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Claude Skills by robsonkades
github.com/robsonkades305 skills0 installs424 views
- Skill EngineeringDesigning and reviewing agent skills: scope boundaries, the SKILL.md frontmatter contract, progressive disclosure across references and scripts, explicit decision rules, and quality gates. Use when creating a new skill, when reviewing one that is too long or never activates, when deciding what belongs in SKILL.md versus a reference, or when converting an existing prompt into a skill. Does not cover packaging, versioning or distribution, and does not cover writing the domain expertise itself.Votes: 0GitHub stars: 2
- Slo And AlertingEngineering service-level contracts and actionable alerting: defining user-centered SLIs and SLOs with explicit populations and windows, negotiating error-budget policy, separating request- and time-based semantics, deriving multi-window burn alerts, handling low traffic and missing data, and routing symptoms or predictive hazards by urgency and actionability. Use when an SLO is ambiguous, an SLA lacks operating margin, alert noise is high, resource thresholds page without context, or PromQL ...Votes: 0GitHub stars: 2
- Sql Query PerformanceMaking one SQL statement fast, from its execution plan rather than a guess: reading estimated against actual rows, finding the operation that actually costs, whether a scan is wrong at all, index selectivity and composite column order, covering indexes, and the predicates that quietly disable an index. Use when a query is slow and the plan has not been read, when "add an index" is the proposed fix, when a predicate wraps the column in a function or compares mismatched types, when OFFSET pagin...Votes: 0GitHub stars: 2
- Sql Server PerformanceDiagnosing and tuning SQL Server 2022+ from engine evidence: waits, blocking/deadlocks, RCSI and version store, cardinality and parameter-sensitive plans, memory grants and parallelism, clustered/columnstore storage, statistics and index maintenance, tempdb/files/memory, readable replicas, and mssql-jdbc behavior. Use when the symptom or proposed change depends on SQL Server internals. Not generic single-query tuning, ORM behavior, or HikariCP sizing.Votes: 0GitHub stars: 2
- Startup Cds Crac LeydenCutting JVM startup and warm-up while staying on the JVM: CDS and AppCDS, the Leyden AOT cache (JEP 483/514/515), CRaC checkpoint and restore and its constraints, what each mechanism actually accelerates, verifying the cache is really in use, and measuring time-to-first-good-response instead of time-to-port-open. Use when cold start hurts a serverless or autoscaled deployment, when a CI pipeline pays for hundreds of JVM launches, when a CRaC flag fails with Unrecognized VM option, when an App...Votes: 0GitHub stars: 2
- Stateless Service DesignMaking a service instance disposable so replicas are interchangeable: what stateless actually means — no correctness/routing dependency on one instance's volatile history; the in-process state inventory; and session state as a placement decision between sticky routing, an external store and a signed token. Use when replicas is raised above 1, when a @Scheduled job suddenly runs N times, when a local cache disagrees between instances, when an in-memory rate-limit counter or idempotency map is ...Votes: 0GitHub stars: 2
- Stream Processing Runtime PerformanceOperating Kafka Streams and Apache Flink for predictable throughput, state and recovery: separating their execution models, sizing partitions or operator parallelism, diagnosing backpressure, bounding native state, and relating commits or checkpoints to result visibility. Use when one partition or operator limits a pipeline, checkpoints grow or stall, RocksDB drives RSS outside the heap, exactly-once changes latency, or effective runtime configuration differs from declared settings. Generic t...Votes: 0GitHub stars: 2
- Streaming Pipeline TopologiesComposable stage shapes for event-driven pipelines — copier, filter, splitter, sharder, merger — with ordering, semantic parallelism, state, shuffle and recovery boundaries; exactly-once scope across source, state and sinks; bounded joins and windows; watermarks, late-data policy, backlog versus flow control, and reproducible replay. Use when a stage is parallelised, when a join grows state without bound, when a stage re-keys the stream, when late events arrive after a window closed, when a w...Votes: 0GitHub stars: 2
- Structured ConcurrencyStructuredTaskScope as a lifetime guarantee for a fan-out: fork, join, close, and the rule that no subtask thread outlives the block. Covers the API as it stands on each JDK — still a preview API on every released version, renamed between 25 and 26 and changed again in 27 — the Joiner completion policies, scope timeouts, nesting, and what close actually waits for. Use when writing or reviewing a parallel fan-out inside one request, when a sibling task keeps running after another failed, when ...Votes: 0GitHub stars: 2
