Skill UI

Manage Zotero reference libraries programmatically with the pyzotero Python client and Zotero Web API v3. Retrieve, create, update and delete items, collections, tags and attachments; search libraries and export BibTeX or CSL-JSON citations for research automation workflows.

Provides comprehensive guidance on determining the optimal scaling strategy for Qdrant vector databases. Covers when to transition from vertical to horizontal scaling, how to select the right number of nodes and shards, and best practices for setting replication factors to ensure zero-downtime operation and fault tolerance. Also details proper shard management and common scaling pitfalls to avoid.

A comprehensive guide for optimizing query latency in Qdrant. This resource explains advanced performance tuning techniques, focusing on critical resource management like RAM utilization, segment count adjustments, and HNSW parameter tuning. It details strategies for scaling, quantization, and hardware considerations (e.g., local NVMe) to ensure consistently low-latency search performance, and outlines common pitfalls to avoid.

A comprehensive guide for diagnosing production performance issues in Qdrant vector databases. Learn how to systematically check the optimizer status, analyze high memory usage (OOM crashes), and troubleshoot slow query latencies using key metrics and dedicated API endpoints. Essential for maintaining optimal operational health.

Qiskit is a Python framework for building, simulating, and executing quantum circuits. It supports local simulation, noisy simulation, and IBM Quantum hardware execution. Users can utilize V2 primitives like Sampler and Estimator for variational algorithms and quantum machine learning tasks.

Simulate closed and open quantum-system models using QuTiP 5. Supports deterministic, trajectory, and steady-state workflows for local quantum-dynamics work requiring explicit physical assumptions and numerical convergence.

Generate production-quality React components and UIs using the specialized Rayden UI component library and Tailwind CSS. This skill ensures that all generated code strictly adheres to a defined design system, including correct component usage, design tokens, prop validation, and established layout patterns. Ideal for scaffolding complex pages like dashboards, login forms, and data tables while maintaining premium aesthetics and consistency.

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.

This specialized skill automates the process of converting visual designs (from Stitch) into high-quality, modular React and Vite components. It adheres to modern frontend best practices, enforcing logic isolation via custom hooks, data decoupling using mock data files, and ensuring type safety with TypeScript interfaces. The workflow includes automated asset fetching, style mapping (Tailwind), and rigorous validation cycles to produce production-ready, maintainable code.

Write competitive research proposals for NSF, NIH, DOE, DARPA, and NSTC. Covers agency-specific formatting, review criteria, budgets, broader impacts, significance, innovation, and compliance.

Compile verified scholarly evidence and references for scientific manuscripts or research briefs. Runs multi-pass Parallel Search with Extract source verification, ranked deduplication, and optional Research/Chat backends to deliver a manuscript-ready research packet targeting 60 unique references.

Scanpy is a scalable Python toolkit for single-cell RNA-seq analysis, covering quality control, normalization, dimensionality reduction, clustering, and visualization. It supports converting R formats to h5ad and includes ready-to-run CLI scripts for end-to-end workflows, making it ideal for exploratory scRNA-seq analysis and publication-quality plotting.