Skill UI

This client library provides robust functionality for securely accessing, storing, and managing sensitive secrets, such as passwords and API keys, within Azure Key Vault using the Rust programming language. It supports full CRUD operations including getting specific versions, updating properties, and listing all secrets, making it essential for building secure, enterprise-grade cloud applications.

This module provides comprehensive connection methods for Azure Database for PostgreSQL Flexible Server using Node.js and TypeScript with the pg package. It supports both traditional password authentication and modern, recommended Microsoft Entra ID (passwordless) authentication. The guide demonstrates best practices, including connection pooling, parameterized queries to prevent SQL injection, and robust transaction management (BEGIN/COMMIT/ROLLBACK).

This SDK provides a comprehensive client for building advanced search applications using Azure AI Search with TypeScript. It supports cutting-edge retrieval methods including Vector Search, Hybrid Search (combining keywords and vectors), and Semantic Search. Ideal for developers building e-commerce, documentation, or knowledge retrieval systems requiring deep search capabilities.

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.

Walks through broken authentication assessments by analyzing login flows, password policies, brute-force/credential-stuffing, and session/token security to document vulnerabilities and mitigation steps for web applications.

Guides analysts through assessing web authentication, credential stuffing, password policies, session tokens, and fixation flows to uncover broken authentication risks before attackers do.

A comprehensive expert for configuration management, specializing in validating, testing, and ensuring the correctness of application settings. It creates robust validation schemas (e.g., JSON Schema) and performs critical checks, including identifying potential security secrets (API keys, passwords), ensuring data consistency across different environments (development, staging, production), and enforcing type safety for reliable deployments.

Automates Django view generation by guiding through best practices, producing production-ready code, and validating backend-focused outputs whenever users mention related keywords or request assistance.

A comprehensive guide to optimizing costs when using the Exa API. This skill teaches techniques like implementing query-level caching (LRU/Redis), strategically selecting search types (keyword vs. neural), query deduplication for batch jobs, and setting up usage monitoring and budget alerts. Use this when managing Exa billing or reducing API expenditure in RAG applications.

This guide identifies and avoids anti-patterns and common integration mistakes when working with Exa's neural search API. It covers crucial topics such as distinguishing between keyword and neural searches, properly retrieving content, handling date filters, and managing client instances. Use this when reviewing Exa-powered code, onboarding new team members, or auditing existing integrations for robustness and correctness.

A comprehensive guide for migrating search pipelines from traditional keyword-based APIs (Google, Bing, Tavily) to Exa's advanced neural search capabilities. This guide covers building an adapter layer, implementing feature-flag traffic shifting, translating legacy query syntax, and leveraging Exa's unique features like semantic and similarity search for superior results.

Provides minimal working examples and comprehensive instructions for querying the Fireflies.ai GraphQL API. Users can learn how to list workspace users, fetch recent meeting transcripts, and retrieve detailed summaries, including action items and keywords, using code examples in TypeScript, Python, and Bash. Ideal for initial API setup, integration testing, or learning GraphQL patterns for meeting data.