Skill UI

Offers a reference structure for Claude Code plugin skills, describing triggers, file layouts, and best practices so you can craft new skills quickly and consistently.

Automates file format conversion guidance within data pipelines, covering ETL, workflow orchestration, data transformation, and streaming standards with production-ready examples.

Provides minimal working examples and comprehensive instructions for querying the Fireflies.ai GraphQL API. Users can learn how to list workspace users, fetch recent meeting transcripts, and retrieve detailed summaries, including action items and keywords, using code examples in TypeScript, Python, and Bash. Ideal for initial API setup, integration testing, or learning GraphQL patterns for meeting data.

This guide details the comprehensive setup process for authenticating with the Fireflies.ai GraphQL API. It covers retrieving the API key, configuring environment variables, and verifying connectivity using code examples for Node.js, Python, and cURL. Essential for securely integrating Fireflies data into external applications and automating transcript access.

A comprehensive, step-by-step checklist for deploying Fireflies.ai integrations to a live production environment. This guide ensures API key management, webhook setup, robust health checks (including a TypeScript example), continuous monitoring, and a defined rollback procedure are all executed correctly for a successful go-live.

This skill provides a comprehensive guide and multiple code examples (cURL, Node.js, Python) for generating presentations using the Gamma API. It implements the standard asynchronous 'Generate-Poll-Retrieve' pattern: first POST to create the generation job, then GET to poll the status until complete, and finally retrieve the viewable and exportable URLs (PDF/PPTX).

Generates complete, production-ready Google Cloud Platform (GCP) code examples and infrastructure templates. It spans various modern AI patterns, including ADK agents, Genkit RAG flows, and multimodal analysis using Vertex AI and Gemini. The output includes runnable code, deployment configuration (Terraform/IaC), security best practices (IAM, VPC-SC), and monitoring setup, ensuring enterprise-grade reliability and cost optimization.

This comprehensive guide provides documentation and code examples for utilizing the Gemini API, Google's advanced multimodal AI platform. It enables developers to power applications with cutting-edge capabilities, including text generation, multimodal understanding (images, audio, video), function calling, and structured data output. Supports major languages like Python, JavaScript, and Go.

Transforms OpenAPI specifications into comprehensive, interactive documentation sites. This skill generates runnable code examples (cURL, Python, JS, Go), detailed authentication guides, error references, and supports versioning. It is crucial for building professional developer portals that guide users through API usage seamlessly.

A comprehensive guide detailing common Groq API error codes (e.g., 401, 429, 400). It provides root causes, proper fixes, and code examples (Python, TypeScript) for debugging API integrations, ensuring stable operation in development environments.

A comprehensive guide to using Groq's high-speed LPU for chat completion. This resource provides code examples in TypeScript and Python, covering basic chat interactions, streaming responses, and advanced multimodal features. Ideal for developers building high-performance, low-latency AI applications using the Groq API.

This guide provides comprehensive instructions for installing and configuring the official Groq SDK in both Python and TypeScript environments. It covers dependency setup, secure API key management using environment variables, and provides code examples to verify a successful connection to Groq's ultra-fast LLM inference API. Essential for initiating any project powered by Groq.