Skill UI

This skill provides strategies and patterns to optimize cloud spending across AWS, Azure, and GCP. It covers visibility, right-sizing, pricing models, and architecture optimization to reduce costs while maintaining performance. Includes specific guidance on reserved instances, spot instances, tagging, and budget alerts.

Master Firebase backend services including Authentication, Firestore, Realtime Database, Cloud Functions, Storage, and Hosting. Learn security rules, data modeling for read-heavy workloads, and cost optimization to avoid pitfalls like expensive reads and query limitations.

This skill evaluates content for AI citability based on research from Princeton and Georgia Tech. It scores content on answer block quality, self-containment, and structural readability to optimize visibility in AI-generated responses. Ideal for SEO and GEO strategies to ensure AI models extract and cite your content effectively.

This skill helps reduce LLM API and infrastructure costs by 50-90% using strategies like model selection, prompt caching, batching, quantization, and self-hosting. It covers cost tracking, right-sizing models for tasks, provider-side caching, and semantic caching to avoid redundant calls. Suitable for developers managing AI spend and optimizing cloud infrastructure.

This skill provides comprehensive techniques for optimizing prompts used with any Large Language Model (LLM). It teaches proven methodologies—including Role definition (R), Context setting (S), Constraints (C), Instructions (I), and Templates (T)—to transform vague inputs into precision-engineered instructions. Users can reliably achieve structured JSON output, implement Chain-of-Thought reasoning, reduce hallucinations, and minimize token usage, ensuring consistent and high-quality results across different AI platforms.

An expert guide for deploying and optimizing Large Language Models (LLMs) entirely on local hardware. Mastering the entire local AI ecosystem, including inference engines like Ollama, vLLM, and llama.cpp. Provides deep knowledge on quantization formats (GGUF, EXL2, AWQ), VRAM calculation, and ensuring privacy-first, offline deployment for state-of-the-art models.

This skill provides quantitative analysis frameworks and CLI indicator scripting via Longbridge. It supports pairs trading, volatility strategies, multi-factor models, and statistical methods like ADF/GARCH. Users can run scripts against K-line data for strategy optimization, hedging, and ML-based prediction without requiring login. Ideal for quantitative finance workflows.

Covers core principles for mobile game development, including touch input handling, battery and thermal optimization, and performance targets. Provides guidance on iOS and Android app store requirements, monetization models, and common anti-patterns to ensure a smooth user experience on constrained mobile platforms.

This skill provides comprehensive strategies and technical blueprints for monetizing digital products, especially SaaS platforms. It covers everything from defining advanced pricing models (freemium, value-based pricing) and optimizing revenue flows (LTV/CAC, churn prevention) to practical Stripe integrations. Use it when you need to set up subscription plans, process webhooks, or implement automated billing cycles for your software.

Expert in Prisma ORM covering schema design, migrations, query optimization, relations modeling, and database operations for PostgreSQL, MySQL, and SQLite. Provides diagnostics, best practices, and prioritized fixes for common issues.

Build financial models, backtest trading strategies, and analyze market data with risk metrics, portfolio optimization, and statistical arbitrage using pandas, numpy, and scipy.

Expert in building Retrieval-Augmented Generation systems for LLM applications. Masters embedding models, vector databases, chunking strategies, and retrieval optimization. Capable of designing retrieval pipelines, implementing hybrid search, and optimizing context windows to ensure high-quality generation from retrieved documents.