- Structured LoggingDesigning application logs as governed event schemas: choosing events and fields, correlation and context lifecycle, exception and severity semantics, synchronous versus buffered delivery, overload/drop behavior, injection prevention, data minimization, integrity/retention and measurable cost. Use when logs require regex parsing, correlation is missing or stale across async work, events disappear under load, fields drift between services, failures are duplicated, secrets or untrusted text rea...Votes: 0GitHub stars: 2
- Tail Latency AnalysisDiagnosing and mitigating end-to-end latency tails: defining the latency population, decomposing stage and queue time with per-request evidence, quantifying fan-out under dependence, attributing correlated JVM/OS/network/dependency events, and selecting bounded tail-tolerance mechanisms such as deadlines, partial results, hedging and load-aware routing. Use when p99/p99.9 regresses, stage percentiles do not explain an end-to-end percentile, deploys create cold tails, wide fan-out amplifies ra...Votes: 0GitHub stars: 2
- Task Queues And Competing ConsumersDistributing work to a pool of interchangeable workers through a queue: the lease and visibility-timeout model, and why an expired lease can duplicate work instead of failing it; sizing the timeout from processing plus prefetch wait; heartbeats and their failure mode; admission and retention bounds; priority starvation; and age, backlog, arrival and drain rate as autoscaling signals. Use when two workers process one message although nothing retried or failed, when a lease is relied on for mut...Votes: 0GitHub stars: 2
- Tcp TuningThe network stack under a JVM service: listen backlog and accept queues, Nagle and delayed ACK, socket buffer sizing against bandwidth-delay product, congestion control choice, keepalive and timeout alignment along the path, and diagnosing retransmissions and queue drops. Use when a small request/response protocol shows a stable ~40 ms latency floor, when a client throws BindException or EADDRNOTAVAIL under burst, when SYNs are dropped at peak, when one core saturates while the others idle on...Votes: 0GitHub stars: 2
- TddTest-driven development as a judgement call rather than a doctrine: the red-green-refactor loop and what each step is actually for, the discipline of watching a test fail for the stated reason, step size, and an explicit account of where TDD pays and where test-after or characterisation is the better choice. Use when deciding whether to drive a change with tests, when starting a bug fix, when a design is hard to test and the cause is not obvious, when tests are being written after the fact to...Votes: 0GitHub stars: 2
- Technical Debt DecisionsDeciding when a shortcut is a legitimate trade and when it is just damage: separating deliberate and inadvertent debt, constraints delivery pressure does not waive, containing a shortcut so it can be undone, recording it where someone will find it, and choosing which debt to repay by its carrying cost rather than by how much it annoys you. Use when a deadline or an incident is pushing work to be cut, when someone proposes shipping now and cleaning up later, when a spike is about to become pro...Votes: 0GitHub stars: 2
- Thread Sizing And Virtual ThreadsChoose and size platform-thread pools or virtual-thread-per-task execution from workload shape, capacity evidence and lifecycle constraints. Covers CPU versus waiting, queue/admission policy, resource limits exposed by virtual-thread migration, ThreadLocal cost, naming, pinning boundaries after JEP 491, and Java 21/24/25 observability. Use when pool size, virtual-thread adoption or post-migration latency/resource pressure is under review.Votes: 0GitHub stars: 2
- Timeouts And DeadlinesBounding how long a call may take and propagating that bound: per-hop timeouts versus an absolute deadline, deadline propagation over HTTP and gRPC, remaining-budget arithmetic and refusing work that cannot finish, cooperative cancellation of abandoned callee work, and keeping connect, read, total and retry timeouts consistent. Use when a client sets a connect timeout but no request timeout, when Future.get() or join() is called with no bound, when a timeout is a round number repeated across ...Votes: 0GitHub stars: 2
- Unified LoggingConstructing, validating and operating HotSpot unified JVM logging: exact versus wildcard tag-set selection, levels, outputs, decorators, file rotation, asynchronous drop/stall modes, runtime VM.log changes, environment-injected options and legacy-flag migration. Use when -Xlog is empty, excessive, missing after restart, rejected at startup, changed live with jcmd, mixed with container logs, or evaluated for overhead. Producing and preserving the intended evidence belongs here; interpretation...Votes: 0GitHub stars: 2
