Skill UI

A comprehensive checklist for ensuring any Evernote integration is production-ready. It covers critical operational aspects including API key management, security hardening (encryption, sanitization), rate limit handling, robust monitoring setup, and post-deployment verification steps. Use this guide when deploying or auditing a live Evernote connection.

A comprehensive guide providing production-ready architectural patterns for building scalable, maintainable, and reliable integrations with Evernote. This skill covers microservices design, multi-level caching strategies (e.g., Redis), robust synchronization processes using webhooks and message queues, and establishing data mirroring schemas for complex SaaS applications.

A comprehensive guide detailing production-ready best practices for interacting with the Evernote SDK. Covers advanced topics such as efficient search using NoteFilter, handling attachments via MD5 hashing, robust error management (rate limiting, specific exceptions), optimized batch processing, and idempotent tag/notebook management for complex applications.

This comprehensive guide provides detailed steps for upgrading Evernote SDK versions. It specifically addresses common breaking changes, such as converting legacy callback-based API calls to modern Promise/async-await patterns. It also demonstrates how to build compatibility layers for seamless, gradual migration in existing production applications.

A comprehensive guide for deploying Exa-powered search APIs to production environments. This skill covers best practices for integrating Exa into Vercel Edge Functions, Docker containers, and Google Cloud Run. It includes detailed steps for secret management, implementing Redis caching for performance, and setting up health check endpoints, ensuring a robust and scalable production search solution.

This guide details how to configure and manage the Exa search API across development, staging, and production environments. It ensures API key isolation, implements environment-specific search limits, and provides strategies for cost control and performance optimization by utilizing caching layers like Redis. Essential for scalable, multi-stage deployments.

A comprehensive guide and code implementation for setting up observability, metrics, and alerting for Exa search integrations. This skill tracks crucial KPIs such as search latency (P50/P95), error rates, result usage, and cache hit ratios. It is essential for monitoring search quality, debugging performance bottlenecks, and managing API resource usage in production environments.

This guide provides advanced technical patterns for optimizing Exa API performance in production workloads. It covers critical strategies such as selecting the optimal search type based on latency budgets (e.g., instant vs. neural), implementing robust result caching using LRU, minimizing content retrieval size, and executing parallel queries to maximize throughput. Essential for building reliable, low-latency, and cost-effective search integrations.

A comprehensive checklist guiding the full lifecycle deployment of Exa search integrations to a production environment. It covers critical stages including pre-deployment security audits, code quality verification, performance baselines, monitoring setup, and emergency rollback procedures. Use this guide when preparing for a major launch or verifying production readiness.

This skill provides the production-ready reference architecture for integrating Exa into complex applications. It covers advanced search pipelines, RAG implementation for context generation, and structured content discovery. Use this to design new Exa integrations, review project structures, or establish industry-standard best practices for neural search systems.

This skill provides robust, production-grade patterns for building fault-tolerant search service integrations, specifically targeting Exa. It covers implementing query fallback chains, circuit breakers to prevent cascading failures, exponential backoff for retries, and graceful degradation levels. Use this when designing mission-critical search features that must remain available and functional even if underlying services fail, rate limit, or suffer performance degradation.

A comprehensive guide to implementing production-ready patterns for the Exa-js SDK. Covers critical architectural concerns such as client singletons, type-safe wrapper functions, advanced error handling, exponential backoff retry logic, and robust response validation using Zod. Use this when integrating Exa APIs into large-scale applications or establishing team coding standards for maximum stability and maintainability.