Skill UI

This skill provides advanced architectural patterns for optimizing high-volume integrations with the Navan API. It addresses common bottlenecks like rate limiting, sequential calls, and naive pagination by implementing robust solutions such as data-type-specific response caching, controlled parallel fetching with concurrency throttling, efficient cursor-based pagination, and HTTP connection reuse. Use this when building scalable, reliable, and high-throughput systems.

This skill implements resilient API interaction patterns for external services. It uses adaptive rate-limiting techniques, including exponential backoff and jitter, to gracefully handle HTTP 429 errors, adapting to undocumented server limits. Furthermore, it provides a dedicated request queue mechanism to manage concurrency, ensuring reliable execution of large-scale, bulk data operations without triggering service throttling.

This comprehensive guide provides advanced strategies for optimizing and scaling Qdrant vector database throughput (QPS). It covers performance tuning techniques, such as optimizing segment size, enabling quantization, and using batch search. Furthermore, it details horizontal scaling methods using read replicas and addressing disk I/O bottlenecks, ensuring high performance for large-scale, high-concurrency retrieval applications.

This guide provides a comprehensive methodology for load testing and capacity planning within Snowflake data warehouses. It covers optimizing query performance by adjusting warehouse sizes (Scale UP), simulating high concurrency using multi-threading (Scale OUT), and configuring advanced scaling policies (Standard, Economy, Maximized). Users can benchmark critical queries using SQL and simulate real-world user traffic using Python, ensuring robust and cost-efficient production environments.

This guide provides comprehensive instructions on managing performance and concurrency within Snowflake. It covers key concepts like warehouse sizing, multi-cluster configuration, and detecting query queuing issues. Users learn how to right-size resources and implement application-level rate limiting to prevent throttling and optimize data warehouse throughput for complex analytics workloads.

This skill provides comprehensive strategies for handling rate limits when interacting with the Webflow Data API v2. It covers using SDK built-in retries, implementing custom exponential backoff with jitter, controlling concurrency using request queues, and optimizing calls with bulk endpoints (e.g., createItemsBulk). Use this guide when encountering 429 errors or when maximizing API throughput is critical for robust applications.

A comprehensive playbook for advanced security testing, focusing on race conditions and TOCTOU (Time-of-check to time-of-use) vulnerabilities in web applications. It guides users to exploit non-atomic, state-changing operations (e.g., coupons, balance deductions, single-use rewards) by sending highly synchronized, parallel requests (including HTTP/2 single-packet attacks). Essential for identifying weaknesses in authorization and transactional integrity.