Skill UI

Automate the testing and validation of Clari export pipelines within a Continuous Integration/Continuous Deployment (CI/CD) environment. This tool helps developers ensure API connectivity, validate export schemas, and systematically test the reliability of Clari integrations, preventing deployment issues before they reach production.

This tool gathers comprehensive diagnostic information from the Clari API, including connectivity status, recent forecast lists, job history, and environment details. It is essential for users preparing support tickets, debugging integration issues, or providing comprehensive samples to technical support teams. All sensitive data is automatically redacted.

A collection of production-ready client implementation patterns for interacting with the Clari v4 API, provided in both Python and TypeScript. This guide covers essential functionalities like listing and exporting forecast data, implementing job polling, and managing complex data transformation pipelines, ensuring reliable and reusable integration for development teams.

A comprehensive guide on deploying applications connected to ClickHouse Cloud across various modern cloud environments, including Vercel, Fly.io, and Google Cloud Run. This guide covers best practices for connection pooling, secure secret management, implementing health checks, and ensuring graceful shutdowns in serverless and containerized setups.

This bundle collects comprehensive diagnostic information for troubleshooting ClickUp API v2 issues. It generates a redacted, safe bundle containing authentication status, rate limit details, workspace enumeration, and API latency measurements. Use this when preparing support tickets or investigating persistent connectivity problems.

A comprehensive, production-ready patterns library for interacting with the ClickUp API v2. It provides typed wrappers, robust error handling, rate limit management, and implements singleton/multi-tenant support, making complex ClickUp integrations reliable and scalable in TypeScript projects.

This script automates the collection of comprehensive diagnostic evidence for Cohere API v2 troubleshooting. It gathers environment details (Node/Python versions), SDK versions, API connectivity tests, and detailed request/response logs, packaging everything into a single, support-ready bundle for efficient issue resolution.

Automate the entire deployment lifecycle for ML inference services on CoreWeave GPU cloud. This workflow integrates unit testing, container image building (to GHCR), and rolling deployment to CoreWeave Kubernetes clusters via GitHub Actions. Ideal for ensuring stable, high-performance deployment of GPU-dependent models. Key features include validating GPU manifest requests and managing deployments using standard Kubernetes APIs.

This skill provides comprehensive tools and best practices for interacting with Amazon Aurora DSQL, a PostgreSQL-compatible distributed SQL database. It covers schema management, secure query execution, multi-tenant architecture implementation, and safe data migration using MCP tools and CLI scripts. Ideal for building scalable, distributed applications.

This skill provides a comprehensive guide and implementation for deploying a containerized Fathom AI meeting service. It is designed to handle the processing of meeting transcripts, summaries, and action items via webhooks. The solution includes Docker setup, environment variable management, robust health checks, and detailed steps for implementing rolling updates, ensuring continuous and reliable meeting data synchronization.

A foundational guide to interacting with the Fathom API. This skill demonstrates essential use cases, including listing meetings, fetching detailed transcripts, and retrieving AI-generated summaries and action items. It is ideal for initial API testing, validating connectivity, or understanding the Fathom data response structure.

This setup provides a local development loop for integrating and testing Fathom API functionalities. It utilizes mock meeting and transcript data, making it ideal for building meeting analytics tools, simulating webhook handlers, or iterating on complex transcript processing pipelines without requiring live API calls. It ensures a robust environment for isolated development testing.