Skill UI

An expert system for designing and implementing advanced AI context architectures. It specializes in integrating intelligent memory systems, vector databases, and knowledge graphs to ensure AI applications maintain coherent, relevant, and scalable state across complex, multi-agent workflows. Essential for enterprise RAG implementation and stateful AI development.

This skill details advanced techniques for enhancing the effective context capacity of LLMs. It outlines four core strategies—Compaction, Observation Masking, KV-Cache Optimization, and Context Partitioning—to prevent context limits from constraining task complexity. By strategically managing token usage, users can reduce operational costs, minimize latency, and implement robust, long-running agent systems for handling large documents or conversations.

This skill set provides advanced, structured strategies for optimizing Large Language Model (LLM) interactions. It covers techniques such as intelligent context summarization, dynamic trimming, context routing, and precise token budget allocation to prevent 'context rot'. It is essential for building robust, long-running, multi-turn conversational AI systems.

Contract Test Creator automatically assists with designing and implementing contract tests, guiding on best practices, producing production-ready code and configurations, and validating results whenever the user invokes contract test creator tasks.

Guidelines for building Convex backends with TypeScript, detailing syntax, validators, schema design, queries, mutations, actions, scheduling, and file storage so you can implement Convex database operations, real-time updates, and cron jobs consistently.

The official SDK for building applications that programmatically interact with GitHub Copilot. It provides comprehensive features including session management, custom tool definition (function calling), real-time streaming, and lifecycle hooks. Supports multiple languages, including Node.js, Python, Go, and .NET, making AI integration seamless across your tech stack.

Framework for improving existing marketing copy through seven sequential sweeps that check clarity, voice, benefits, evidence, specificity, and more while preserving the original message and brand tone.

A comprehensive guide to utilizing a core, token-driven component library and design system patterns. It details best practices for managing UI styles—including spacing, color, and typography—by using semantic design tokens instead of hard-coded values. Ideal for building consistent, scalable, and maintainable user interfaces across different platforms.

Provides targeted guidance for improving LCP, INP, and CLS to boost page experience and search rankings, with checklists, issue breakdowns, and actionable fixes for rendering and interaction bottlenecks.

A comprehensive pattern for building robust and cost-efficient LLM application pipelines. This guide details combining model routing based on task complexity, immutable cost tracking, limited retry logic, and prompt caching to manage API expenditures while maintaining high quality. Essential for production systems handling variable-complexity, high-volume tasks.

A comprehensive guide detailing systematic strategies and patterns for optimizing cloud spending across major platforms including AWS, Azure, and GCP. It covers best practices for rightsizing resources, leveraging reserved instances, implementing lifecycle policies, and setting up robust cost governance, ensuring cost efficiency without sacrificing performance or reliability.

Automated AWS skill that activates when you invoke cost optimization analyzer, offering guided best practices, code/config validation, and recommendations across compute, storage, networking, and serverless domains.