Skill UI

Selects game engines and frameworks by platform, genre, and architecture (full canvas shell vs hybrid DOM shell + guest viewport). Covers Phaser, PixiJS, Kaplay, Canvas/WebGL, Three.js, Babylon.js, Godot, Unity, Ink, Twine. Use when choosing a stack or comparing runtimes before implementation.

Expert hybrid cloud architect for designing multi-cloud solutions across AWS, Azure, GCP, and private clouds, covering connectivity, security, cost, and observability.

Configure secure, high-performance connectivity between on-premises and cloud environments using VPN, Direct Connect, and ExpressRoute. This skill covers AWS, Azure, and GCP integration, routing, security, and high availability patterns for hybrid infrastructure.

This skill provides structured patterns for combining vector similarity search with traditional keyword-based search. It is essential for building advanced Retrieval-Augmented Generation (RAG) systems, sophisticated search engines, or any retrieval task requiring high recall. Use this when pure semantic understanding is insufficient, and precise matching of specific terms (like names or codes) is necessary.

This skill provides sophisticated project estimation by adapting to human-only, hybrid, or agent-first development modes. It uses research-backed PERT statistics and confidence bands (P50, P75, P90) to forecast development timelines for tasks, backlogs, and capacity planning. It continuously calibrates estimates based on actual completion data, ensuring accuracy in AI-assisted and hybrid development environments.

Expert in building Retrieval-Augmented Generation systems for LLM applications. Masters embedding models, vector databases, chunking strategies, and retrieval optimization. Capable of designing retrieval pipelines, implementing hybrid search, and optimizing context windows to ensure high-quality generation from retrieved documents.

This comprehensive workflow guides the end-to-end implementation of Retrieval-Augmented Generation (RAG) systems. It covers critical stages, including selecting optimal embedding models, setting up vector databases, designing chunking strategies, implementing hybrid retrieval, integrating Large Language Models (LLMs), and performing rigorous evaluation. Use this when building knowledge-grounded AI applications or advanced semantic search systems.

Build and operate Retrieval-Augmented Generation (RAG) systems using vector stores, embedding pipelines, and hybrid search. This skill covers ingesting documents, generating embeddings, storing in vector databases, and serving grounded LLM responses. It includes setting up embedding pipelines, vector store infrastructure, and deploying hybrid search (dense + sparse) to reduce hallucinations and improve semantic search over large document collections.

Expert in vector databases, embedding strategies, and semantic search implementation. Proficient with tools like Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recommendation systems, and similarity search. Optimizes index configuration, hybrid search, and performance tuning for scalable AI systems.

A comprehensive skill for interacting with Weaviate vector databases. It enables advanced operations including semantic search, hybrid keyword querying, schema inspection, data exploration, collection creation, and bulk data import (CSV, JSON, PDF). Use this skill when you need to query data conceptually, retrieve specific raw objects, or manage the lifecycle of Weaviate collections.

This skill covers web browser game development, including framework selection (Phaser, Three.js, Babylon.js), hybrid DOM+canvas architectures, WebGPU adoption, performance optimization, PWA implementation, and audio handling. Use it for building HTML5/WebGL games or selecting browser runtimes.

Builds a minimal remote and hybrid work register tracking employee location, week start, HQ versus remote days, core-hours compliance and manager approval. Emits CSV, SQL, JSON Schema or Notion field lists on request, using empty templates only, never real employee data.