Skill UI

This skill details the deployment of Privileged Access Management (PAM) for critical database systems, including Oracle, SQL Server, PostgreSQL, and MySQL. It covers essential security controls such as session proxy configuration, credential vaulting, query auditing, and enforcing least-privilege access, helping organizations meet stringent compliance and security standards.

This comprehensive guide details the workflow for creating robust, database-agnostic integration tests for data access layers migrating from Oracle to PostgreSQL. It outlines best practices for generating deterministic test cases using controlled seed data, ensuring that business logic and behavior remain consistent and validated across both source and target database systems.

This comprehensive guide covers best practices for building robust database systems. It teaches crucial concepts like schema normalization, effective indexing strategies, selecting the right database (e.g., SQLite vs PostgreSQL) and ORM, and optimizing queries to prevent common performance issues like N+1 problems. It emphasizes making context-aware architectural decisions.

A command-line interface (CLI) for accessing and interacting with Model Context Protocol (MCP) servers. It acts as a unified gateway, allowing users to discover, inspect, and execute tools and APIs from external sources like filesystems, databases, APIs, and specialized services. Essential for programmatic workflow automation and system integration.

Cross-database SQL performance optimization assistant offering query tuning, indexing strategies, pagination, batch operations, and monitoring guidance for MySQL, PostgreSQL, SQL Server, Oracle, and other relational systems.

Provides a comprehensive setup guide for running ClickHouse locally using Docker Compose. This includes defining the database schema, seeding mock data, and setting up robust integration tests (using vitest). Ideal for developers building OLAP systems or performing local data analysis to ensure schema and query reliability.

Learn how to build complex, multi-step AI agents using Cohere's Chat API v2. This skill demonstrates defining external tools (like weather APIs or database searches) and implementing the full agent loop: model calls tool -> execute tool -> feed result back -> final answer. Ideal for creating autonomous, tool-using workflows that interact with external systems.

This plugin allows developers to build Framer components by syncing data from external data sources (such as APIs or databases) into Framer's Managed Collections. It serves as the primary integration pattern, handling both schema creation and item population. Use this when your design requires displaying dynamic content driven by external systems.

Provides comprehensive programmatic access to Notion, allowing users to create, update, archive, and compose rich content blocks within pages and databases. This skill covers the full page lifecycle—from initial creation with structured properties to appending complex blocks (headings, lists, toggles, code) and managing status updates. It is essential for building automated knowledge bases, automating content workflows, and programmatically managing enterprise information systems using the Notion API.

Qdrant is a high-performance vector database. This client SDK suite provides official, easy-to-use libraries for multiple programming languages (including Python, Java, Go, and TypeScript). It enables developers to seamlessly integrate sophisticated vector search capabilities into their applications, supporting both REST and gRPC APIs. Ideal for building semantic search engines, recommendation systems, and advanced AI applications.

A comprehensive and advanced playbook for mastering SQL injection techniques. It covers critical areas including WAF bypass, out-of-band data exfiltration, second-order injection, and exploitation strategies across major database systems (MySQL, MSSQL, Oracle, PostgreSQL). Essential for professional penetration testing and security auditing.

This skill provides a comprehensive guide for building scalable Retrieval-Augmented Generation (RAG) pipelines and persistent agent memory using Pinecone as the vector database. It covers index setup, embedding large corpuses, implementing dense and hybrid semantic search, and advanced metadata filtering for real-world production systems. Use this for building searchable knowledge bases and context-aware AI agents.