Skill UI

This skill provides a comprehensive guide for deploying LangChain chains and agents into production-grade APIs. It supports multiple development stacks, including Python (LangServe/FastAPI) and Node.js (Express). Topics covered include containerization using Docker, setting up robust health checks, and deploying to major cloud platforms like Google Cloud Run and AWS Lambda. Learn how to build scalable, observable, and enterprise-grade API endpoints for advanced LLM applications.

Master the configuration of Langfuse webhooks to capture crucial prompt lifecycle events (Created, Updated, Deleted). This skill guides you through building a secure endpoint to intercept these events, enabling powerful, automated integrations. Use cases include triggering CI/CD pipelines upon production prompt changes, syncing data to external systems, or notifying teams via Slack.

Automates Leiga operations via Rube MCP by discovering the latest tool schemas, validating toolkit connections, and executing multi-step commands through Composio endpoints before running workflows.

This comprehensive guide details the end-to-end setup process for integrating Lindy AI into external applications. Learn how to obtain and manage API keys, install and initialize SDKs (Python/Node.js), and securely configure webhook authentication endpoints to enable programmatic access and trigger AI agents.

A comprehensive guide for setting up a local development loop to test AI agent integrations. This skill teaches developers how to build and debug webhook receivers, callback handlers, and associated application code that interacts with a cloud-hosted AI agent (like Lindy). It requires using tunneling services (e.g., ngrok) to expose local endpoints for receiving webhooks and simulating the entire agent-to-application data flow.

A comprehensive guide and implementation using TypeScript to establish production-grade observability for Linear API integrations. This includes defining Prometheus metrics (tracking latency, error rates, rate limits, and webhooks), implementing structured logging (using pino), and setting up robust health check endpoints. It ensures full visibility into API performance and system health, critical for mission-critical SaaS applications.

This skill guides developers through setting up and processing Lokalise webhooks for real-time content synchronization. It covers the API integration steps to register webhook endpoints, handling various translation lifecycle events (key creation, translation updates, file imports), and implementing secure payload verification using webhook secrets. It demonstrates building robust, asynchronous event handlers in Node.js/Express, perfect for automating workflows based on content changes in a SaaS environment.

A comprehensive debugging toolkit designed for diagnosing complex issues within MaintainX integrations. It includes environment diagnostics, detailed request/response logging (using interceptors), and robust health checks for multiple core API endpoints. Use this when troubleshooting connectivity, data integrity, or unexpected API behavior.

This skill provides a comprehensive guide to implementing observability for MaintainX API integrations. It covers best practices for structured logging, Prometheus metrics collection (Counters, Histograms, Gauges), API request tracing using Axios interceptors, and setting up health and alerting endpoints. Use this when you need to monitor API reliability, detect performance degradation, and ensure rapid issue detection in your connected services.

Defines MCP server tooling with file search, query execution, resource endpoints, prompt templates, and transport configurations alongside a client setup example for streamlined project automation.

This comprehensive checklist guides the safe and robust deployment of Mistral AI integrations to a production environment. It covers critical operational steps, including secure credential management, rigorous code quality gates, establishing health endpoints, implementing circuit breakers for resilience, executing gradual rollouts, and defining emergency rollback procedures to ensure system stability and high availability.

This bundle collects comprehensive diagnostic evidence from the OpenEvidence clinical decision support API. It validates API credentials, checks query endpoint health, retrieves evidence citations, and captures model metadata. Use it to diagnose complex issues like query failures, missing references, or high latency without needing direct dashboard access.