Skill UI

A comprehensive Python SDK for interacting with Azure Table Storage and Cosmos DB Table API. This library enables developers to perform full NoSQL key-value operations, including creating, reading, updating, and deleting (CRUD) entities, executing complex queries using filtering, and managing batch transactions. It supports both synchronous and asynchronous operations, making it ideal for building resilient, high-throughput cloud applications.

This Python SDK provides comprehensive management capabilities for Azure API Center. It allows developers to programmatically handle the entire API lifecycle, including API registration, version control, metadata definition, definition import, and deployment management across an organization's API estate, ensuring robust governance and centralized control.

This SDK provides comprehensive Java support for managing secrets within Azure Key Vault. It enables developers to securely store, retrieve, update, list, delete, and recover sensitive configuration data, such as API keys, database passwords, and connection strings. It is essential for building secure, production-ready applications that comply with best security practices.

A comprehensive guide to modern backend development patterns for scalable server-side applications using Node.js, Express, and Next.js. Covers API design (RESTful), data access patterns (Repository, Service Layer), database optimization (N+1 prevention, Transactions), and advanced caching strategies (Redis, Cache-Aside). Essential for building robust, high-performance APIs.

An expert resource for developing highly reusable, production-grade cloud infrastructure using AWS Cloud Development Kit (CDK) in languages like TypeScript, Python, or Java. This guide provides established patterns for common services (e.g., Serverless APIs, ECS, Data Pipelines), focusing on best practices such as implementing least privilege, separating stateful resources, and ensuring monitoring via CloudWatch.

Documenting backend architecture patterns, API design, database optimization, caching, and error-handling best practices tailored for scalable Node.js, Express, and Next.js API routes.

An expert developer specializing in secure backend coding practices, vulnerability mitigation, and robust API design. Proficient in preventing common attacks such as SQL injection, XSS, and CSRF. Covers comprehensive areas including input validation, authentication mechanisms (OAuth 2.0, MFA), database security, and implementing necessary security headers (CSP, HSTS) for building secure-by-design applications. Ideal for implementing security fixes or building new, hardened backend services.

A comprehensive guide to building robust, production-ready GraphQL APIs. This skill covers schema design (SDL/code-first), implementing efficient resolvers with DataLoader for batching, handling real-time subscriptions via WebSockets, and integrating field-level authorization and complexity limiting. Supports major runtimes like Node.js and Python.

Provides deep, advanced debugging techniques for complex data enrichment failures within the Clay platform. This guide helps isolate root causes related to provider degradation, data flow errors, and API column issues when standard troubleshooting methods fail. It covers layer testing (Webhook, API), error pattern analysis, and local API replication, enabling users to diagnose deep system issues.

This comprehensive guide provides solutions for the most frequent errors encountered when using Clay for data enrichment, webhooks, and API integrations. It covers issues such as 422/404 webhooks, credit limits, data quality failures, and rate limiting, ensuring smooth data workflow management.

This advanced workflow uses Claygent AI to perform deep research on target companies by scraping websites. It extracts critical data points such as funding rounds, tech stacks, and potential pain points. These insights are then leveraged to generate highly personalized, human-sounding email openers at scale, ensuring high relevance for targeted outreach campaigns.

This guide details advanced strategies for optimizing and reducing data enrichment spending on platforms like Clay. Techniques include connecting private API keys (for significant savings), optimizing multi-step data pipelines (waterfalls), pre-filtering raw input data to prevent wasted credits, and implementing comprehensive budget monitoring. Ideal for professionals managing high-volume, cost-sensitive data pipelines.