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Found 184 Skills
Single deployable with enforced module boundaries for team autonomy without distributed complexity. Triggers: modular-monolith, module boundaries, single deployment, team autonomy Use when: teams need autonomy without distributed overhead DO NOT use when: already using microservices or system is small.
Implement production-ready service mesh deployments with Istio, Linkerd, or Cilium. Configure mTLS, authorization policies, traffic routing, and progressive delivery patterns for secure, observable microservices. Use when setting up service-to-service communication, implementing zero-trust security, or enabling canary deployments.
Comprehensive technology-agnostic prompt generator for documenting end-to-end application workflows. Automatically detects project architecture patterns, technology stacks, and data flow patterns to generate detailed implementation blueprints covering entry points, service layers, data access, error handling, and testing approaches across multiple technologies including .NET, Java/Spring, React, and microservices architectures.
Use when facing complex decisions, architectural trade-offs, philosophical questions, or any problem requiring deep analysis before action. Use when the user asks to "think deeply", "question assumptions", "analyze from first principles", "challenge this decision", debates between two approaches (e.g. monolith vs microservices, build vs buy, SSR vs CSR), or invokes /socrates. Also triggered when other skills need a thinking engine for rigorous pre-analysis. Even if the problem seems simple, if there are hidden assumptions worth examining, this skill applies.
Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.
Use when creating professional architecture diagrams, cloud infrastructure visuals, network topologies, Kubernetes cluster diagrams, or microservices architecture diagrams as PNG/SVG images using Python Diagrams library with real provider icons (AWS, Azure, GCP, K8s, OnPrem, Generic)
Grafana Mimir scalable long-term metrics storage. Covers architecture (distributor/ingester/compactor/querier/ query-frontend/store-gateway/ruler), deployment modes (monolithic/microservices), configuration, Prometheus remote write, PromQL querying, multi-tenancy, compaction, and operations. Use when working with Mimir for metrics storage, scaling Prometheus, configuring Mimir clusters, writing PromQL, or debugging Mimir.
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).
Implements concurrent Go patterns using goroutines and channels, designs and builds microservices with gRPC or REST, optimizes Go application performance with pprof, and enforces idiomatic Go with generics, interfaces, and robust error handling. Use when building Go applications requiring concurrent programming, microservices architecture, or high-performance systems. Invoke for goroutines, channels, Go generics, gRPC integration, CLI tools, benchmarks, or table-driven testing.
Grafana Tempo distributed tracing backend. Covers TraceQL query language (span selectors, attribute scopes, pipeline operators, structural operators, metrics functions), trace ingestion via OTLP/Jaeger/Zipkin, Tempo architecture (distributor/ingester/compactor/querier/metrics-generator), full configuration reference with YAML, metrics-from-traces (span metrics, service graphs, TraceQL metrics), deployment modes (monolithic/microservices/Helm/Kubernetes), multi-tenancy, performance tuning, caching, and HTTP API. Use when working with distributed traces, writing TraceQL queries, deploying Tempo, configuring trace pipelines, or setting up Grafana-Tempo integrations (traces-to-logs, traces-to-metrics, traces-to-profiles).
Build ASP.NET Core Web APIs with .NET 10 (C# 14.0). Supports project scaffolding, CRUD operations, Entity Framework integration, dependency injection, testing with xUnit, Docker containerization, and following 2025 best practices. Use when creating REST APIs, microservices, backend services, implementing CRUD operations, setting up Entity Framework, adding authentication/authorization, or containerizing .NET applications. Triggers on .NET, ASP.NET Core, C#, Web API, REST API, microservices, dotnet, csharp development tasks.
Configures Gradle with Spring Boot projects including plugin setup, bootable JAR creation, layered JARs for Docker optimization, and multi-module Spring Boot configurations. Use when asked to "set up Spring Boot with Gradle", "create executable JARs", "configure Docker layering", or "set up Spring Boot microservices".