cost-optimization
Systematic cloud cost optimization for AWS, Azure, GCP, and OCI through resource rightsizing, automated governance, pricing model analysis, and architectural best practices.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
142 skills found
Systematic cloud cost optimization for AWS, Azure, GCP, and OCI through resource rightsizing, automated governance, pricing model analysis, and architectural best practices.
Optimize Node.js performance via Redis caching, clustering, profiling, and monitoring to build fast, scalable, and efficient backend services.
Optimize agent context windows through KV-caching, observation masking, summarization-based compaction, and context partitioning to reduce costs and latency.
Optimize Apache Spark jobs with partitioning strategies, memory management, shuffle tuning, and data skew mitigation for high-performance data processing pipelines.
React and Vite performance optimization guidelines. Use when writing, reviewing, or optimizing React components built with Vite.
Optimize your App Store and Google Play metadata with expert ASO frameworks. Craft high-ranking titles, descriptions, and keyword fields to maximize search visibility and conversion rates for iOS and Android.
Webpack reference tool for frontend developers. Provides guides, troubleshooting, performance tips, and best practices for configuration and project management.
React Native performance optimization guide covering FPS, TTI, bundle size, memory leaks, and profiling patterns based on Callstack's industry-standard expertise.
An intelligent gateway that analyzes, scores, and routes user requests across 27 agents, 27 skills, and 14 MCPs to optimize Claude Code execution.
Expert SvelteKit deployment guidance covering production builds, static/node/cloudflare adapters, Vite configuration, and library authoring best practices.
Analyze and audit React projects for security, performance, correctness, and architecture issues with actionable diagnostics and scoring.
Autonomous multi-team codebase improvement agent with specialized modes: narrow (goal-directed), broad (hypothesis-divergent), and sweep (quality-focused).