Skill UI

This skill defines the mandatory conventions and architectural rules for developing maintainable, cross-platform applications using Avalonia UI and the Zafiro toolkit. It enforces a functional-reactive MVVM approach, prioritizing explicit error handling via Result types, and mandates leveraging Zafiro's existing abstractions to ensure code quality and predictability.

Automates Basin toolkit operations via Rube MCP by discovering tools through RUBE_SEARCH_TOOLS, ensuring connections via RUBE_MANAGE_CONNECTIONS, and executing commands with RUBE_MULTI_EXECUTE_TOOL using schema-compliant arguments while managing session and memory expectations.

Guides Claude Code skill authors through designing and structuring workflow-based skills with numbered phases, decision routing, subagent delegation, and progressive disclosure so multi-step automations remain predictable and auditable.

Automates Docker Hub workflows through the Composio MCP integration, letting teams list organizations, create orgs and repositories, manage members and teams, and configure image-push webhooks for predictable deployments.

Documented workflow for orchestrating Extracta AI operations through Composio’s Rube MCP, emphasizing tool discovery, connection checks, and schema-compliant executions with RUBE_SEARCH_TOOLS and RUBE_MULTI_EXECUTE_TOOL calls.

This guide teaches developers how to achieve type-safe and predictable error handling in TypeScript using functional programming concepts from fp-ts, specifically focusing on the Either and TaskEither patterns. Instead of relying on disruptive try/catch exceptions, this pattern treats errors as explicit data values, forcing the calling code to handle failure paths, which is crucial for building robust, maintainable, and functional APIs and services.

Learn practical, type-safe patterns for building complex React applications using fp-ts. This guide covers key functional programming concepts like handling optional values (Option), managing failure states (Either), and structuring data fetching and forms, ensuring your code is predictable and robust for React 18/19 and Next.js 14/15.

This comprehensive guide establishes strict architectural and performance standards for senior frontend engineers working with React, TypeScript, and Suspense. It dictates best practices for component design, feature implementation, data fetching (useSuspenseQuery), and code structure (feature-based organization). Use this when building any new component, feature, or handling data mutation to ensure the resulting application is scalable, predictable, and maintainable.

Guides automation of Notion via Composio’s Rube MCP toolkit, covering setup, tool sequences, parameter expectations, and common pitfalls for pages, databases, blocks, schemas, users, and comments.

This skill provides comprehensive best practices and Python code examples for optimizing API calls to Large Language Models (LLMs) via OpenRouter. It covers benchmarking model latency, implementing streaming to achieve low Time-To-First-Token (TTFT), and processing requests concurrently using asynchronous programming (asyncio). Use this when developing real-time, high-throughput applications that require predictable and fast model responses.

Automates Pingdom maintenance by ensuring you first discover the current tool schemas via Rube MCP, confirm the Pingdom connection, and then execute workflows with schema-compliant arguments so operations stay reliable and predictable.

Blueprint skill describing the architecture, stack, folder layout, API patterns, and testing/deployment workflows used by the Zenith AI customer discovery platform clade. Use it as a reference when working on this dedicated project to understand expectations for frontend, backend, AI integration, and QA.