- Universal Scalability LawFitting and falsifying the Universal Scalability Law (USL): load/resource definition, the scale coefficient gamma, contention alpha, coherency/retrograde beta, peak conditions, identifiability, uncertainty and held-out validation. Use when throughput saturates or falls as threads, users, cores or pods increase; when scale-out is proposed from too few points; or when comparing architectural scalability curves. Does not cover `L = λW`, queue/pool sizing (littles-law-and-queueing), latency-at-lo...Votes: 0GitHub stars: 2
- Varhandles And Memory OrderingDesigning and proving low-level Java variable access with VarHandle plain, opaque, acquire/release and volatile modes; compare-and-set/exchange, weak CAS, read-modify-write, fences, coordinates, signature-polymorphic typing, supported modes, and mixed-access hazards. Connects modes to synchronization edges and allowed outcomes, with model, generated-code and performance evidence when relevant. Use when selecting or reviewing low-level access modes, adapting existing handles or dynamic coordin...Votes: 0GitHub stars: 2
- View And Representation PatternsProducing the response: Template View, Transform View and Two Step View as three ways to turn a model into output, and what each becomes in a JSON API, a server-rendered page or a hypermedia fragment. Use when logic is accumulating inside templates, when a template triggers database queries during rendering, when the same data must be rendered in several formats and the mapping is duplicated per format, when a consistent look or envelope must be applied across every screen or endpoint, when e...Votes: 0GitHub stars: 2
- Virtual Thread MigrationMigrating an existing service to virtual threads as a staged programme rather than a flag: inventorying what each thread pool was implicitly limiting, auditing for pinning, file I/O and ThreadLocal caches, declaring the replacement limits before the flip, canarying one workload at a time, re-sizing the connection pool, and the rollback criteria. Use when a team plans to enable virtual threads service-wide, when a single flag is about to be flipped in production, when a migration made latency ...Votes: 0GitHub stars: 2
- Virtual Threads InternalsDiagnose HotSpot virtual-thread mounting, heap stack chunks, FIFO work-stealing scheduling, carrier capture, residual native/VM-frame pinning after JEP 491, scheduler compensation boundaries and memory/GC effects without treating implementation details as API guarantees. Use when pin events, scheduler queue/pool growth, native calls or class initialization, CPU-ready virtual threads or retained suspended stacks explain a scalability regression on Java 21–25. Not introductory adoption (thread-...Votes: 0GitHub stars: 2
- Zgc And ShenandoahOperating ZGC and Shenandoah in production: concurrent relocation via coloured pointers and load barriers, the CPU the concurrent phases actually take, allocation stalls, and which flags still exist. Use when a service migrated to a concurrent collector and throughput dropped, when a GC log shows "Allocation Stall", when a pod of 1-2 CPUs runs ZGC or Shenandoah, when a config still carries -XX:+ZGenerational or G1 flags after the migration, when a ZGC-versus-Shenandoah comparison does not dec...Votes: 0GitHub stars: 2
- Zgc Generational InternalsGenerational ZGC internals: coloured pointers without multi-mapping, the load and store barriers, the young and old cycles and their STW phases, the remembered-set bitmap and its double buffering, relocation and page management, allocation stalls, and the generational log and JFR event names. Use when a deploy script still carries -XX:+ZGenerational, when jdk.ZAllocationStall events appear or allocation stalls cluster in traffic peaks, when a pause script greps only "Pause Mark" and reports a...Votes: 0GitHub stars: 2
- Change Data Capture OperationsOperating Debezium source CDC through snapshots, lag, restarts, log retention and failover. Use when PostgreSQL WAL or MySQL binlogs accumulate, a connector cannot resume, a snapshot is interrupted, schema history is missing, or captured tables need controlled resynchronization. Covers source continuity and sink replay consequences; consumer offset resets, transactional outbox design, stream runtime tuning and cross-engine migration belong to neighboring skills.Votes: 0GitHub stars: 2
- Java Build And DependenciesDiagnose and repair Maven or Gradle builds when a managed dependency is missing, a transitive version wins unexpectedly, compilation and runtime classpaths differ, or the launcher JDK, toolchain and release target disagree. Use for dependency conflicts, missing runtime artifacts or generated code, plugin classpath failures and unreliable dependency resolution. Covers focused build repairs and reproducibility checks; intentional JDK upgrades, classloader internals and published-library governa...Votes: 0GitHub stars: 2
- Java Date And TimeModel and validate Java date and time values when choosing between civil dates, local date-times and instants, resolving DST gaps or overlaps, applying calendar arithmetic, testing time-dependent rules, or preserving temporal meaning across parsing, JSON and JDBC. Covers java.time types, region versus offset, Duration versus Period, Clock injection and precision contracts. Does not cover calendar job scheduling or operational timeout budgets (timeouts-and-deadlines).Votes: 0GitHub stars: 2
