Skill UI

This skill provides a comprehensive guide to designing and developing autonomous AI agents for code plugins. It covers the required file structure (YAML frontmatter), best practices for defining agent roles, designing robust system prompts, and setting up clear triggering conditions. Use this when you need to conceptualize, structure, or refine an agent's capabilities to handle complex, multi-step tasks autonomously.

A comprehensive guide to configuring and maximizing the potential of Claude Code, an advanced agentic coding tool. This resource details best practices, setup templates (CLAUDE.md), advanced prompting techniques (e.g., thinking keywords), and debugging strategies for building reliable, complex software autonomously.

Guides how to author Claude Code slash commands using Markdown prompts, YAML frontmatter, dynamic arguments, Bash execution, and best-practice organization for reusable workflows and interactive automation.

This skill orchestrates a comprehensive, multi-stage Git development workflow, simulating the process from code commit to PR preparation. It leverages specialized AI agents (code reviewers, test automators, prompt engineers) to systematically enforce best practices. Key functions include code quality assessment, breaking change analysis, running unit/integration/E2E tests, and generating Conventional Commit messages, ensuring code readiness and high quality before merging.

A comprehensive guide detailing best practices for securing Groq API keys and managing data privacy. It covers critical steps such as using environment variables, implementing secure key rotation procedures, preventing key leaks via pre-commit hooks, and defending against prompt injection attacks for robust application development.

This skill automatically gathers and structures comprehensive context for Apple product development. It analyzes existing project files (like README, Info.plist, and code) and prompts the user for details across product overview, target platforms, technology stack, design system, and accessibility requirements. The output is a structured context document used by other specialized skills to ensure consistent, informed design and development decisions.

Guides Claude Code plugin authors through creating event-driven hooks that validate tool usage, react to outcomes, and gate completion with prompt-based or command hooks, covering PreToolUse, PostToolUse, Stop, Session events, and session context loading.

A comprehensive guide for developers on utilizing the Kling AI Text-to-Video REST API. This skill provides minimal working examples in Python and Node.js, demonstrating the complete workflow: submitting a text prompt, polling the task status, and retrieving the final generated video URL. Ideal for integrating advanced AI video generation capabilities into development projects.

This guide documents common mistakes, gotchas, and anti-patterns encountered during Kling AI API integration. It covers critical best practices regarding data types, token management, polling, URL persistence, and prompt engineering to ensure stable and reliable AI video generation workflows. Essential reading for robust development and troubleshooting.

Integrate Langfuse into CI/CD pipelines (e.g., GitHub Actions) to automate the testing and validation of Large Language Models (LLMs). This guide covers prompt regression testing, tracing validation, and setting up experiment-driven quality gates, ensuring reliable and high-performing AI applications throughout the development lifecycle.

Defines MCP server tooling with file search, query execution, resource endpoints, prompt templates, and transport configurations alongside a client setup example for streamlined project automation.

A comprehensive guide detailing essential security measures for integrating Mistral AI models. Covers API key management, defending against prompt injection, implementing content moderation, sanitizing outputs, and secure logging practices, ensuring robust and safe application development.