Skill UI

This skill is designed for understanding complex database structures. It allows users to list all available tables, intelligently filter relevant tables based on natural language queries, retrieve detailed schemas (columns, types, primary/foreign keys), and map inter-table relationships. It culminates in generating the M-Schema format, which is essential for accurately preparing the context needed for advanced SQL query generation.

This technique is designed for entity recognition and hypothesis generation when identifying Indian or Bollywood actors based on indirect clues. Instead of running broad searches, users should hypothesize a small set of candidate names (1-3) using the provided clues (e.g., awards, family history, controversies). Subsequently, targeted verification searches must be executed for each constraint against the candidate names to confirm the correct identity.

Use the esm Python SDK with ESM3 and ESMC for protein sequence generation, embeddings, function conditioning, structure prediction, inverse folding, and Forge/Biohub inference workflows.

Generate and edit images using OpenRouter's AI models like Gemini and Seedream. Supports photos, illustrations, logos, and concept art via command line. Requires API key for generation tasks.

Plans, audits, and safely runs ChicagoHAI HypoGeniC/HypoRefine workflows for LLM-assisted hypothesis generation from labeled text datasets, with pinned installs, config validation, dataset leakage checks, and bounded local review before any model call.

This skill helps formulate evidence-bounded scientific questions and candidate hypotheses. It turns observations into transparent, testable research plans without treating hypotheses as facts. It distinguishes between observations, mechanisms, and predictions, ensuring rigorous research design and safety compliance.

This skill acts as an elite Art Director for generating premium, highly actionable, and structurally sound frontend design references. It moves beyond generic AI aesthetics by enforcing principles like strong hierarchy, generous spacing, and image-led composition. Ideal for creating realistic, development-ready concepts for landing pages, hero sections, and multi-section websites.

Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Includes layout design, color schemes, multi-column formats, figure integration, and AI-powered visual element generation for conference presentations and academic posters.

Python cheminformatics toolkit for fine-grained molecular control: SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D coordinate generation, similarity, reactions, and visualization.

Facilitates evidence-aware scientific ideation with independent generation, structured discussion, explicit assumptions, transparent evaluation, adversarial review, and decision logs. Use for early-stage research brainstorming and prioritizing candidate directions.

SymPy is a Python library for exact symbolic mathematics, enabling algebra, calculus, equation solving, and linear algebra without numerical approximations. Ideal for physics calculations, code generation, and generating LaTeX output. Use when precision matters over speed.

TorchDrug is a modular PyTorch library for graph learning tasks including molecular property prediction, molecule generation, and knowledge graph reasoning. It provides datasets, models, and training engines for building workflows in computational chemistry and biology. Ensure compatibility with PyTorch 1.8-2.0 and Python 3.7-3.10 before implementation.