Skill UI

Programmatic access to Google NotebookLM via CLI/SDK: create notebooks, add diverse sources, chat about content, generate artifacts, download outputs, and embed into automated workflows.

A comprehensive guide to optimizing website content for modern AI search systems, including ChatGPT, Perplexity, and Google AI Overviews. It covers structural improvements, maximizing citability scores, incorporating multi-modal elements, building brand authority, and implementing technical standards like llms.txt and proper server-side rendering (SSR). Essential for maximizing organic reach in the LLM era.

Self-hosted open-source alternative to Google NotebookLM. Organize research sources, generate AI notes and summaries, create multi-speaker podcasts, chat with documents, and search materials via full-text or vector search with 16+ AI providers.

This skill provides comprehensive deployment guides for Cohere API v2 applications across major cloud platforms including Vercel, Fly.io, and Google Cloud Run. It covers critical aspects like secret management, setting up reliable health checks, optimizing performance, and implementing streaming chat endpoints to ensure production readiness.

Tracks AI share-of-voice for a brand across ChatGPT, Gemini, Perplexity, Google AI Overviews and AI Mode via the SE Ranking API, plus SERP rankings, backlink profiles and competitor gap analysis.

A technical specialization focused on Generative Engine Optimization (GEO). This skill ensures that specific web pages are structured, documented, and optimized for modern AI answer engines (Google AI Overviews, ChatGPT, Bing Copilot). It focuses on technical elements like structured data (JSON-LD), semantic HTML, and robust metadata to maximize discoverability, trustworthiness, and quotability for AI consumption, rather than traditional SEO ranking.

A comprehensive tool to evaluate a brand's presence and citation accuracy across major AI answer engines, including ChatGPT, Gemini, Perplexity, and Google AI Overviews. It analyzes how the brand is described and recommended by various AI platforms, providing a structured audit report and an optimization playbook to improve search visibility.

Provides advanced strategies for optimizing content and brand presence for generative AI search platforms (AEO/GEO). Covers AI Visibility, Citation Tracking, Entity Consistency, and Knowledge Graph optimization across tools like ChatGPT, Gemini, and Google AI Overviews. Essential for brands adapting to modern AI search experiences.

Expert guide for the Gemini Notebook (formerly NotebookLM) CLI and MCP server. Manage notebooks, add sources from URLs, YouTube, text or Google Drive, generate podcasts, reports, quizzes and mind maps, plus research, chat and workflow automation.

This skill enables comprehensive market research by leveraging Apify Actors to extract data from platforms like Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor. It supports analyzing market conditions, geographic opportunities, pricing strategies, consumer behavior, and product validation. Users can select specific actors for tasks such as market density, geospatial analysis, trend data, or hospitality insights. The workflow involves identifying research needs, fetching actor schemas, configuring output formats (CSV, JSON, or chat), and summarizing findings. It is ideal for g...

This skill leverages Apify Actors to discover and track emerging trends across major social media platforms including Google Trends, Instagram, Facebook, YouTube, and TikTok. It enables users to extract data for content strategy by selecting specific actors for search trends, hashtags, visual analysis, or engagement metrics. The workflow involves fetching actor schemas, configuring output formats (CSV, JSON, or chat), and summarizing key insights to inform marketing and content decisions.

This comprehensive guide covers all aspects of integrating the Google Gemini API into your applications using Python or Node.js. It details basic text generation, advanced multimodal inputs (text, image, audio), streaming responses, function calling/tool use, multi-turn chat implementation, and production best practices like model selection and robust error handling.