Results for “unichain”

Configure and use UnoCSS, an instant atomic CSS engine with presets, rules, shortcuts, and integrations for Vite and Nuxt.

UniFFI by Mozilla — generates idiomatic Kotlin, Swift, Python, and Ruby bindings from a Rust crate. Covers UDL definition, proc-macro mode, async support, callback interfaces, error handling, custom types, and the Kotlin Multiplatform fork (uniffi-kotlin-multiplatform-bindings) used by BDK, Breez SDK, CDK, LWK. USE WHEN: user mentions "UniFFI", "Rust to Kotlin", "Rust to Swift", "FFI bindings", "uniffi-rs", "UDL file", "uniffi-bindgen", "BDK bindings", "Breez SDK bindings", "kotlin-multiplatform-bindings", "Mozilla UniFFI" DO NOT USE FOR: Raw C FFI - use `languages/swift` interop quick-ref + Rust core DO NOT USE FOR: WebAssembly bindings - use wasm-bindgen DO NOT USE FOR: Flutter/Rust bridge - use `flutter_rust_bridge` skill if exists DO NOT USE FOR: React Native - use `uniffi-bindgen-react-native` (out of scope here)

Configure and use UnoCSS, an instant atomic CSS engine that is a superset of Tailwind CSS, including rules, shortcuts, presets, and integrations.

UnoCSS instant atomic CSS engine, superset of Tailwind CSS. Use when configuring UnoCSS, writing utility rules, shortcuts, or working with presets like Wind, Icons, Attributify.

Build onchain applications with React components and TypeScript utilities from Coinbase's OnchainKit, supporting wallet connection, token swaps, NFT minting, and payment processing.

Build onchain applications with React components and TypeScript utilities from Coinbase's OnchainKit. Use when users want to create crypto wallets, swap tokens, mint NFTs, build payments, display blockchain identities, or develop any onchain app functionality. Supports wallet connection, transaction building, token operations, identity management, and complete onchain app development workflows.

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.