Skill UI

This specialized skill analyzes content against Google's E-E-A-T framework (Experience, Expertise, Authority, Trust). It identifies missing credibility signals, suggests improvements, and generates actionable strategies for building deep topical authority. Ideal for optimizing content, especially for YMYL (Your Money Your Life) topics, ensuring maximum search engine trust and visibility.

This specialized skill generates comprehensive, best-practice SEO metadata packages, including optimized titles, compelling descriptions, and structured URLs. It ensures strict compliance with character limits (e.g., 150-160 characters) while strategically integrating primary and secondary keywords, emotional triggers, and clear CTAs. Use this when launching new content or needing A/B test variations to maximize search visibility and click-through rates across platforms.

This specialized skill guides users in formatting and structuring content to maximize its eligibility for featured snippets and rich results across Search Engine Results Pages (SERP). It focuses on best practices for Q&A format, list generation, and comparative tables, ensuring content is highly concise, direct, and easily digestible by search algorithms.

This skill analyzes and optimizes the structural integrity of web content to maximize SEO performance. It provides expert guidance on creating search-friendly information architecture, including optimizing header hierarchies (H1-H6), suggesting relevant schema markup (e.g., FAQ, HowTo), and identifying crucial internal linking opportunities. Use it to build robust, highly scannable, and authority-driven content blueprints.

Serve production-grade LLM APIs with vLLM, leveraging PagedAttention, continuous batching, quantization, and tensor parallelism to maximize throughput while keeping latency, GPU usage, and scalability under control for OpenAI-compatible deployments.

A specialized reverse-engineering skill designed to extract comprehensive functional and non-functional specifications from existing, undocumented, or legacy codebases. It operates by analyzing code structure, tracing data flows, and identifying observable behaviors. The output is structured using EARS (Easy Approach to Requirements Syntax), providing clearer requirements documentation, architectural diagrams, and dependency maps for onboarding or system modernization.

This comprehensive checklist guides the secure deployment and hardening of a Supabase project for production use. It covers critical security measures such as enforcing Row Level Security (RLS), separating client and service keys, optimizing connection pooling via Supavisor, setting up Point-in-Time Recovery (PITR) backups, and configuring network restrictions. Use this guide before launching or for conducting security audits to ensure maximum stability and security.

Automates Taxjar operations through Composio's toolkit using Rube MCP by discovering current tool schemas, ensuring an active connection, and executing workflows with schema-compliant arguments and memory.

This skill provides advanced guidelines for designing robust and effective tools specifically for autonomous AI agents. It shifts the focus from traditional developer APIs to contracts optimized for Language Models (LLMs). Key topics covered include treating tool descriptions as prompt engineering, implementing namespacing, applying the Consolidation Principle, and utilizing Architectural Reduction patterns (like file system access) to maximize agent reliability and workflow complexity.

This robust tool provides comprehensive tracking and analysis for your cryptocurrency holdings. It calculates real-time portfolio valuations using external APIs (like CoinGecko), analyzes asset allocation, tracks Profit & Loss (P&L), and issues concentration risk alerts. Ideal for users who need to check total portfolio value, view detailed holdings, analyze diversification, or export structured data for tax reporting and record-keeping.

A comprehensive foundation skill for monitoring cryptocurrency markets. It provides real-time quotes, 24-hour change metrics, and deep historical price data for over 10,000 coins. Users can track specific symbols, view predefined watchlists (e.g., DeFi, Top 10), or export detailed OHLCV data in CSV format. This skill serves as the foundational data layer for crypto portfolio management, tax calculation, and DeFi analysis applications.

Provides production-ready Megatron-Core workflows for training 2B–462B parameter LLMs with tensor/pipeline/expert/context parallelism, maximizing GPU efficiency on H100 clusters.