Skill UI

This skill acts as a professional social media strategist and content writer. It generates high-quality, engaging, and SEO-optimized posts tailored specifically for platforms like Instagram, LinkedIn, and Facebook. By incorporating structured writing rules (Hook, Value, CTA) and adjusting tone and style for each platform, it helps users transform basic keywords and topics into actionable, audience-focused content that drives engagement and growth.

Use the StackBlitz SDK to seamlessly embed live, interactive code playgrounds (WebContainers) directly into documentation, blog posts, or tutorials. This method allows users to view and experiment with code examples (e.g., React, TypeScript) without leaving the current page, making tutorials and documentation highly engaging and functional. Supports embedding from GitHub repositories or creating inline projects.

This guide details how to install and configure the WebContainer API, enabling client-side Node.js execution directly in the browser. It also provides instructions for integrating the StackBlitz SDK, which is used for embedding highly interactive code editors into web applications. The guide covers necessary dependency installations, code examples, and crucial HTTP header configuration (COOP/COEP) required for cross-origin isolation and secure operation.

This assistant helps generate clear, concise, and highly structured reports for stakeholders and leadership. It guides users in creating professional status updates, progress summaries, and executive reports, ensuring all key metrics, risks, and necessary actions (asks) are highlighted for maximum clarity and impact.

Generates structured DESIGN.md files that serve as a single source of truth for AI-powered screen generation (Google Stitch). This skill translates complex, anti-generic design directives into precise semantic rules, covering typography, color calibration, motion physics, and layout principles to enforce a premium, high-agency UI/UX standard. It ensures outputs are sophisticated and avoid common AI design clichés.

TileDB-VCF is a high-performance library built on TileDB's sparse array technology, designed for the efficient storage and retrieval of large-scale genomic variant-call data (VCF/BCF). It supports scalable, incremental ingestion of single-sample VCF/BCF files and enables highly efficient parallel querying across vast genomic regions and multiple samples. This tool is essential for building robust population genomics databases, conducting GWAS, and performing large-scale cohort studies.

This skill provides a production-grade, containerized integration service for connecting to the Together AI platform. It facilitates high-performance inference, fine-tuning, and model deployment across over 100 open-source models using Together's OpenAI-compatible API. Includes comprehensive Docker setup, environment variable management, health checks, and zero-downtime rolling update strategies for robust, real-time LLM serving.

A comprehensive guide and implementation demonstrating how to handle API rate limits when interacting with AI services like Together AI. It details the token bucket algorithm for client-side throttling and provides robust retry mechanisms (exponential backoff) to manage 429 (Rate Limit Exceeded) and 5xx server errors, ensuring stable, high-throughput batch processing.

A comprehensive reference architecture for building scalable, cost-effective, and robust AI services. This system manages the full AI lifecycle, including intelligent model routing (for quality/cost trade-offs), response caching (using Redis), asynchronous batch processing, and fine-tuning pipeline management via Together AI's OpenAI-compatible API. Ideal for enterprise applications requiring high availability across multiple open-source models.

This guide provides advanced search strategies for tracking Asian music, including K-pop, J-pop, and Filipino genres. It details how to construct highly specific queries by incorporating regional keywords, understanding idol comeback cycles, and utilizing cultural details (such as zodiac or national identity) to narrow down search results and avoid generic noise.

This skill provides a structured framework for capturing, organizing, and maintaining persistent facts about the user. By segmenting facts into topic-specific files (e.g., coding preferences, tech stack, goals), it creates a reliable, objective knowledge base. This structure is crucial for AI agents and applications to achieve highly personalized interactions and provide accurate context.

This meta-skill establishes a rigorous and mandatory workflow for all AI agent interactions. It dictates that before generating any response, the agent must check for and invoke all relevant specialized skills, regardless of the perceived complexity or simplicity of the user request. It defines strict rules for skill prioritization, establishes user instructions as the highest authority, and outlines structured processes for various development scenarios, ensuring systematic and complete task execution.