Skill UI

This skill is designed for understanding complex database structures. It allows users to list all available tables, intelligently filter relevant tables based on natural language queries, retrieve detailed schemas (columns, types, primary/foreign keys), and map inter-table relationships. It culminates in generating the M-Schema format, which is essential for accurately preparing the context needed for advanced SQL query generation.

This advanced skill optimizes LLM context usage by implementing strict rules for prompt caching, efficient log pruning, AST-based code inspection, and compact data structuring. It minimizes token consumption and maximizes information density, suitable for highly technical and iterative development workflows.

Generate comprehensive software requirements specifications following EARS format. Analyzes project context, creates acceptance criteria, and ensures scope boundaries are clearly defined before implementation. Supports both greenfield and brownfield projects with sub-agent delegation for codebase exploration and domain research.

Provides technology-agnostic guidance for architecting and reviewing modular systems. This skill covers core architectural principles such as bounded contexts, state isolation, explicit contracts, and failure containment. Use it when determining service boundaries, assessing coupling between domains, or designing new greenfield architectures without assuming a specific framework, language, or repository structure.

This comprehensive workflow guides the implementation of a core Algolia search feature. It covers advanced concepts such as full-text search, combining multiple filters (e.g., price range, stock status), utilizing faceted navigation for refined filtering, managing pagination, and displaying highlighted search results. This is essential for building robust and highly functional e-commerce search UIs.

A comprehensive guide for developers encountering complex issues with the Claude API, including context window overflow management, debugging tool use failures, handling streaming corruption, and diagnosing unexpected stop reasons. Provides Python code snippets and diagnostic commands to ensure robust AI integration.

This skill integrates the Clawdbot agent with the LINE messaging platform, enabling robust communication capabilities. It supports core messaging actions such as sending text, sending files, and replying to user messages. This is highly useful for developing AI agents and bots marketed to regions like Japan, Taiwan, Thailand, and Indonesia.

This comprehensive guide details the full plugin architecture for extending Claude Code. Learn how to build various extension points, including auto-activating skills, slash commands, specialized agents, and Model Context Protocol (MCP) servers. It serves as the definitive reference for integrating custom tools and workflows into the Claude ecosystem.

Configure comprehensive CI/CD pipelines for integrating Grammarly's text analysis into your development workflow. This setup uses GitHub Actions to run unit and integration tests on pull requests, validating API connectivity, enforcing content quality gates (e.g., minimum grammar scores), and ensuring documentation quality before merging to the main branch.

Skills this deployment guide covers building, configuring, and deploying a containerized Grammarly writing assistant service. It provides detailed instructions for production setup, including Docker configuration, environment variable management (for OAuth credentials), health checks, and zero-downtime rolling updates when integrating Grammarly's Text API for grammar, clarity, and tone checking.

This comprehensive checklist guides developers through the necessary steps to deploy a robust and reliable Grammarly API integration in a production environment. It covers critical aspects such as secure credential storage, rate limit handling, implementing text chunking, designing error resilience patterns (circuit breakers, retries), and establishing comprehensive monitoring and alerting systems to ensure high content quality and system uptime.

This guide provides production-ready patterns for integrating with the Grammarly API using both TypeScript and Python. It covers essential architectural aspects, including typed client implementation, robust token management (OAuth flow), and efficient text chunking for processing large documents. Use this when building scalable, reliable Grammarly-powered features into your application.