Skill UI

This skill aggregates public sentiment and discussion about any given topic from the last 30 days. It pulls comprehensive data and engagement metrics from major sources including Reddit, X, YouTube, TikTok, Hacker News, and general web sources. It is invaluable for market research, competitive analysis, or understanding rapidly changing cultural and technological trends.

Automates News API operations via Rube MCP/Composio by first discovering tool schemas, confirming connections, and executing RUBE_MULTI_EXECUTE_TOOL flows with schema-compliant arguments for repeatable news workflows.

This skill enables the development of robust, event-driven pipelines interacting with the Perplexity Sonar API. Since Perplexity lacks native webhooks, this system simulates event patterns using advanced techniques: Streaming Server-Sent Events (SSE) for real-time data, job queues (like BullMQ/SQS) for asynchronous batch research, and cron-triggered monitoring for scheduled news and trend alerts. It provides patterns for building complex, reliable, and scalable AI applications.

Parallel Web Research skill orchestrates Parallel Chat and Extract APIs to search the internet, perform deep intelligence work, and craft cited summaries, with model controls, JSON outputs, and citation verification for market, news, technical, and general queries.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

This workflow utilizes the SerpApi to perform advanced, multi-engine searches across platforms including YouTube, Bing, Google News, Google Shopping, and Google Maps. It is essential for data scraping, SEO research, and building comprehensive search features that require aggregating results from diverse sources beyond standard Google search. Use it to collect videos metadata, product pricing, local business details, and news articles efficiently.

Utilize this tool to programmatically access and parse search engine result pages (SERP) data from multiple sources, including Google, Bing, YouTube, and Google News. It returns comprehensive, structured JSON data, allowing developers and marketers to extract organic results, knowledge graph entries, ads, and local information for advanced SEO analysis, market research, and data science projects. Supports both Python and Node.js implementations.

This guide outlines production-ready patterns for integrating SerpApi into robust search services. It covers essential best practices, including defining typed result interfaces for type safety, implementing LRU caching to conserve API credits, and building multi-engine abstractions to handle various search types (web, news, images). It also demonstrates asynchronous search processing for non-blocking operations.

A comprehensive skill that automates the entire process of creating professional, production-ready thumbnails for articles or newsletters. It reads the article copy, proposes multiple composition concepts (e.g., bold claim, conceptual object), writes tailored prompts, calls the Gemini API for image generation, and evaluates the results using computer vision, returning ranked candidates with rationale.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

This skill connects to the public, read-only AI HOT API to retrieve the latest Chinese AI news, curated selections, hot topics, and daily reports. It is essential for users needing up-to-date information on large language models, industry breakthroughs, or major AI events, ensuring results are based on real-time data rather than pre-trained knowledge.