Skill UI

TorchDrug is a PyTorch-native toolbox for building graph neural networks tailored to molecules, proteins, and biomedical knowledge graphs, covering property prediction, generation, retrosynthesis, and knowledge graph reasoning with curated datasets and models.

A comprehensive skill for leveraging massive pre-trained transformer models across diverse AI domains, including Natural Language Processing (NLP), Computer Vision (CV), and Audio. Use this skill for advanced tasks such as text generation, classification, question answering, summarization, object detection, and model fine-tuning on proprietary datasets. It provides streamlined pipelines and granular control for deployment.

This comprehensive tool enables automated lead generation by scraping contact and business data from numerous online platforms. It leverages specialized Apify Actors to extract diverse prospects, including business details, creator profiles, and contact information from sources like Google Maps, Instagram, TikTok, and Facebook. It is ideal for market research, lead qualification, and building robust outreach databases.

This powerful tool helps translate natural language requirements into robust, normalized relational database schemas. It can generate comprehensive schema designs, complete with relationships, constraints, and advanced architectural concerns like multi-tenancy, soft deletes, and audit trails. Furthermore, it automates the generation of database migrations (supporting Prisma, TypeORM, Alembic, etc.), corresponding type definitions (TypeScript/Python), seed data, and Entity-Relationship Diagrams (ERD) using Mermaid.

A comprehensive tool for generating, iterating, and scaling high-performing ad copy across major paid advertising platforms (Meta, Google, LinkedIn, etc.). Use this skill when you need to develop ad headlines, body copy, or creative variations, optimizing content based on funnel stage (Awareness, Consideration, Decision) and existing performance data to maximize conversion rates and pass platform reviews.

Master the creation and manipulation of 3D geometry within the Three.js framework. This guide covers built-in primitive shapes (Box, Sphere, Cylinder), advanced procedural geometries (Extrude, Tube, TorusKnot), and text visualization. Crucially, it details the use of BufferGeometry, allowing developers to store vertex, normal, UV, and color data in optimized typed arrays for high-performance rendering and custom mesh construction.

Comprehensive guide to LLM Operations (LLMOps). Covers advanced topics like Retrieval-Augmented Generation (RAG), vector database management (Pinecone, Chroma), embeddings, fine-tuning, prompt engineering, and cost optimization. Essential for bridging the gap between AI prototypes and reliable, scalable, production-grade AI systems.

An expert guide for developing production-grade AI applications, chatbots, and generative UIs using the Vercel AI SDK, Next.js, and React. Covers core concepts including streaming text (`streamText`), managing chat state (`useChat`), implementing complex tool/function calling, and ensuring robust structured data generation (JSON schemas) across multiple LLM providers.

This skill extracts up to 50 highly relevant, SEO-friendly keywords and tags from any given text. It is designed to identify core topics, domain terminology, and potential search phrases, formatting them into a strict, comma-separated list suitable for metadata generation, tagging, or search engine optimization (SEO). Use it whenever you need to optimize content for search engines.

This skill analyzes DNS query logs to detect sophisticated threats such as data exfiltration via DNS tunneling, Domain Generation Algorithm (DGA) usage, and covert Command and Control (C2) channels. It utilizes advanced techniques like entropy analysis, query volume anomaly detection, and subdomain length analysis within SIEM platforms, helping SOC teams identify threats that bypass traditional network security controls.

A comprehensive guide for analyzing PCAP files captured during malware execution. It demonstrates advanced techniques using Wireshark, Zeek, Suricata, and Python (scapy) to identify Command and Control (C2) communications, data exfiltration channels, Domain Generation Algorithms (DGA), and periodic beaconing patterns. Essential for malware reverse engineering and network threat detection.

This skill fetches the latest, live documentation and code examples for specific libraries and frameworks (e.g., Next.js, React, Prisma). Instead of relying on static or outdated training data, it utilizes the Context7 MCP to provide accurate, up-to-date answers for setup questions, API references, and code generation based on current best practices.