Skill UI

This guide provides a comprehensive local development setup for LLM applications using Langfuse. It enables fast iteration cycles, real-time trace debugging, and hot reloading, making it ideal for developers building and testing complex AI workflows locally. Instructions cover environment setup, advanced SDK usage, and optional self-hosted Docker deployment.

Framework for building stateful, multi-actor AI applications with LangGraph, covering graph construction, reducers, persistence, human-in-the-loop patterns, and ReAct agents suitable for Python production systems.

A comprehensive guide for setting up a local development loop to test AI agent integrations. This skill teaches developers how to build and debug webhook receivers, callback handlers, and associated application code that interacts with a cloud-hosted AI agent (like Lindy). It requires using tunneling services (e.g., ngrok) to expose local endpoints for receiving webhooks and simulating the entire agent-to-application data flow.

This guide provides a comprehensive workflow for setting up a local development environment for Linear integrations. It covers project scaffolding, environment configuration, connection verification using the official SDK, robust integration testing with Vitest, and simulating webhooks using ngrok. Essential for developers building and testing SaaS connections with Linear.

This guide provides a comprehensive local development environment setup for Internationalization (i18n) using Lokalise. It details configuring the project structure, implementing CLI scripts for synchronizing source strings (push) and translations (pull), setting up file watching for hot reloading, and generating mock translations for robust offline testing. Ideal for developers managing multi-language applications.

A comprehensive guide to setting up a local development loop for building and testing MaintainX integrations. This workflow utilizes TypeScript, hot reloading, mock API servers, and automated unit/integration testing. It provides a sandboxed environment for developers to efficiently develop and debug their services.

A comprehensive guide to establishing a fast, reproducible local development lifecycle for Mistral AI integrations. This workflow includes setting up project scaffolding, implementing hot reloading with tsx, performing unit tests with Vitest mocking, and executing live integration tests against the Mistral API. Ideal for setting up reliable AI application development environments.

Enables Claude to monitor and analyze application CPU usage, detect hotspots, inefficient loops and regexes, and offer optimization strategies such as asynchronous processing or algorithmic improvements to boost performance.

Walks through n8n validation feedback, from errors to warnings and suggestions, and explains profiles and loops so you can interpret results, fix config mistakes, and deploy reliably.

This skill guides the creation of structured, importable JSON templates for the Obsidian Web Clipper. It facilitates the analysis of a target website's content structure, including DOM, Schema.org data, and CSS selectors. Users can map complex web elements into a robust template format, incorporating advanced logic like conditionals and loops, ensuring the resulting clipboard data is consistently formatted and ready for immediate use.

This guide establishes a comprehensive and rapid development loop for Obsidian plugins. It covers the entire workflow, from setup (cloning templates, symlinking) to advanced features, including running esbuild in watch mode, achieving hot-reloading (via Ctrl+R or automatic methods), deep debugging with Chrome DevTools, and running unit tests with vitest. Essential for developers seeking fast feedback and reliable plugin iteration.

This provides a local development loop for integrating the OpenEvidence clinical decision support API. Developers can build health-tech tools and quickly iterate using mock evidence queries, citation responses, and clinical summaries. It supports toggling between mock mode for rapid development and sandbox mode for validation against the real platform, ensuring development uses de-identified data.