Skill UI

This guide details integrating FoundationModels for running Large Language Models (LLMs) directly on the device (iOS 26). It covers advanced patterns including text generation, extracting structured data using @Generable, implementing custom tool calling for domain logic, and streaming responses for real-time UI updates. Key features emphasize strong privacy and offline capability, ensuring no data leaves the device.

This skill acts as a specialized expert for transitioning codebases across various frameworks, languages, versions, and platforms. It generates detailed migration plans, automated migration scripts, comprehensive risk assessments, and rollback strategies. Use it when upgrading technology stacks or moving code between disparate systems to ensure minimal disruption and maintain core functionality.

This orchestrator skill provides comprehensive core principles for game development, covering topics like the Game Loop, design patterns (State Machine, ECS), performance budgeting, and input abstraction. It guides users by routing them to specialized sub-skills based on required platforms (Web, Mobile, PC), dimensions (2D, 3D), and specialty areas (AI, Networking, Art). Ideal for structuring complex game projects from concept to implementation.

This guide provides comprehensive strategies for optimizing API usage and managing expenditure when interacting with AI generation platforms like Gamma. It details implementing credit tracking systems to monitor consumption, employs cost-saving techniques (such as selecting lower-tier images or using templates), and demonstrates setting up proactive budget alerts to ensure spending remains within budget.

A comprehensive guide for deploying applications, especially those integrated with AI services like Gamma, to major cloud environments including Vercel, AWS, GCP, and GitHub. Covers best practices for secret management, environment variable configuration, and setting up CI/CD pipelines across various cloud architectures.

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.

A comprehensive guide to Generative Engine Optimization (GEO), shifting content strategy from traditional SEO (Google ranking) to maximizing citation rates within AI search platforms like ChatGPT, Claude, and Perplexity. Learn how to structure content, build authority, and incorporate schema to be the preferred source for large language models.

A comprehensive guide to diagnosing and resolving common technical issues encountered with the Granola application. Covers fixes for audio capture failures, transcription quality degradation, calendar syncing problems, and integration errors with platforms like Slack and Notion. Includes platform-specific troubleshooting steps for macOS and Windows users.

This skill provides comprehensive setup and automation for integrating Granola with major SaaS platforms, including Slack, Notion, HubSpot, Attio, and Zapier. It automates the synchronization of meeting notes, action item extraction, and follow-up processes across diverse business tools, ensuring seamless cross-platform workflows and maximizing team productivity.

A comprehensive guide detailing the strategy for migrating from competing meeting note tools (such as Otter.ai, Fireflies, Fathom) to a new platform like Granola. This skill covers assessing migration scope, performing source-specific data exports (TXT, JSON, Markdown), selecting the optimal migration strategy (Fresh Start, Selective, Full Archive), and executing a phased transition through parallel runs and final cutover procedures. It ensures historical data preservation and minimizes operational disruption.

A comprehensive reference architecture for deploying meeting intelligence platforms (like Granola) across large organizations. This blueprint details the core data capture pipeline, integration topology using middleware (Zapier), multi-workspace structure (Sales, HR, Engineering), and robust security layers (SSO, AES-256) to ensure automated workflows from meeting to action item across all departments.

Comprehensive guide for deploying applications powered by the Groq inference API. Covers best practices and specific setup instructions for multiple production environments, including Vercel Edge Functions, Google Cloud Run, Docker containers, and other containerized platforms. Essential for setting up robust, low-latency, production-ready AI services.