- Online Database Schema MigrationsPlanning and reviewing same-engine relational schema rollouts while old and new application versions coexist. Use for a hot-table column or constraint change, resumable backfill, migration-runner or Spring Boot startup failure, cutover, or contraction with a defined rollback boundary. Covers DDL execution risk and data correctness; not cross-engine migration, ingestion throughput tuning, or API/event schemas.Votes: 0GitHub stars: 2
- Spring Security For ApisConfigure and review Spring Security Servlet APIs when adding protected operations, changing credential delivery, fixing uncovered routes, validating JWT or opaque tokens, mapping authorities, or diagnosing bypassed method checks and CSRF, CORS or 401/403 failures. Covers access-boundary discovery, resource-server wiring and adversarial security tests; object ownership, tenant policy and transactional authorization belong to java-application-security-basics and service-layer-design. Excludes ...Votes: 0GitHub stars: 2
- Spring Boot JpaImplement, diagnose and review Spring Boot 4 persistence with Spring Data JPA when creating a durable service or verifying entity state, mappings, identifiers, fetching, transactions, locking or datasource configuration. Covers SQL Server and PostgreSQL distinctions. Excludes reactive persistence and deep database execution-plan tuning.Votes: 0GitHub stars: 2
- Spring Boot WebImplement, document and diagnose Spring Boot 4 MVC and Servlet APIs when HTTP binding, validation, error responses, Tomcat capacity or consumer contracts need verification. Covers documentation strategy, complete springdoc OpenAPI descriptions, examples and UI. Excludes WebFlux, identity providers and database query design.Votes: 0GitHub stars: 2
- Spring BootCreate and integrate Spring Boot 4 services, or configure and diagnose bean composition, auto-configuration, external properties and lifecycle. Use for a new service's delivery contract as well as focused wiring changes. Coordinates HTTP, persistence, security and operational specialists; excludes Boot 3 migration and detailed endpoint or ORM query design.Votes: 0GitHub stars: 2
- Spring Boot ObservabilityWire Spring Boot metrics, observations, traces and Actuator for a maintained service, or diagnose when a managed HTTP client loses trace context, asynchronous work detaches from its parent, instrumentation duplicates data, metric labels grow, or management endpoints and health groups expose the wrong behavior. Owns Boot integration; metric schema, trace topology, telemetry cost and SLO policy belong to specialists.Votes: 0GitHub stars: 2
- Spring Boot TestingConfigure Spring Boot test harnesses for new service acceptance, or diagnose slices that omit real wiring, rollback that hides behavior, live-server state leaks and cached contexts that outlive test services. Use for executable boundary and lifecycle checks, not general test strategy or application security policy.Votes: 0GitHub stars: 2
- Spring Http ClientsImplement outbound Spring integrations or diagnose RestClient, WebClient and HttpExchange proxies that lose Boot configuration, stall, buffer oversized responses or retry uncertain mutations. Covers transport wiring and response ownership; hands off general retry, deadline and idempotency policy. Excludes server endpoints and automatic framework migration.Votes: 0GitHub stars: 2
- Spring Transactions And EventsImplement use-case transaction boundaries and diagnose Spring interception and transaction-bound listeners when rollback differs from intent, after-commit work disappears, or persisted event publications need recovery. Verify proxy entry, rollback rules, listener phases and repeat-safe republication. Excludes general isolation design, ORM tuning and broker delivery topology.Votes: 0GitHub stars: 2
- Api Gateway And BffDesign or review an API gateway or backend for frontend when client journeys need different representations, too many round trips, an entry policy, or explicit degradation. Decide whether a BFF is warranted; define edge responsibility, bounded composition, identity propagation and failure contracts while keeping domain invariants in their owning services. Excludes replica selection and framework security implementation.Votes: 0GitHub stars: 2
- Bounded Context DesignDesign or review bounded contexts when the same business term has conflicting meanings, rules change under different owners, or a shared domain model couples unrelated workflows. Establish language, invariants, context relationships and translation contracts. Use before splitting or merging domain models; keep process extraction with distribution-boundaries and internal rule organization with domain-logic-organization. A bounded context does not automatically become a service.Votes: 0GitHub stars: 2
