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.

A comprehensive, multi-phase workflow designed for creating production-ready Bash scripts. This guide covers the entire development lifecycle, including defensive pattern implementation, structured error handling (traps, retry logic), logging strategies, rigorous unit testing using Bats, and professional documentation. Ideal for system administration, CI/CD automation, and core DevOps scripting.

A comprehensive guide to building robust, production-ready GraphQL APIs. This skill covers schema design (SDL/code-first), implementing efficient resolvers with DataLoader for batching, handling real-time subscriptions via WebSockets, and integrating field-level authorization and complexity limiting. Supports major runtimes like Node.js and Python.

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 comprehensive template provides a production-grade reference architecture for CodeRabbit AI code reviews. It is designed to guide teams in establishing rigorous coding standards by defining specific, best-practice instructions for various layers (API, Database, Authentication, Frontend, CI/CD, Infrastructure). Use this as a robust starting point to build a comprehensive, automated, and secure code quality review process.

Contract Test Creator automatically assists with designing and implementing contract tests, guiding on best practices, producing production-ready code and configurations, and validating results whenever the user invokes contract test creator tasks.

Provides automated guidance for designing and implementing cron job schedulers in backend projects, covering best practices, production-ready code, and validation for node.js, Python, Go, databases, and microservices patterns.

A comprehensive, step-by-step checklist and audit script designed for validating Customer.io integrations before going live. It covers credential verification, email deliverability setup (SPF, DKIM, DMARC), API connectivity smoke tests, campaign readiness, and setting up operational monitoring alerts for a smooth, reliable production launch.

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.

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 checklist and guide for deploying Deepgram integrations into a production environment. It covers critical areas including robust authentication practices, system resilience design (e.g., backoff strategies, circuit breakers), performance optimization (singleton clients, audio preprocessing), security measures (PII redaction), and mandatory monitoring setup (Prometheus metrics and alert rules). Essential for any go-live phase.

Provides reference architectures for building high-scale, reliable transcription systems using Deepgram. It covers four main patterns: synchronous REST for short files, async queues (BullMQ) for batch processing, WebSocket for real-time streaming, and a hybrid router for mixed workloads. Use this when designing production-grade audio processing pipelines.