Skill UI

Provides PostgreSQL optimization advice covering index design, query plan inspection, partitioning, JSONB tweaks, connection pooling, and tuning checkpoints to stabilize OLTP workloads.

Guides teams through setting up PostHog observability with ingestion health checks, flag latency tracking, billing-aware volume monitoring, alerts for anomalies, and dashboards for key metrics and API performance.

Optimize PostHog API performance by tuning client batching, local flag evaluation, sampling noisy events, and crafting efficient HogQL queries to keep integrations responsive when facing slow responses or heavy throughput.

Profiles application performance by analyzing CPU usage, memory allocation, and execution time with the application-profiler plugin, then identifies bottlenecks and suggests code-level optimizations for faster execution.

A comprehensive guide on creating projections and read models from event streams. This skill is essential for implementing the read side of CQRS (Command Query Responsibility Segregation), constructing materialized views, or significantly optimizing query performance in complex event-sourced architectures. Use it when data aggregation and reporting are derived from historical events.

Provides ready-to-use role and task prompt templates for developers, writers, reviewers, and analysts, helping them request debugging, documentation, performance, and creative assistance via structured guidance.

Provides prioritized performance optimization recommendations across frontend, backend, and infrastructure, offering bottleneck analysis, impact estimates, and phased implementation roadmaps when users request speed improvements or reviews.

This comprehensive guide provides methods for profiling, analyzing, and optimizing Python code. It covers advanced techniques such as CPU profiling, memory leak mitigation, improving I/O operations, and optimizing database queries. Use this skill when diagnosing slow-running applications, reducing system latency, or implementing high-performance, resource-efficient algorithms in a production environment.

A comprehensive guide for building modern, production-ready Python 3.11+ applications. This skill enforces strict type hinting, asynchronous patterns (async/await), robust unit testing (pytest), and rigorous code validation using mypy, black, and ruff. Use it for developing complex, high-performance, and highly maintainable Python services.

A specialist guide for building and optimizing modern Rails 7+ web applications. Expertise covers implementing Hotwire (Turbo Frames/Streams) for partial page updates, optimizing Active Record queries (N+1 prevention), configuring real-time communication via Action Cable, managing background tasks with Sidekiq, and ensuring code quality through comprehensive RSpec testing. Ideal for complex, high-performance backend development.

A comprehensive guide maintained by Vercel for optimizing performance in React and Next.js applications. It covers critical rules across multiple categories, including eliminating waterfalls, bundle size optimization, server-side caching, and granular control over client-side rendering and data fetching. Use this when building new components or refactoring existing code for maximum speed and efficiency.

Automated assistance for building React components, offering best practices, production-ready code generation, and validation guidance for frontend patterns like accessibility and performance optimization.