Skill UI

Guides on handling PostHog rate limits with exponential backoff, jitter, idempotent keys, queuing, and header monitoring to keep API calls reliable during throttling or retry scenarios.

Defines a batch-processing pattern for APIs that validates payloads, runs synchronous or async execution with concurrency limits, tracks per-item progress, reports partial failures, and integrates retries and throttling for large bulk operations.

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.

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.

Provides Replit-specific rate limiting guidance, adding exponential backoff with jitter, deterministic idempotency keys, queue throttling, and header monitoring so apps stay within quotas while retrying safely.

Provides Retell AI clients with structured rate limit handling by combining exponential backoff with jitter, idempotent request keys, header monitoring, and optional queueing so retries stay safe when 429 or limit headers indicate throttling.

Guides systematic load, stress, spike, and soak testing with k6, Artillery, JMeter, Locust, or autocannon, producing SLA-aligned metrics, bottleneck analysis, and CI gates for production-like services.

Configure Sentry to monitor application performance, enable distributed tracing, and visualize spans so teams can identify bottlenecks and validate that requests propagate through services as expected.

Provides Speak language API rate-limiting helpers, including per-endpoint throttling, batch queues, and retry-on-429 handling to keep pronunciation assessments and conversation calls inside the documented quotas.

This skill provides systematic patterns and best practices for transforming slow database queries into lightning-fast operations. It covers advanced topics such as proper indexing strategies, detailed query plan analysis (EXPLAIN), resolving common issues like N+1 problems, and designing highly performant database schemas. Use this when debugging performance bottlenecks, improving application response times, or ensuring scalability for growing datasets.

This skill specializes in optimizing complex SQL queries, designing efficient database schemas, and diagnosing performance bottlenecks across various SQL dialects (PostgreSQL, MySQL, SQL Server, etc.). Use it when dealing with slow queries, complex data aggregation, advanced joins, or when needing to implement best practices like CTEs, window functions, and covering indexes. It provides deep analysis of execution plans (EXPLAIN/ANALYZE) to ensure peak data retrieval performance.

Implements middleware policies to throttle API requests, limit concurrency, queue priorities, and use circuit breakers with adaptive limits, protecting backends from overload while surfacing throttle-state headers for clients.