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Found 698 Skills
Comprehensive Ruby implementations of Gang of Four (GoF) design patterns. Use when implementing object-oriented design solutions, refactoring to reduce coupling, solving architecture problems, or when user mentions specific patterns (Factory, Singleton, Observer, Strategy, etc.) in Ruby context.
Use when writing or refactoring Ruby code that integrates Claude Code via the claude-agent-sdk gem (ClaudeAgentSDK.query, ClaudeAgentSDK::Client, streaming input, ClaudeAgentOptions configuration, tools/permissions, MCP servers, hooks, structured output, budgets, sandboxing, session resumption/rewind, and Rails patterns like jobs or ActionCable).
React component composition patterns for building flexible, maintainable UIs. Covers compound components, context-based state, explicit variants, and React 19 APIs. Use when designing component APIs, refactoring prop-heavy components, or building reusable component libraries.
Comprehensive documentation quality system combining automated validation with ToolUniverse-specific auditing. Detects outdated commands, circular navigation, inconsistent terminology, auto-generated file conflicts, broken links, and structural problems. Use when reviewing documentation, before releases, after refactoring, or when user asks to audit, optimize, or improve documentation quality.
RESTful API design guidelines following the Richardson Maturity Model through to Level 3 (HATEOAS) for Ruby on Rails. This skill should be used when designing, building, reviewing, or refactoring REST APIs to ensure proper resource modeling, HTTP method semantics, hypermedia controls, content negotiation, and API evolvability. Triggers on tasks involving API controllers, serializers, routing, link relations, pagination, error handling, or HTTP caching in Rails.
Zustand state management best practices for React applications. Use when writing, reviewing, or refactoring Zustand stores to ensure optimal performance and maintainability. Triggers on tasks involving state management, stores, selectors, re-renders, and Zustand patterns.
This skill should be used when the user asks to "use the oracle" or "ask the oracle" for deep research, analysis, or architectural questions. The oracle excels at multi-source research combining codebase exploration and web searches, then synthesizing findings into actionable answers. Use for complex questions requiring investigation across multiple sources, architectural analysis, refactoring plans, debugging mysteries, and code reviews.
This skill SHOULD be used when writing, reviewing, or refactoring Neovim plugins in Lua. Apply Neovim community best practices, plugin architecture patterns, and idiomatic Lua style to ensure clean, maintainable plugins.
Ruby on Rails performance and maintainability optimization guidelines for building backend APIs and frontend web applications. This skill should be used when writing, reviewing, or refactoring Ruby on Rails code to ensure optimal patterns for controllers, models, ActiveRecord queries, caching, views, API design, security, and background jobs. Triggers on tasks involving Rails controllers, ActiveRecord queries, migrations, Turbo/Hotwire, API endpoints, background jobs, or Rails performance improvements.
Ruby performance optimization guidelines. This skill should be used when writing, reviewing, or refactoring Ruby code to ensure optimal performance patterns. Triggers on tasks involving object allocation, collection processing, ActiveRecord queries, string handling, concurrency, or Ruby runtime configuration.
Kotlin + Arrow typed error handling using Raise DSL and wrapper types (Either/Option/Ior/Result/nullable), including validation with accumulation, interop with exceptions, and custom error wrappers. Use for designing or refactoring error modeling, converting exception-based flows, building smart constructors, accumulating validation errors, or integrating Outcome/Progress-style wrappers with Arrow.
Apply production-ready Databricks SDK patterns for Python and REST API. Use when implementing Databricks integrations, refactoring SDK usage, or establishing team coding standards for Databricks. Trigger with phrases like "databricks SDK patterns", "databricks best practices", "databricks code patterns", "idiomatic databricks".