- Cross Service Query DesignChoose API composition or a read model when a query joins data owned by multiple services, a list needs cross-service filtering or ordering, or projection lag changes what a consumer may conclude. Define freshness, completeness, authorization, query bounds and rebuild. Excludes fan-out mechanics, event-store adoption and CDC operations.Votes: 0GitHub stars: 2
- Java Ddd AggregatesDesign and implement Java DDD aggregates when deciding which entities must change atomically, moving invariants out of setters, separating creation from rehydration, or preventing concurrent writes from bypassing the root. Covers domain identity, child ownership, valid transitions and aggregate version checks. Use for aggregate boundaries and lifecycle behavior; bounded-context discovery and ORM mapping have separate owners.Votes: 0GitHub stars: 2
- Java Ddd Domain EventsModel Java DDD domain events when an aggregate transition needs an explicit business fact, handlers see mutable state, rehydration emits duplicate facts, or saving loses pending events. Define immutable payloads, occurrence identity, time, collection lifetime and the integration boundary in domain/application/infrastructure packages. Excludes broker operations, event sourcing and Spring listener configuration.Votes: 0GitHub stars: 2
- Java Ddd Domain ServicesPlace Java DDD behavior in an aggregate, value object, domain service, policy, specification or factory using business ownership and consistency requirements. Use when a service takes over entity behavior, a rule combines several domain concepts, a policy needs external facts, or creation and rehydration are confused. Covers business names and packages, pure decision contracts and rule validation; excludes application orchestration, database query construction and persistence implementations.Votes: 0GitHub stars: 2
- Java Ddd RepositoriesImplement or review Java DDD aggregate persistence when a Gateway loses identity, audit or child state, concurrent updates bypass an aggregate invariant, database errors become not-found results, or an in-memory fake hides missing saves. Preserve inward dependencies and the project's Gateway, JpaEntity and Repository naming. Owns reconstitution and aggregate persistence contracts; excludes aggregate boundary discovery, generic Repository selection and detailed ORM configuration.Votes: 0GitHub stars: 2
- Java Ddd TestingWrite and review Java DDD tests for aggregate invariants, value-object equality, use-case outcomes, gateway rehydration, concurrency conflicts and domain-event durability. Use when extracting behavior into a domain model, testing rejected transitions, replacing repository mocks with in-memory gateways, or checking whether persistence tests protect the aggregate's consistency boundary. Follows domain, application and infrastructure packages. Does not choose bounded contexts or replace general ...Votes: 0GitHub stars: 2
- Java Ddd Use CasesImplement or review Java DDD application use cases when commands, aggregate orchestration, authorization and commit outcomes are mixed. Preserve action-based packages, UseCase/DefaultUseCase contracts and framework-independent commands and outputs; distinguish creation, absence, concurrency and replay. Excludes deciding whether a service layer is needed, strategic context design and Spring or ORM configuration mechanics.Votes: 0GitHub stars: 2
- Java Ddd Value ObjectsDesign and review Java DDD value objects when primitives hide business meaning, factories accept invalid values, equality disagrees with collections, or records expose mutable state. Covers semantic equality, identifiers, immutable composition, explicit normalization, money, units, ranges, and persistence or JSON boundaries within a bounded context. Use for CustomerDocument.of(), OrderID, monetary values, and replacing primitive obsession. Aggregate consistency and use-case orchestration belo...Votes: 0GitHub stars: 2
- Java DddTurn a business workflow into a Java DDD model and a complete use-case slice when language, invariants and responsibilities must be resolved together. Discover the context, choose proportionate tactical patterns, and preserve the project's domain, application and infrastructure naming. Use for a new domain capability or a model refactoring spanning several DDD building blocks; focused aggregate, value-object, persistence and Spring mechanism tasks have specialist owners.Votes: 0GitHub stars: 2
- Microservices ArchitectureCoordinate interdependent architecture decisions when a microservices initiative spans domain, data, interaction and operation, or specialist proposals conflict. Build an evidence-backed decision map with owners, unresolved constraints and a first verifiable slice. Does not replace initial system triage, the decision to distribute a boundary, or a specialist's local implementation guidance.Votes: 0GitHub stars: 2
- Progressive Service DeliveryPlan and verify gradual service releases when cohorts, mixed versions and persisted effects affect promotion or recovery. Choose valid cohort signals and explicit promote, pause or abort criteria.Votes: 0GitHub stars: 2