Skill UI

Design and implement conversational AI assistants with context management, integration boundaries, and validation. Provides guidance, best practices, and checklists for building production-ready chatbots and AI-powered applications.

Master comprehensive evaluation strategies for LLM applications, covering automated metrics like BLEU and ROUGE, human evaluation dimensions, and LLM-as-Judge patterns. This skill helps measure performance, compare models, detect regressions, and validate prompt improvements. Includes Python implementation examples for metrics and evaluation suites.

This skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

Curated upstream guidance for Longbridge Research. Provides institutional data, sell-side research, and investment research frameworks including analyst ratings, consensus estimates, financial calendars, shareholder data, insider trades, short selling data, industry rankings, peer group trees, investment idea generation, investment proposals, coverage initiation, competitive analysis, financial planning, DeFi yield analysis, and on-chain data. Use when the user's goal matches the documented workflows.

This skill provides comprehensive guidance on Makepad 2.0's Domain Specific Language (DSL) syntax for building UI code. It covers key rules like property assignment, named instances, merge operators, and registration patterns. Use this when developing or debugging Makepad applications to understand the runtime script_mod! macro and Splash scripting language.

This skill provides guidance on Makepad 2.0's two-layer event system for building UI code. It covers Splash inline handlers like on_click and on_render, and Rust MatchEvent trait methods. Use this when developing Makepad applications to handle user interactions, dynamic rendering, and business logic efficiently.

This skill provides comprehensive guidance for building and debugging user interfaces using Makepad 2.0 widgets. It covers the complete widget catalog including containers, text, buttons, inputs, media, and navigation components. It also includes critical coding rules for layout, styling, and performance optimization to ensure correct UI rendering.

Expert guidance on Makepad event and action handling, covering Event enum variants, Hit processing, widget actions, and patterns for widget-to-parent communication. Suitable for UI interaction, lifecycle, and input event handling in Makepad applications.

Provides expert guidance on Makepad cross-platform development, covering supported platforms, graphics backends, runtime platform detection, conditional compilation, and platform-specific APIs for desktop, mobile, web, and more.

Provides guidance for developing Makepad UI in Rust, covering setup, patterns, shaders, packaging, and troubleshooting. Helps identify relevant tools and workflows for building cross-platform applications.

This skill provides comprehensive methodologies for calculating Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM). It guides users through top-down, bottom-up, and value theory approaches for startup strategy, fundraising, and business planning. Ideal for validating market opportunities and defining realistic growth projections.

Comprehensive hardening guide for Model Context Protocol (MCP) servers, covering transport encryption, mTLS, authentication, authorization, input validation, and audit logging to secure AI agent integrations.