Skill UI

A comprehensive reference architecture for building scalable, cost-effective, and robust AI services. This system manages the full AI lifecycle, including intelligent model routing (for quality/cost trade-offs), response caching (using Redis), asynchronous batch processing, and fine-tuning pipeline management via Together AI's OpenAI-compatible API. Ideal for enterprise applications requiring high availability across multiple open-source models.

A comprehensive guide to implementing production-ready patterns for interacting with the Together AI API. This includes a singleton client for seamless OpenAI-compatible integration, robust error wrappers with retry logic, and a fluent request builder. It covers best practices for LLM inference, model setup, and handling diverse response types (chat, embedding, fine-tuning).

This comprehensive guide serves as a checklist for interacting with Veeva Vault in a production environment. It details best practices for using the REST API, executing complex VQL queries, and integrating with the VAPIL Java SDK. Coverage includes authentication flows, common data patterns, document lifecycle management, and essential error handling procedures for life sciences and CRM operations.

A comprehensive guide and workflow for deploying static websites (e.g., Vue, React, Angular, Hugo, Jekyll) from a local environment to a production server using VSCode SFTP. This skill covers setting up secure SFTP connections, generating production-ready Nginx configurations (including security headers, caching, and HTTPS redirects), and providing a complete deployment checklist for smooth CI/CD-like workflows.

Configure secure and isolated Webflow integrations across development, staging, and production environments. This guide details how to manage separate API tokens, Site IDs, and secure secrets using industry-standard secret managers like HashiCorp Vault, AWS Secrets Manager, and GCP Secret Manager, ensuring data integrity and reliable deployment in a CI/CD pipeline.

Implement a comprehensive observability stack for Webflow Data API v2 integrations. This skill provides structured code using Prometheus metrics, OpenTelemetry distributed tracing, and structured logging (pino) to monitor API call frequency, latency, error rates, and rate limit usage. Ideal for developers building robust, production-grade Webflow-connected SaaS applications that require deep performance insights and reliable alerting.

Provides a comprehensive checklist and technical guidelines for safely deploying Webflow Data API integrations to a production environment. Covers critical areas like token security, rate limit management, implementing circuit breakers, setting up health checks, and handling various API errors to ensure reliable, high-availability service.

Provides a comprehensive, layered reference architecture for building production-grade integrations with Webflow's Data API v2. This guide separates concerns into distinct layers: API access, business logic (CMS, e-commerce), webhook handling, and caching, ensuring scalability and maintainability for complex web applications.

A comprehensive guide to implementing production-ready patterns for the Webflow SDK. Covers essential architectural patterns such as singleton client management, robust typed error handling (including specific HTTP status codes like 401, 403, 429), efficient pagination helpers, rate limit monitoring via raw response access, and multi-tenant client factory setup. Essential for building scalable, enterprise-grade Webflow integrations.

This skill provides a powerful mechanism for modifying and extending AWS infrastructure using Pulumi handlers and dedicated declarative components. It allows developers to manage complex cloud setups, including configuring OpenSearch, VPC networking, resource tagging, custom domains, blue-green deployment strategies, and implementing environment-conditional configurations (e.g., production vs. development).

This comprehensive checklist provides guidance for integrating the Wispr Flow voice-to-text API into a production environment. It covers best practices for both WebSocket and REST API usage, addressing critical elements like authentication, robust error handling (e.g., 401 Unauthorized or network disconnections), and optimizing performance. It is essential for building reliable, voice-powered applications, especially those handling complex contexts like programming code and CLI commands.

This comprehensive checklist provides guidance for integrating Workhuman Social Recognition and its rewards API into production environments. It covers essential API concepts, including OAuth 2.0 authentication, peer-to-peer recognition workflows, configurable award levels, and bidirectional synchronization with major HRIS systems (e.g., Workday, SAP). Use this resource when building robust and scalable employee recognition or reward management systems.