Skill UI

This minimal working example demonstrates core API interactions with Instantly.ai v2. It shows how to list active campaigns, check email account health/vitals, and pull detailed campaign analytics (open rate, reply rate). Ideal for developers setting up new integrations or testing API setup.

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 provides minimal working examples demonstrating the LangChain Expression Language (LCEL). It shows how to chain together diverse components—such as prompts, LLMs, and output parsers—using simple pipe syntax (e.g., .pipe() or |). Ideal for developers starting a new LangChain project, understanding core AI workflow patterns, or mastering structured data output.

A minimal example demonstrating how to implement basic tracing using the Langfuse SDK. It illustrates the hierarchy of traces, spans, and generations (LLM calls), providing code examples in TypeScript and Python for easy setup and integration testing.

This guide demonstrates the basic workflow for building an AI agent using a webhook trigger. The agent receives structured data (payload), utilizes an LLM to extract key information and generate a concise summary (summarization step), and finally executes an action by posting the summary to Slack or sending an email. Ideal for beginners learning about AI agent architecture, testing data flow, and implementing simple automated system notifications.

This guide details how to use the official @linear/sdk to interact with the Linear project management API. It covers performing core CRUD operations, such as creating new issues, listing teams, querying issue states, and performing raw GraphQL requests. Ideal for developers needing to integrate Linear into a custom workflow, test API connectivity, or learn foundational automation patterns.

This comprehensive guide provides an end-to-end walkthrough for integrating with the Lokalise platform. It demonstrates core localization tasks, including listing projects, creating new multilingual projects, adding translation keys, and updating translations for multiple languages using both the Node SDK and the CLI. Ideal for developers establishing robust internationalization (i18n) pipelines.

This comprehensive guide demonstrates the fundamental workflow for creating, retrieving, and managing work orders using the MaintainX REST API. It provides actionable code examples using both cURL for quick testing and TypeScript for robust client implementation. It is essential for developers integrating a CMMS system or testing basic API connectivity.

A comprehensive, hands-on guide to building a minimal working Obsidian plugin. This skill demonstrates the five core building blocks of any Obsidian plugin, including defining typed settings, creating various command types (palette, editor, callback), implementing modals, and utilizing status bar updates. Perfect for developers new to the Obsidian API or those needing a structured way to learn core plugin patterns.

Provides a minimal working example demonstrating how to integrate Perplexity's API for web-grounded answers. Learn to perform advanced searches, retrieve cited sources, and handle features like domain filtering and streaming using both TypeScript and Python. Ideal for integrating real-time, source-backed search functionality into applications.

This skill guides users through building a minimal yet comprehensive working application on the Replit platform. It demonstrates how to integrate and use core platform services such as the built-in Key-Value Database, Object Storage for file handling, user Authentication, and standard web frameworks (Express/Flask). Use this guide when starting a new Replit project or when learning the foundational infrastructure services provided by the platform.

This skill provides a comprehensive walkthrough for setting up and testing Sentry error monitoring using both Node.js and Python SDKs. It demonstrates how to capture various event types, including simple messages and full exceptions, and crucially, how to enrich these events with user context, searchable tags, and detailed breadcrumbs. This is essential for verifying robust error logging and monitoring in a production environment.