Skill UI

This comprehensive workflow guides the entire lifecycle of building a complex full-stack feature, from initial architectural design to final integration testing. It enforces an API-first approach, ensuring that the database schema, backend services, and frontend components are developed cohesively, promoting scalability, testability, and adherence to modern industry best practices.

An expert guide and framework for building production-grade, sophisticated AI agent systems. This skill specializes in utilizing the latest LangChain 0.1+ and LangGraph APIs to implement multi-agent orchestration, advanced Retrieval-Augmented Generation (RAG) pipelines (e.g., RAG Fusion, HyDE), and complex state management. It covers comprehensive topics from architectural design (Plan-and-Execute, ReAct Agents) to production deployment (FastAPI streaming, LangSmith observability, caching, and robust error handling).

Guides designing robust microservices with service boundaries, event-driven communication, saga orchestration, API gateways, health checks, and anti-pattern awareness for resilient distributed systems.

This skill implements a sophisticated, config-driven rules engine for OpenRouter API calls. It dynamically determines the optimal large language model (LLM) by evaluating a comprehensive context, including user subscription tier, remaining cost budget, specific task type (code, chat), required tools, and latency requirements. This is essential for building production-grade, cost-aware, and robust LLM orchestration systems.

This guide demonstrates how to implement clean and robust asynchronous pipelines in TypeScript using `TaskEither` from `fp-ts`. It solves the common problem of deeply nested, unmanageable `try/catch` blocks, allowing developers to compose sequential API calls and operations while correctly handling success and failure paths in a functional, immutable manner. Ideal for complex data fetching and workflow orchestration.

Guides developers to wrap Feishu API calls into reusable lark-cli skills, covering API research, command templates, and best practices for authentication, permissions, and orchestration.

A robust, production-ready architecture pattern for integrating with multiple Adobe APIs, including Firefly Services, PDF Services, and I/O Events. This pattern enforces a layered structure (API -> Service -> Client -> Infrastructure), ensuring clean separation of concerns, centralized authentication, robust error handling boundaries, and scalable workflow orchestration for enterprise applications.

This skill provides the core mechanism for integrating Hex into external data pipelines. It enables triggering, monitoring, and managing Hex projects (e.g., via Airflow or Dagster) programmatically. Users can implement parameterized runs, execute multi-step ETL workflows sequentially, and handle status polling and error management, making it ideal for production data orchestration.

A comprehensive guide to setting up a robust local development loop for Hex API orchestration. This includes defining the project structure, creating a typed API client using TypeScript, and implementing mocked unit tests (e.g., using vitest) to ensure fast iteration and reliable testing of data pipelines and external service interactions.

This guide provides production-ready patterns for integrating with the Hex platform API using TypeScript and Python. It covers essential best practices like robust retry logic, typed client usage, pipeline orchestration, and Airflow integration, helping developers establish standardized, reliable coding standards for complex Hex workflows.

This detailed guide outlines a production-ready, layered architecture for building complex AI applications using the Cohere API v2. It covers implementing Retrieval-Augmented Generation (RAG) pipelines, advanced tool-use agents, and multi-model orchestration. Use this structure when designing new Cohere integrations or establishing robust architectural standards for enterprise AI solutions.

This comprehensive guide provides a production-grade reference architecture for building robust Text-to-Speech (TTS) and voice applications using the ElevenLabs API. It covers detailed project structure, service layer design (including TTS orchestration, voice management, and caching), configuration handling, and best practices for streaming and multi-model orchestration, ensuring scalability and reliability in a commercial SaaS environment.