Skill UI

Evaluates API rate limiting controls for bypass vulnerabilities by probing headers, IPs, methods, versions, and encodings, ensuring throttling defenses hold up during brute-force, credential stuffing, or DoS assessments.

Uses tc, iperf3, netem, and Scapy-based flows to throttle bandwidth, add latency, and emulate Slowloris-style exhaustion so authorized testers can validate QoS controls, application resilience, and monitoring detection.

A comprehensive guide to diagnosing and resolving performance bottlenecks in React applications. This skill teaches advanced techniques like state isolation, memoization (using `useMemo`, `useCallback`, and `React.memo`), and list virtualization. It guides users through profiling using React DevTools to identify render hotspots, ensuring components render efficiently and maintain high application responsiveness.

This skill provides a comprehensive, structured workflow for diagnosing performance bottlenecks in SwiftUI applications. It guides users through a code-first review to detect common issues like invalidation storms, layout thrash, or heavy main-thread work. When code review is insufficient, it provides detailed guidance on collecting runtime evidence using Instruments, enabling precise root cause analysis and targeted remediation strategies.

A powerful operational companion for database developers. This skill assists with the daily lifecycle of database interactions, including translating natural language requirements into optimized SQL queries, generating database migrations, performing comprehensive schema introspection across multiple dialects (PostgreSQL, MySQL, SQLite, SQL Server), and identifying performance bottlenecks through detailed query optimization and index recommendations. It also supports ORM patterns like Prisma and SQLAlchemy.

Guides you through profiling scripts, processes, GPUs, memory, or interconnects with external tools and custom instrumentation, then summarizes CPU, memory, and communication bottlenecks plus actionable recommendations.

Collection of battle-tested PyTorch training recipes covering architecture selection, optimizers, LR scheduling, precision tips, and debugging to train or fine-tune LLMs, vision, diffusion, and biomedical models with high GPU throughput.

This tool guides the creation of actionable monitoring dashboards for observability platforms like Grafana and SigNoz. Instead of merely displaying raw metrics, it focuses on structuring data to answer critical operational questions: Is the system healthy? Where are the bottlenecks? What changes occurred? And what action should be taken? It transforms raw metrics into decision-making tools.

Golang performance optimization patterns and methodology; applies when profiling or benchmarks highlight a bottleneck and you need targeted solutions for allocations, CPU, GC tuning, caching, pooling, or hot-path code reviews.

Guides Go engineers on using samber/hot for in-memory caches with TTL, loader chains, sharding, and metrics, plus choosing eviction algorithms to fit work-set and stability needs.

Provides a measurement-driven workflow for improving web application performance, covering when to optimize, how to profile front-end and back-end bottlenecks, and how to monitor Core Web Vitals before and after fixes.

A universal assistant for conducting deep code reviews across major SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). It rigorously analyzes SQL code for critical vulnerabilities (like SQL injection), performance bottlenecks, maintainability issues, and adherence to industry best practices. Features include security audits, index optimization recommendations, query structure analysis, and schema design validation, ensuring robust and secure database development.