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Found 391 Skills
Optimize Harness CI/CD pipeline performance via MCP. Configure parallel test execution with Test Intelligence, design multi-layer caching strategies, analyze pipeline bottlenecks with stage-level timing breakdowns, optimize cache hit rates, and design monorepo CI pipelines with selective builds. Use when asked to speed up pipelines, improve cache hit rates, set up parallel testing, optimize build times, or configure monorepo builds. Do NOT use for creating new pipelines (use create-pipeline instead) or debugging failures (use debug-pipeline instead). Trigger phrases: pipeline speed, slow pipeline, cache hit rate, parallel tests, test intelligence, build optimization, caching strategy, monorepo pipeline, pipeline bottleneck, build speed.
PostgreSQL + Redis database design patterns. Use for data modeling, indexing, caching strategies. Covers JSONB, tiered storage, cache consistency.
TanStack Query v5 (React Query) server state management. Use for data fetching, caching, mutations, or encountering v4 migration, stale data, invalidation errors.
Redis expert. Caching strategies, session storage, rate limiting, pub/sub. Use for caching implementation and Redis configuration.
JavaScript micro-optimizations and performance patterns. Use when optimizing loops, array operations, caching, or DOM manipulation. Includes Set/Map usage, early returns, and memory-efficient patterns.
Optimize Fireflies.ai API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for Fireflies.ai integrations. Trigger with phrases like "fireflies performance", "optimize fireflies", "fireflies latency", "fireflies caching", "fireflies slow", "fireflies batch".
TanStack Query (React Query) v5 best practices for data fetching, caching, mutations, and server state management. Use when building data-driven React applications, setting up query configurations, implementing mutations/optimistic updates, configuring caching strategies, integrating with SSR, or fixing v4→v5 migration errors.
Refactor Next.js code to improve maintainability, readability, and adherence to App Router best practices. Identifies and fixes God Components, prop drilling, inappropriate 'use client' usage, outdated Pages Router patterns, missing Suspense boundaries, incorrect caching strategies, and useEffect data fetching anti-patterns. Applies modern Next.js 15 patterns including Server Components, Client Components, Server Actions, streaming with Suspense, proper caching strategies, Container-Presentational pattern, layout composition, parallel routes, and intercepting routes.
Use when implementing or debugging ANY network request, API call, or data fetching. Covers fetch API, axios, React Query, SWR, error handling, caching strategies, offline support.
Analyzes web performance using Chrome DevTools MCP. Measures Core Web Vitals (FCP, LCP, TBT, CLS, Speed Index), identifies render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed.
Golang performance optimization patterns and methodology - if X bottleneck, then apply Y. Covers allocation reduction, CPU efficiency, memory layout, GC tuning, pooling, caching, and hot-path optimization. Use when profiling or benchmarks have identified a bottleneck and you need the right optimization pattern to fix it. Also use when performing performance code review to suggest improvements or benchmarks that could help identify quick performance gains. Not for measurement methodology (see golang-benchmark skill) or debugging workflow (see golang-troubleshooting skill).
In-memory caching in Golang using samber/hot — eviction algorithms (LRU, LFU, TinyLFU, W-TinyLFU, S3FIFO, ARC, TwoQueue, SIEVE, FIFO), TTL, cache loaders, sharding, stale-while-revalidate, missing key caching, and Prometheus metrics. Apply when using or adopting samber/hot, when the codebase imports github.com/samber/hot, or when the project repeatedly loads the same medium-to-low cardinality resources at high frequency and needs to reduce latency or backend pressure.