Skill UI

A comprehensive guide for developing, optimizing, and standardizing skills for AI agents. This resource provides a decision tree for choosing the right architecture (Tier 1-3), incorporating best practices like CSO (LLM SEO) and Anti-Rationalization, and ensuring compliance through rigorous testing and checklists. Essential for robust AI system building.

This skill facilitates the end-to-end deployment of web applications and websites, supporting full-stack architectures including backend APIs, databases, and file storage. It is used when the user wishes to publish a project to a public, live URL, managing the entire deployment lifecycle from template selection to status checking and updates.

PyHealth delivers a full-stack Python toolkit for building, evaluating, and deploying clinical machine learning models, covering EHR datasets, medical coding systems, physiological signals, and healthcare-tailored architectures such as RETAIN, SafeDrug, and Transformer-based pipelines.

Guides using SHAP to explain ML predictions, compute feature importance, generate diagnostic plots, debug models, analyze bias, and compare models across tree, deep, linear, or black-box architectures.

Transforms natural-language prompts into Excalidraw JSON diagrams, supporting flowcharts, relationships, mind maps, architecture, DFD, swimlane, class, sequence, and ER views; ideal when users ask to visualize processes or system structures and need editable Excalidraw files.

Creates and validates Mermaid diagrams across 20+ types, renders SVG/PNG/ASCII, enforces curated styling, and supports batch rendering with themes; ideal for architecture, flow, and ERD visualization requests.

Guides teams through defining page hierarchies, navigation, URL patterns, and internal linking so websites stay intuitive for users while supporting SEO goals and future expansion.

A specialized assistant designed to act as a senior software architect. It critiques code generated by AI tools or rapidly prototyped code, moving beyond simple syntax checks. The auditor identifies deep structural flaws, technical debt, architectural weaknesses, and production risks (e.g., security vulnerabilities, poor error handling, tight coupling) that make code fragile or unsuitable for deployment.

Analyzes a repository to surface architecture, configs, and tasks so engineers, leads, and contractors receive consistent onboarding documentation and setup guidance.

A comprehensive guide covering patterns and architectures for automating code execution using LLMs. It spans simple sequential pipelines (e.g., daily dev scripts) to advanced, RFC-driven multi-agent Directed Acyclic Graph (DAG) orchestration. Ideal for building CI/CD style continuous development pipelines, managing complex state, and automating quality gates without human intervention.

Query InterPro for protein family, domain, and GO annotations via a REST API with Python helpers, enabling function prediction, domain architecture mapping, and evolutionary classification insights for proteomic workflows.

This expert skill reviews the architecture and design of the Bitcoin Lightning Network protocol. It analyzes complex Layer 2 scaling tradeoffs, compares various channel factory approaches, and evaluates critical technical aspects—including trust models, on-chain footprint, consensus requirements, HTLC/PTLC compatibility, liveness guarantees, and watchtower support. Use this when assessing the cryptographic and systemic soundness of L2 blockchain protocols.