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Found 2,258 Skills
Improve interface performance across loading speed, rendering, animations, images, and bundle size. Makes experiences faster and smoother.
Recommend Azure VM sizes, VM Scale Sets (VMSS), and configurations based on workload requirements, performance needs, and budget constraints. No Azure account required — uses public documentation and the Azure Retail Prices API. USE FOR: recommend VM size, which VM should I use, choose Azure VM, VM for web/database/ML/batch/HPC, GPU VM, compare VM sizes, cheapest VM, best VM for workload, VM pricing, cost estimate, burstable/compute/memory/storage optimized VM, confidential computing, VM trade-offs, VM families, VMSS, scale set recommendation, autoscale VMs, load balanced VMs, VMSS vs VM, scale out, horizontal scaling, flexible orchestration. DO NOT USE FOR: deploying VMs or VMSS, deploying apps (use azure-deploy), looking up existing VMs (use azure-resource-lookup), cost optimization of running VMs (use azure-cost-optimization), non-VM services like App Service or AKS.
Audit and optimize Convex application performance, covering hot path reads, write contention, subscription cost, and function limits. Use when a Convex feature is slow, reads too much data, writes too often, has OCC conflicts, or needs performance investigation.
When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'ad iterations,' 'creative testing,' or 'ad performance optimization.' This skill covers generating ad creative at scale, iterating based on performance data, and enforcing platform character limits. For campaign strategy and targeting, see paid-ads. For landing page copy, see copywriting.
Routing skill for Convex work in this repo. Use when the user explicitly invokes the `convex` skill, asks which Convex workflow or skill to use, or says they are working on a Convex app without naming a specific task yet. Do not prefer this skill when the request is clearly about setting up Convex, authentication, components, migrations, or performance.
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).
Golang everyday observability — the always-on signals in production. Covers structured logging with slog, Prometheus metrics, OpenTelemetry distributed tracing, continuous profiling with pprof/Pyroscope, server-side RUM event tracking, alerting, and Grafana dashboards. Apply when instrumenting Go services for production monitoring, setting up metrics or alerting, adding OpenTelemetry tracing, correlating logs with traces, migrating legacy loggers (zap/logrus/zerolog) to slog, adding observability to new features, or implementing GDPR/CCPA-compliant tracking with Customer Data Platforms (CDP). Not for temporary deep-dive performance investigation (→ See golang-benchmark and golang-performance skills).
Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.
Design and optimize database schemas for SQL and NoSQL databases. Use when creating new databases, designing tables, defining relationships, indexing strategies, or database migrations. Handles PostgreSQL, MySQL, MongoDB, normalization, and performance optimization.
Optimize application performance for speed, efficiency, and scalability. Use when improving page load times, reducing bundle size, optimizing database queries, or fixing performance bottlenecks. Handles React optimization, lazy loading, caching, code splitting, and profiling.
Systematically debug code issues using proven methodologies. Use when encountering errors, unexpected behavior, or performance problems. Handles error analysis, root cause identification, debugging strategies, and fix verification.
Access Wind financial data. Covers A-shares / Hong Kong stocks market data (latest price / K-line / minute-level) and financial fundamentals (financial reports / share capital / events / technical indicators / risks), ETF / public funds market data and full-dimensional data (profile / finance / holdings / performance / holders / management companies), listed company announcements and financial news, macroeconomic and industry indicators. Requires WIND_API_KEY (obtained from the Developer Center at aimarket.wind.com.cn/#/user/overview). **Excludes**: US stocks / European stocks / Japanese stocks, exchange rates / futures quotes, cryptocurrencies, non-financial data.