Skill UI

A specialized skill for optimizing database performance and scalability across PostgreSQL and MySQL. It guides users through analyzing slow queries, interpreting execution plans (EXPLAIN ANALYZE), designing optimal indexing strategies, tuning configuration parameters, and resolving bottlenecks like lock contention. Essential for DevOps engineers, database administrators, and backend developers.

This skill acts as a Developer Experience (DX) specialist, focusing on minimizing development friction and maximizing productivity. It helps optimize environment setup, automate repetitive workflows, enhance tooling, and improve project documentation. Use it when establishing new projects, refining existing development cycles, or troubleshooting workflow bottlenecks to achieve seamless and efficient development.

Automated help for npm script workflows inside DevOps Basics, offering guided best practices, production-ready configs, and validation for CI/CD or infrastructure requests.

Flash Attention optimizer delivers 2-4x speedup and 10-20x memory savings for transformer attention, ideal when training or running long-context models that hit GPU memory or latency limits; supports PyTorch native scaled_dot_product_attention, the flash-attn library, H100 FP8 precision, and sliding-window attention.

Analyzes SQL statements, identifies bottlenecks, suggests indexes and rewrites, and leverages the sql-query-optimizer plugin so you can improve database responsiveness when queries run slowly.

Guides adding PyTorch FSDP2’s fully_shard integration to training loops, covering correct distributed init, bottom-up sharding, mixed precision/offload policies, DTensor-aware optimizers, and distributed checkpointing so oversized models or DeviceMesh sharding goals work reliably.

Automates Tailwind class optimization for frontend developers, guiding users through best practices, validating CSS patterns, and generating React/Vue-friendly code with accessibility and performance assurances.

Python framework for multi-objective optimization, offering NSGA-II/III, MOEA/D, benchmark suites, customizable operators, and visualization to help engineering teams explore Pareto fronts and make multi-criteria decisions.

Guides Odoo users through configuring FIFO/AVCO valuation, reordering rules, putaway strategies, warehouse routes and multi-step flows to ensure accurate stock levels and traceable receipts/shipments.

A comprehensive guide and methodology for identifying, measuring, and fixing performance bottlenecks across the entire stack. This skill covers optimizing database queries (e.g., N+1 problems, missing indexes), improving API efficiency (caching, parallel processing), and enhancing frontend performance (memoization, code splitting, image optimization). It emphasizes the critical 'Measure First' principle to ensure all optimizations are data-driven and effective.

The /hub:spawn command launches N subagents that work on the same task simultaneously. Each agent operates within an isolated git worktree, ensuring true parallelism and resource separation. Users can optionally specify templates (e.g., `optimizer`, `refactorer`) to guide agents toward specific strategies for improving code quality, performance, or test coverage. Ideal for complex software engineering tasks requiring diverse, competing approaches.

This advanced skill optimizes LLM context usage by implementing strict rules for prompt caching, efficient log pruning, AST-based code inspection, and compact data structuring. It minimizes token consumption and maximizes information density, suitable for highly technical and iterative development workflows.