Skill UI

This skill guides the secure deployment of Claude API integrations into production cloud environments. It provides comprehensive instructions for implementing services across multiple infrastructures, including Docker, GCP Cloud Run, and Kubernetes. The guide covers best practices such as secret management, health checks, and reliable rollback procedures to ensure high service reliability.

This comprehensive skill provides multi-layered guardrails for integrating with LLMs like Claude. It enforces security and compliance by implementing input validation (PII detection, length checks), system prompt restriction (scope control, safety rules), output filtering (preventing sensitive data leakage), cost governance, and model access policies. Ideal for building secure, robust, and governed AI applications.

Implements robust rate limiting, backoff logic, and quota management for the Anthropic Claude API. It handles 429 errors and optimizes request throughput by managing Requests Per Minute (RPM), Input Tokens Per Minute (ITPM), and Output Tokens Per Minute (OTPM). This skill provides advanced strategies including SDK retries, custom header awareness, queue-based throttling, and batch processing for stable, high-throughput production applications.

A comprehensive guide for building applications with Claude, ensuring responsible data handling. This skill covers critical patterns such as PII redaction (stripping sensitive data like emails, phone numbers, and card numbers), optimizing the 200K token context window through conversation trimming, and implementing best practices for data retention and privacy compliance when interacting with the Anthropic API.

This skill provides comprehensive guides for deploying stateless, serverless API wrappers powered by Claude (Anthropic). It details how to integrate and stream responses from the Messages API across major cloud environments, including Vercel Edge Functions, Fly.io, and Google Cloud Run. It is essential for productionizing AI applications that require robust secret management, scalable infrastructure, and real-time streaming capabilities.

A deep dive into handling typed content blocks (text, image, tool_use, thinking, document) in LangChain 1.0. This skill standardizes multi-modal message composition, tool-call iteration, and complex content handling across providers like Claude, GPT-4o, and Gemini, solving key API discrepancies.

A comprehensive guide to advanced, production-ready LLM inference using LangChain 1.0. This skill addresses common pitfalls and bugs when integrating multiple providers (Claude, GPT-4o, Gemini), covering issues like structured output reliability, correct streaming token accounting, and robust handling of complex AIMessage content blocks. It teaches best practices for model initialization, provider routing, and version-safe code implementation.

This skill provides comprehensive guidance on correctly configuring Model Context Protocol (MCP) servers within Claude Code. It details the critical concepts of configuration scope (user vs. project) and outlines best practices to prevent context pollution across different coding sessions. Users learn how to safely add, remove, and clean up MCP settings using specific JSON files, ensuring a stable and efficient development environment.

This advanced skill is designed to generate high-quality, publication-ready academic illustrations and diagrams. It utilizes a sophisticated, multi-stage iterative workflow involving Claude for planning, layout optimization, and strict visual review, combined with a dedicated local Codex app-server bridge for native image rendering. The process ensures that generated figures meet the rigorous aesthetic and structural standards required for top-tier conferences and journals (e.g., CVPR, NeurIPS).

This wrapper integrates Shopify's official AI Toolkit MCP server with Claude Code. It provides essential developer capabilities, including real-time GraphQL schema validation, Liquid template linting (checking for deprecated filters and anti-patterns), and instant search across Shopify's extensive documentation. Use this skill when setting up complex Shopify MCP integrations, ensuring code quality, or debugging API calls.

This skill provides comprehensive diagnosis and optimization for agent skill libraries. By analyzing historical session transcripts from platforms like Claude Code and Codex, alongside static skill file checks, it scores each skill across 8 dimensions. It identifies issues such as low trigger rates, poor post-invocation user reaction, and incomplete workflow execution, generating a prioritized report (P0/P1/P2) to significantly improve the agent's overall performance and reliability.

A comprehensive guide on how to write, organize, and optimize skills for AI agents using a Test-Driven Development (TDD) approach, focusing on Claude Search Optimization (CSO) and token efficiency.