data. Essential for maintaining compliance and data integrity in production environments.

A comprehensive guide and implementation framework for managing real-time data flow using Clay's event-driven architecture. This skill covers both inbound webhooks (POSTing data into Clay tables) and outbound HTTP API callbacks (receiving enriched data from Clay). It provides production-ready TypeScript code for setup, signature verification, and idempotent processing, enabling robust, event-driven integrations.

A comprehensive guide demonstrating how to implement robust authentication using Clerk across various modern web environments, including Next.js Server Components, Client Components, API routes, and Server Actions. Learn best practices for securing endpoints, managing session data, and handling authenticated requests from end-to-end.

A comprehensive guide for designing production-grade lead enrichment pipelines in Clay. Covers three integration patterns (Webhook, API), detailed table schema design, advanced data waterfall logic, implementing complex ICP scoring formulas, and setting up robust CRM synchronization flows for go-to-market data operations.

This skill guides the comprehensive, multi-step rollout of CodeRabbit AI code review across an entire organization. It covers setting organization-level defaults, customizing team-specific review rules (e.g., API security, frontend performance), and automating deployment via multi-repo scripts and branch protection enforcement. Use when establishing standardized, high-quality AI code review practices company-wide.