Skill UI

A comprehensive pattern for configuring API clients across multiple operational environments (development, staging, production). This skill uses TypeScript schemas and factory patterns to ensure environment isolation, manage distinct credentials, enforce rate limiting, and implement feature gating. It is essential for building robust, scalable SaaS applications that interact with external services like Apollo.io.

This skill provides a comprehensive and isolated setup for managing Deepgram API integrations across different deployment stages (Development, Staging, Production). It includes typed configuration management, a client factory pattern, and Docker Compose profiles, ensuring that each environment uses specific credentials, models, and feature settings (like diarization or PII redaction) without conflict. Ideal for robust, multi-stage application deployment.

Provides Django testing strategies combining pytest-django, factory_boy, DRF helpers, mocking, and coverage so teams can adopt TDD workflows for models, views, serializers, and APIs.

This guide details how to configure a robust multi-environment setup for Evernote integrations. It ensures proper isolation and configuration management between development, staging, and production environments. Learn to use environment variables, build an environment-aware client factory, and set up CI/CD pipelines, ensuring reliable and secure API connectivity across all stages.

Automates guidance for implementing factory patterns within test automation, offering best-practice code generation, validation, and setup assistance for unit, integration, and mocking scenarios.

Provides expert guidance for using llama-factory to fine-tune LLMs through its WebUI, covering QLoRA/LoRA quantized setups, multimodal models, and automation tips for developers exploring models like Llama, Qwen, or Gemma.

This skill guides developers through advanced, safe, and systematic code refactoring using Test-Driven Development (TDD) principles. It provides a comprehensive workflow encompassing pre-assessment, detecting code smells, applying major design patterns (SOLID, Factory, Strategy), optimizing performance, and ensuring safety through rigorous, incremental testing. Use this when improving code structure, restructuring large components, or updating legacy systems while guaranteeing functional integrity and maintainability.

A comprehensive guide covering best practices for unit and integration testing, including Test-Driven Development (TDD) and Behavior-Driven Development (BDD). This guide details factory functions for creating reusable mock data and props, advanced mocking strategies for modules and hooks, and custom rendering utilities, ensuring tests are maintainable and reliable in React/TypeScript environments.

Theme Factory delivers 10 curated color and font themes plus a workflow to apply or generate palettes for slides, docs, reports or landing pages, ensuring consistent visual identity across artifacts.

This expert skill reviews the architecture and design of the Bitcoin Lightning Network protocol. It analyzes complex Layer 2 scaling tradeoffs, compares various channel factory approaches, and evaluates critical technical aspects—including trust models, on-chain footprint, consensus requirements, HTLC/PTLC compatibility, liveness guarantees, and watchtower support. Use this when assessing the cryptographic and systemic soundness of L2 blockchain protocols.

A comprehensive technical reference for implementing advanced Lightning Network channel factories. It covers complex topics such as multi-party channels, Layer 2 scaling on Bitcoin, and advanced protocols including Decker-Wattenhofer invalidation trees, MuSig2 key aggregation, and encrypted Noise NK transport. Essential for developers building highly scalable and secure Bitcoin infrastructure.

An expert guide detailing the SuperScalar protocol and Bitcoin Lightning channel factories. It explains scalable onboarding mechanisms using shared UTXOs, advanced cryptographic structures like Decker-Wattenhofer trees, and MuSig2. This knowledge is vital for understanding how Bitcoin can scale significantly without requiring disruptive soft forks.