Skill UI

Astro is a modern web framework designed specifically for building high-performance, content-heavy websites like blogs, documentation sites, and portfolios. Its core innovation is the Islands Architecture, which ships zero JavaScript by default, drastically improving performance and Core Web Vitals. It supports multi-framework components (React, Vue, Svelte) in a single project, making it ideal for content developers prioritizing speed and flexibility.

Automatically analyzes unfamiliar codebases to generate a comprehensive, structured onboarding guide. It systematically detects package manifests, framework fingerprints, architecture maps, key entry points, and coding conventions. Ideal for new developers joining a project or setting up a repository for the first time.

This tool audits the token consumption across all components (agents, skills, rules, MCP servers) within a Claude Code session. It analyzes token overhead, identifies bloat (e.g., overly long descriptions, redundant components), and generates a detailed context budget report. Use it to maintain optimal context window usage, improve performance, and prevent context saturation.

Explains any startup equity, legal, or term sheet question—SAFE notes, convertible rounds, and preferred stock—while covering both investor and founder lenses and flagging red flags or negotiable points.

Hono is a minimal and ultrafast web framework built entirely on Web Standards (Request/Response/fetch). It allows developers to build high-performance APIs and full-stack applications that run seamlessly across multiple environments, including Cloudflare Workers, Deno, Bun, and Node.js. It is ideal for edge deployment, Backend for Frontend (BFF) layers, and type-safe backend services.

Connects to the MAXIA AI-to-AI marketplace on the Solana blockchain. This tool allows users to discover, buy, and sell AI services directly between decentralized agents. Features include comprehensive crypto intelligence, such as sentiment analysis and trending data; DeFi yield tracking; Web3 wallet security analysis (e.g., rug detection); and real-time GPU pricing, making it a comprehensive hub for Web3 AI interactions.

A comprehensive guide covering best practices for building and debugging Nuxt 4 applications. It details patterns for ensuring hydration safety, optimizing data fetching with `useFetch` and `useAsyncData`, managing complex routing rules, and implementing lazy loading for superior performance across SSR and client-side environments.

A comprehensive 7-stage workflow designed to manage, audit, and optimize GitHub repositories. This tool automates critical tasks including identifying hardcoded secrets, cleaning up junk files, performing deep documentation reviews, benchmarking against competitors, and validating the final state, transforming messy codebases into production-ready assets.

A Manus-style file planning system for breaking down complex tasks, tracking progress, and preserving context across sessions. It creates task_plan.md, findings.md, and progress.md for multi-step projects and research workflows.

polars-bio accelerates genomic interval math and bioinformatics I/O by combining Polars, Arrow, and DataFusion to handle BED/VCF/BAM/GFF/FASTA streams, SQL queries, and cloud storage with overlap, coverage, and nearest APIs plus streaming fallbacks.

PydanticAI is a robust Python framework that integrates Pydantic's type-checking and validation capabilities into Large Language Models (LLMs). It allows developers to build production-ready AI agents that guarantee structured, validated outputs, moving beyond simple raw strings. Key features include supported tool calling, dependency injection for testability, and multi-model compatibility across major providers like OpenAI, Anthropic, and Gemini. Use this when reliability and correct data structure are paramount.

This skill provides guidance on implementing common architectural patterns and best practices within the PyTorch framework. It is designed for developers building sophisticated deep learning models, helping to improve structure, efficiency, and code maintainability when working with neural networks.