Skill UI

A comprehensive guide to Test-Driven Development (TDD) for Quarkus 3.x services, focusing on achieving high coverage (80%+). It covers unit testing with Mockito, integration testing of REST endpoints, and advanced testing of event-driven architectures using Apache Camel and RabbitMQ.

An expert AI specializing in Slang shader programming for high-performance graphics and compute applications. This model excels at writing, reviewing, refactoring, and optimizing production-grade code for various graphics stages (vertex, fragment, compute, ray tracing, tessellation). It ensures cross-platform compatibility across major APIs (D3D12, Vulkan, Metal, OpenGL) and supports advanced concepts like generics, parameter blocks, and automatic differentiation. Use this skill when integrating shaders into C++ engines or requiring deep knowledge of low-level GPU pipelines.

This skill provides strategic guidance for CCOs and founders in designing advanced customer success operations. It covers honest retention decomposition (analyzing GRR vs NRR), developing differential customer segmentation strategies based on ICP fit, modeling optimal CS team coverage (pooled vs. named), and mapping the ideal CS organizational structure. Ideal for strategic planning and business resource allocation.

This tool provides a comprehensive, "pipeline-paranoid" interrogation of a sales plan. It analyzes critical growth metrics—including revenue coverage, win rate trends, NRR decomposition, ramp time, and discount discipline—to surface potential operational gaps before they become crises. Use before setting quarterly targets or scaling teams.

This skill automatically generates comprehensive unit tests based on provided source code. It supports multiple programming languages (Python, JavaScript, Java, Go, Rust) and popular testing frameworks (pytest, Jest, JUnit). Use it to improve code coverage, test boundary conditions, and validate error handling efficiently, saving manual testing time.

This skill provides a scaffold for building complex, composable recommendation, ranking, and feed pipelines. It implements the robust six-stage pattern (Source→Hydrator→Filter→Scorer→Selector→SideEffect), which is the industry standard for determining "top K items." Use it for social feeds, content CMS ranking, RAG reranking, or any system needing complex candidate prioritization.

This powerful tool compares identical tables across two SQL Server instances (e.g., Production vs. Staging). It efficiently detects missing rows, extra columns, schema drifts, and data mismatches. Leveraging Python and Apache Arrow for fast columnar data transfer, it provides a comprehensive reconciliation report, making it essential for data migration validation and ETL verification.

A structured playbook for improving the time and space complexity (Big-O) of existing, slow code. This skill guides developers through systematic refactoring, focusing on identifying bottlenecks like nested loops or N+1 queries. It emphasizes applying transformations one at a time, maintaining test coverage, and measuring performance gains to ensure correct and efficient code.

LiteParse is a fast, open-source, and local document parser designed for layout-aware text extraction from PDFs, images, and office files. It outputs structured JSON with bounding boxes and metadata, making it ideal for building advanced RAG systems, citation grounding, and complex data pipelines without needing cloud APIs. Features include OCR, batch processing, and page screenshot capture.

A specialized skill for achieving asymptotic performance gains when classical algorithms are already near optimal. It leverages advanced mathematical techniques and probabilistic data structures (e.g., Bloom Filters, HyperLogLog, FFT, MinHash/LSH) to handle massive datasets (n ≥ 10⁶) by accepting bounded approximations or exploiting deep structural properties. Requires strict adherence to error parameter and complexity justification protocols.

A comprehensive guide for optimizing SEO indexing and managing crawl budget specifically for Next.js applications. Covers fixing Google Search Console coverage errors, implementing proper canonical tags, auditing sitemaps, managing static rendering, and optimizing internal linking for maximum search visibility.

A comprehensive tool for extracting YouTube transcripts, searching videos, browsing channels, and monitoring new uploads. It supports detailed transcript analysis, content summarization, and playlist management by leveraging the TranscriptAPI. Ideal for researchers, content strategists, and market analysts who need structured data from video content without downloading files.