Skill UI

A comprehensive guide covering best practices for designing developer-friendly REST APIs. Learn proper resource naming conventions (nouns, plural, kebab-case), effective use of HTTP methods (GET, POST, PUT, PATCH, DELETE), and semantic status codes (4xx, 5xx). The guide also details advanced topics like cursor-based pagination, field filtering, query parameter usage, and robust error handling formats.

A comprehensive guide covering best practices for designing developer-friendly REST APIs. Learn proper resource naming conventions (nouns, plural, kebab-case), effective use of HTTP methods (GET, POST, PUT, PATCH, DELETE), and semantic status codes (4xx, 5xx). The guide also details advanced topics like cursor-based pagination, field filtering, query parameter usage, and robust error handling formats.

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.

Transforms git commits into polished, customer-ready changelog entries by analyzing history, categorizing features/bug fixes, filtering noise, and applying consistent brand voice so releases are ready in minutes.

This guide provides comprehensive patterns and best practices for working with ClickHouse, a high-performance OLAP database. It covers advanced topics such as MergeTree engine design, efficient query optimization (filtering, aggregations, window functions), bulk/streaming data ingestion, materialized view creation, and performance monitoring techniques, ensuring optimal performance for large-scale analytical workloads.

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.

Chroma is an open-source, AI-native embedding database designed for building sophisticated LLM applications. It allows users to store high-dimensional embeddings and associated metadata, facilitating powerful vector search and full-text filtering. Ideal for implementing Retrieval-Augmented Generation (RAG) systems, semantic search, and document retrieval in local or self-hosted environments, making it perfect for open-source AI projects and prototyping.

A sophisticated system for recovering and reconstructing complex project context across distributed, multi-agent AI workflows. It utilizes advanced semantic vector search, relevance filtering, and optimized rehydration patterns to maintain high knowledge fidelity and ensure seamless continuity in long-running, complex AI projects. Essential for advanced RAG implementations.

This guide provides a comprehensive method for optimizing CodeRabbit's review process, focusing on improving speed, relevance, and the signal-to-noise ratio. Learn best practices for managing PR size, selecting the right review profile (e.g., 'assertive' vs. 'chill'), using path instructions to guide feedback, and filtering out low-value files. Ideal for teams looking to reduce review fatigue and ensure consistent code quality checks.

Detects operations in cryptographic code that leak secrets via timing side channels, guiding developers through multi-language analysis and CLI flags for warnings, filtering, architecture, and optimization levels.

A comprehensive workflow for executing advanced, semantic web searches using Exa. This tool moves beyond simple keyword matching, enabling deep context retrieval by understanding the intent behind the query. Key features include RAG context retrieval, content extraction (summaries, highlights, full text), and robust filtering by date range, specific domains, and content categories. Ideal for building knowledge base search features and complex research pipelines.

Leverages the Exa API for semantic/embeddings search, discovering similar content, or filtering by categories like companies, people, and research papers, making research and knowledge retrieval more targeted.