Skill UI

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 guardrail system for external search APIs (like Exa). It enforces content safety policies, manages domain access via allow/blocklists, sanitizes queries to prevent misuse, implements result freshness checks, and enforces per-user usage quotas. Essential for building reliable, secure, and cost-controlled 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.

Build robust, event-driven integrations with Exa using scheduled monitoring and content alerts. This skill allows users to establish competitive intelligence pipelines, track content changes over time, and automate research digests. It supports new article detection, similarity monitoring, and reliable webhook delivery via background queues.

Automates enterprise executive summary creation by guiding workflows, enforcing best practices, and generating production-ready outputs for governance, compliance, and integration scenarios.

Automates guidance for implementing factory patterns within test automation, offering best-practice code generation, validation, and setup assistance for unit, integration, and mocking scenarios.

Automates fastify plugin creation within backend development workflows by guiding through best practices, generating production-ready code, and validating configurations for microservices, caching, and database integrations.

Guides use of the Figma MCP server to pull design context, screenshots, variables, and assets, then convert nodes into production-ready code following project conventions and validation steps.

This skill guides the end-to-end development, deployment, and secure integration of complex AI features into Firebase applications. It covers setting up Cloud Functions, Firestore/Storage rules, Authentication, and connecting robustly with Vertex AI/Gemini for advanced AI capabilities. Focuses on building production-grade, highly secure, data-intensive AI systems.

Firecrawl Automation lets you use Claude Code to scrape pages, crawl sites, batch URLs, extract structured data, and monitor jobs via the Composio integration, ideal for terminal-driven web data pipelines.