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Found 412 Skills
Expert-level Nginx configuration, reverse proxy, load balancing, SSL/TLS, caching, and performance tuning
Migrate a GitHub Actions workflow to RWX. Translates triggers, jobs, steps into an optimized RWX config with DAG parallelism, content-based caching, and RWX packages.
Prevent silent decimal mismatch bugs across EVM chains. Covers runtime decimal lookup, chain-aware caching, bridged-token precision drift, and safe normalization for bots, dashboards, and DeFi tools.
Modern React data fetching patterns. Use when implementing caching, deduplication, optimistic updates, or parallel loading with TanStack Query, SWR, or Suspense.
Design and optimize systems for high concurrency, throughput, scalability, and elastic scale—concurrency models (threads, async/await, actors), lock-free patterns, connection pooling, caching stampede mitigation, horizontal scaling, load balancing, backpressure, queueing, rate limiting, bulkheads, read replicas, sharding, pool tuning, profiling, capacity planning, SLO-driven autoscaling, multi-region and CDN edge architecture. Use when the user asks about high concurrency, scalability, throughput, horizontal scaling, connection pooling, backpressure, rate limiting, caching stampede, read replica, sharding, autoscaling, capacity planning, lock contention, async scalability, or load balancing—not service decomposition (microservices-developer), event buses only (event-driven-architecture), generic CRUD (senior-software-engineer), SRE on-call only (site-reliability-engineer), load tests without architecture (performance-engineer), or cost-only FinOps (cloud-economist).
Build backend AI with Vercel AI SDK v6 stable. Covers Output API (replaces generateObject/streamObject), speech synthesis, transcription, embeddings, MCP tools with security guidance. Includes v4→v5 migration and 15 error solutions with workarounds. Use when: implementing AI SDK v5/v6, migrating versions, troubleshooting AI_APICallError, Workers startup issues, Output API errors, Gemini caching issues, Anthropic tool errors, MCP tools, or stream resumption failures.
Expert .NET backend architect specializing in C#, ASP.NET Core, Entity Framework, Dapper, and enterprise application patterns. Masters async/await, dependency injection, caching strategies, and performance optimization. Use PROACTIVELY for .NET API development, code review, or architecture decisions.
Guidance for setting up HuggingFace model inference services with Flask APIs. This skill applies when downloading HuggingFace models, creating inference endpoints, or building ML model serving APIs. Use for tasks involving transformers library, model caching, and REST API creation for ML models.
Expert performance decisions for iOS/tvOS: when to optimize vs premature optimization, profiling tool selection, SwiftUI view identity trade-offs, and memory management strategies. Use when debugging performance issues, optimizing slow screens, or reducing memory usage. Trigger keywords: performance, Instruments, Time Profiler, Allocations, memory leak, view identity, lazy loading, @StateObject, retain cycle, image caching, faulting, batch operations
Production backend systems development. Stack: Node.js/TypeScript, Python, Go, Rust | NestJS, FastAPI, Django, Express | PostgreSQL, MongoDB, Redis. Capabilities: REST/GraphQL/gRPC APIs, OAuth 2.1/JWT auth, OWASP security, microservices, caching, load balancing, Docker/K8s deployment. Actions: design, build, implement, secure, optimize, deploy, test APIs and services. Keywords: API design, REST, GraphQL, gRPC, authentication, OAuth, JWT, RBAC, database, PostgreSQL, MongoDB, Redis, caching, microservices, Docker, Kubernetes, CI/CD, OWASP, security, performance, scalability, NestJS, FastAPI, Express, middleware, rate limiting. Use when: designing APIs, implementing auth/authz, optimizing queries, building microservices, securing endpoints, deploying containers, setting up CI/CD.
React Query v4 (TanStack Query) best practices, patterns, and troubleshooting. Use when working with useQuery, useMutation, query invalidation, caching, WebSocket integration, or any async state management in React. Based on TkDodo's comprehensive blog series.
Reduce your AI API bill. Use when AI costs are too high, API calls are too expensive, you want to use cheaper models, optimize token usage, reduce LLM spending, route easy questions to cheap models, or make your AI feature more cost-effective. Covers DSPy cost optimization — cheaper models, smart routing, per-module LMs, fine-tuning, caching, and prompt reduction.