Skill UI

This guide teaches how to optimize website content to be discoverable, extractable, and citable by modern AI systems, including Google AI Overviews, ChatGPT, Perplexity, and Claude. Focuses on structural improvements (tables, FAQs, structured data) to ensure your content is selected as a source in AI-generated answers, moving beyond traditional keyword ranking.

Comprehensive guide for configuring Bring Your Own Key (BYOK) for major AI providers, including OpenAI, Anthropic, Google Gemini, Azure, and custom endpoints. This allows users to bypass default quotas, manage costs directly with the source provider, and utilize a wide range of specialized models within the Cursor IDE. It covers setup steps, security best practices, and cost monitoring strategies.

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 skill leverages Google Gemini's advanced image generation model to create high-quality, context-specific visuals. It is essential for developers needing placeholder images for UIs, generating detailed diagrams for technical documentation, or visualizing abstract concepts, logos, and assets across cross-platform projects (Windows, macOS, Linux).

This skill provides deep integration with Google NotebookLM, enabling users to query uploaded documentation using Gemini. It ensures source-grounded, citation-backed answers, significantly reducing hallucinations. Features include managing the notebook library (add, list, search), handling authentication, and implementing a structured follow-up mechanism for comprehensive research.

Runs external LLM CLIs (OpenAI Codex or Google Gemini) to review uncommitted changes, branch diffs, or specific commits, providing an independent second opinion before merges or releases.

This comprehensive guide provides step-by-step instructions for integrating the Google Gemini API into applications using Python and Node.js. It covers the entire lifecycle, from basic text generation to advanced use cases like multimodal inputs (text + image), real-time streaming responses, function calling/tool use, and multi-turn chat. Includes best practices for model selection, error handling, and production deployment.

Guides teams through auditing AI visibility, restructuring content into extractable answers, and monitoring citations so that ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini, and Copilot cite your pages instead of only ranking them.

A specialized skill for generating hyper-realistic, humanized images using Google AI Studio (Gemini). It simulates the imperfections of real photography—such as natural lighting, slight camera shake, and depth of field—to create content that looks genuinely captured by a smartphone. Ideal for creating high-quality assets for social media (influencer style) or educational materials.

This advanced GEO-first tool performs comprehensive audits designed for the modern AI search landscape (ChatGPT, Gemini, Google AI Overviews). It moves beyond traditional SEO, assessing citability scoring, E-E-A-T, technical foundations, structured data validation, and brand authority signals. It provides actionable, client-ready reports to ensure maximum visibility in AI-driven search traffic.

Framework for auditing and optimizing GEO content for each AI search platform, scoring Google AI Overviews, ChatGPT, Perplexity, Gemini, and Bing Copilot with tailored checklists and action steps.

Connects to Google NotebookLM to query your uploaded documentation via Gemini’s source-grounded answers, automating authentication, notebook management, and question workflows through the provided run.py wrapper.