Skill UI

Checks website, GitHub, and local docs to identify messaging inconsistencies and captures version, feature, terminology, and contact differences in a read-only discrepancy report whenever a consistency check is requested.

This comprehensive guide covers the best practices for building production-ready, scalable serverless applications on Amazon Web Services (AWS). Learn to leverage core services like Lambda, API Gateway, and DynamoDB, and implement advanced patterns such as event-driven architectures (SQS/SNS). The content emphasizes performance optimization, robust error handling, structured logging, and deploying infrastructure using SAM/CDK.

This comprehensive guide covers the best practices for building production-ready, scalable serverless applications on Amazon Web Services (AWS). Learn to leverage core services like Lambda, API Gateway, and DynamoDB, and implement advanced patterns such as event-driven architectures (SQS/SNS). The content emphasizes performance optimization, robust error handling, structured logging, and deploying infrastructure using SAM/CDK.

This skill covers the end-to-end development of cross-browser extensions (Chrome, Firefox). Expertise includes mastering Manifest V3, structuring complex architecture (service workers, content scripts), managing local/sync storage, building user interfaces, and implementing monetization models. Ideal for building robust, production-ready tools and navigating store publishing policies.

This guide provides comprehensive instructions for developers to install and set up the Exa SDK (exa-js for Node.js, exa-py for Python). It covers setting up API key authentication using environment variables and demonstrates client initialization for both major languages, enabling developers to utilize Exa's neural search API for web content retrieval.

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.

A systematic guide for debugging complex, hard-to-diagnose issues with Firecrawl. Use this when standard troubleshooting fails, such as when scrapes return empty content, crawl jobs hang indefinitely, or webhooks fail to fire. It employs layer-by-layer isolation techniques, covering API connectivity, target URL accessibility, and content quality to pinpoint failure points.

A comprehensive quick-reference guide for diagnosing and fixing common Firecrawl API errors and response codes. Covers critical issues such as API key validation (401), rate limiting (429), credit exhaustion (402), and handling dynamic content rendering failures in Single Page Applications (SPA). Use this when debugging failed web scraping or crawl job runs.

This advanced workflow executes sophisticated web data gathering tasks. It supports three primary functions: LLM-powered structured data extraction using custom JSON schemas or prompts; efficient batch scraping of multiple known URLs; and rapid site mapping to discover all reachable URLs on a domain. Use this when you require reliable, typed data structures rather than raw markdown content.

This comprehensive guide identifies common anti-patterns and integration mistakes when using Firecrawl for web scraping and content extraction. It serves as a vital code review checklist, helping developers avoid pitfalls such as unbounded crawling, unspecified output formats, or aggressive API polling, ensuring robust and efficient data pipelines.

Provides comprehensive observability patterns for Firecrawl web scraping operations. It covers key metrics such as scrape success rates, credit consumption tracking, content quality assessment, and latency monitoring. Use this skill for implementing robust monitoring dashboards, setting up proactive failure alerts, and optimizing the reliability of web crawling workflows.

This skill provides robust, automated guardrails for web scraping pipelines using Firecrawl. It enforces critical policies to ensure compliance and stability, including domain blocklists (preventing scraping prohibited sites), managing API credit budgets, filtering low-quality content (e.g., error pages, thin content), and implementing granular per-domain rate limiting. Use this when building highly reliable, legal, and cost-efficient scraping solutions.