Skill UI

A comprehensive guide for building or reviewing SwiftUI User Interfaces that utilize the modern Liquid Glass aesthetic. This skill focuses on correctly implementing native Apple APIs (like `glassEffect` and `GlassEffectContainer`) while ensuring proper fallback mechanisms, modifier ordering, and performance for iOS 26+ devices. Ideal for adopting cutting-edge iOS design patterns.

This skill provides comprehensive functionality for reading, creating, editing, and downloading content from Lark Feishu Docs (Docx/Wiki). Whether accessing via URL or token, it supports structured content manipulation using both XML and Markdown formats (v2 API). Use it for fetching document details, updating specific blocks, and managing embedded media and resources like whiteboards and images. Note that it requires prerequisite knowledge for advanced operations.

Acontext serves as a robust memory layer for production-grade AI agents. It provides persistent sessions, disk-based storage, and sophisticated learning spaces that distill complex conversations into reusable, structured skills. Users can manage the entire system—from project setup and login to skill uploading—via a powerful Command Line Interface (CLI) and API, significantly enhancing agents' contextual understanding and long-term knowledge retention.

A powerful utility for performing semantic searches across a large knowledge base of 105K+ skill cards. It allows users to find the most relevant skills based on natural language queries, supporting both Python API integration and Command Line Interface (CLI). This tool is zero-dependency and highly efficient for skill discovery and knowledge retrieval in development workflows.

This skill facilitates reproducible retrieval of scientific, regulatory, or financial facts by querying documented public APIs. It requires defining a strict retrieval contract, handling complex filtering, managing pagination, and ensuring full provenance and auditable results, minimizing reliance on general knowledge inference.

A comprehensive guide to installing the flyctl CLI and setting up secure authentication for Fly.io edge compute deployments. This guide covers both interactive login and API token methods (User, Deploy, Org, Machines), which are essential for CI/CD pipelines and advanced resource management via the Machines API.

This skill provides a comprehensive workflow for integrating external data sources into the Glean enterprise search platform. It covers setting up custom datasources, performing high-volume bulk document indexing using the Indexing API, and granularly managing document permissions (read/write access) to ensure accurate and secure search results for large organizations. Ideal for data engineers and developers building internal knowledge bases.

This document provides a comprehensive guide to managing rate limits when interacting with the Lucidchart API. It details specific limits for various operations (e.g., shape creation, document listing, exporting) and offers implementation patterns, including a token bucket rate limiter class and robust retry strategies. Use this knowledge to build automated workflows that reliably handle high-volume batch processing and prevent API throttling.

This skill provides comprehensive guides for deploying stateless, serverless API wrappers powered by Claude (Anthropic). It details how to integrate and stream responses from the Messages API across major cloud environments, including Vercel Edge Functions, Fly.io, and Google Cloud Run. It is essential for productionizing AI applications that require robust secret management, scalable infrastructure, and real-time streaming capabilities.

This comprehensive workflow guides the implementation of a complete Retrieval-Augmented Generation (RAG) pipeline using Cohere's core services. It demonstrates the full process: embedding documents, searching for relevant context, reranking results for precision, and finally generating a grounded answer with precise citations using the Chat API. Ideal for building knowledge-intensive, enterprise-grade Q&A systems.

This guide demonstrates how to deploy a minimal "Hello World" application to the Fly.io platform. It covers two primary deployment methods: using the simple `flyctl` Command Line Interface (CLI) for quick setup, and utilizing the advanced Machines API for programmatic deployment. This skill is ideal for beginners starting a new Fly.io project, or for implementing robust, globally distributed edge compute infrastructure.

A comprehensive TypeScript SDK providing production-ready patterns for interacting with the Fly.io Machines REST API. It includes a typed client for managing the entire machine lifecycle—creation, state polling, and deletion—across multiple global regions. Features like robust error handling, rate-limit retries, and deployment builders ensure reliable multi-region orchestration for edge computing applications.