Skill UI

Comprehensive Python toolkit for building, analyzing, and visualizing complex networks; supports algorithms, I/O, generation, and community detection across social, biological, transportation, and citation data.

Provides AI-ready drug discovery datasets, splits, and benchmarks covering ADME, toxicity, DTI, DDI, and molecular generation so researchers can train, compare, and optimize therapeutic ML models with curated splits and oracles.

Provides Nano Banana Pro workflows for research talk slides, covering planning, slide generation, citations, and visual continuity for PowerPoint or LaTeX Beamer.

Guides symbolic mathematics work in Python, covering algebraic simplification, calculus, equation solving, linear algebra, physics, number theory, geometry, and code generation to deliver exact symbolic results instead of numeric approximations.

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 skill provides an end-to-end solution for video and audio content creation. Users can upload videos from various sources (YouTube, local files) and perform advanced operations such as real-time streaming, semantic search, and complex editing (trimming, overlays). Key features include AI-powered transcription, subtitle generation, and the ability to generate diverse media assets like images, music, sound effects, and voiceovers, making it ideal for content creators and media professionals.

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.

Use this skill to automatically generate robust CI/CD pipelines (GitHub Actions, GitLab CI) by analyzing the detected project stack (language, dependencies, tools). It ensures fast baseline setup, repeatable testing stages, and environment-aware deployment workflows. Ideal for onboarding new projects, standardizing multi-repo deployments, or optimizing existing, brittle pipelines.

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.

This comprehensive guide provides step-by-step instructions for integrating the Google Gemini API into applications using Python and Node.js. It covers the entire lifecycle, from basic text generation to advanced use cases like multimodal inputs (text + image), real-time streaming responses, function calling/tool use, and multi-turn chat. Includes best practices for model selection, error handling, and production deployment.

Guided workflow for turning PM notes or rough drafts into compliant repo skills, covering draft generation, validation checks, README updates, and optional packaging so every submission passes the repo standards.