Skill UI

Geniml is a comprehensive Python package designed for applying machine learning techniques to genomic interval data stored in BED files. It provides advanced methods like Region2Vec, BEDspace, and scEmbed to learn embeddings for genomic regions, single cells, and metadata. Use it for dimension reduction, clustering, similarity searches, and sophisticated bioinformatic analyses in genomics. Core functionalities include: learning region embeddings (Region2Vec), joint embeddings of regions and metadata (BEDspace), single-cell chromatin accessibility embedding (scEmbed), and building consensus...

This comprehensive tool guides the systematic creation of detailed technical specifications. It orchestrates the entire design lifecycle, including context loading, deep discovery and analysis (tailored for new features, extensions, or simple additions), synthesis using established design principles, and generating a boundary-first, structured design draft. Ensures all requirements are mapped to explicit technical components.

This skill analyzes the implementation gap by comparing approved feature requirements against the existing codebase, architecture, and context. It helps identify missing capabilities, potential integration challenges, and necessary technical research areas. The output provides multiple viable implementation options and a comprehensive analysis report, guiding the transition from requirements definition to technical design.

Defines a Markdown/Mermaid-first documentation skill for scientific and technical writing, providing diagram standards, 24 reference types, and templates so every report, README, or analysis stays text-first, versionable, and visualization-ready.

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 frontend engineers specializing in shadcn/ui. Learn best practices for component discovery, installation, and deep customization using Tailwind CSS and Radix UI. This resource covers project setup, component architecture, and advanced styling techniques for building robust, owned, and highly customizable applications.

This skill guides AI agents to handle complex technical tasks with maximum precision and minimal computational overhead. It implements adaptive verbosity rules, sophisticated input filtering (for logs, source files, VCS, and payloads), and surgical output generation. It ensures context-window awareness, structured reasoning, and adherence to best practices for coding, debugging, and architecture analysis.

This skill acts as a comprehensive Music Learning Coach, guiding users through the full spectrum of music education. It covers fundamental music theory (scales, harmony), structured instrument practice routines, advanced ear training techniques, performance skills, and deep dives into music history. Ideal for beginners and advanced learners looking to build a solid, well-rounded understanding and practical ability in music.

This skill generates comprehensive and structured requirements documents for a new specification. It systematically aggregates context from project files, business rules, and technical constraints, ensuring all generated requirements focus on user-observable behavior (WHAT) rather than implementation details (HOW). It follows established standards like EARS format and includes a rigorous review gate to ensure scope clarity and completeness.

This skill provides an interactive, comprehensive quality review for technical design documents. It systematically validates a feature's readiness for implementation by assessing critical issues, identifying strengths, and providing a clear GO/NO-GO decision with actionable next steps. Ideal for ensuring architectural soundness and catching risks early in the development lifecycle.

Provides technology-agnostic guidance for architecting and reviewing modular systems. This skill covers core architectural principles such as bounded contexts, state isolation, explicit contracts, and failure containment. Use it when determining service boundaries, assessing coupling between domains, or designing new greenfield architectures without assuming a specific framework, language, or repository structure.

A comprehensive guide for developers to optimize performance when integrating Adobe APIs (Firefly, PDF, Photoshop). Techniques covered include implementing token caching, parallelizing asynchronous job submissions, leveraging response caching (LRU), and optimizing connection handling to minimize latency and maximize throughput.