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Claude Skills by robsonkades
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- Adapter Sidecar PatternChoose and review Kubernetes telemetry adapters when a legacy or vendor process emits incompatible metrics, logs or health signals, when deciding between per-pod translation and a node agent, or when an application upgrade silently changes parsed telemetry. Covers translation contracts, evidence-backed enrichment and failure behavior. Excludes in-process interface adaptation (gof-adapter), container mechanics (sidecar-pattern), probe configuration (kubernetes-service-lifecycle) and telemetry ...Votes: 0GitHub stars: 2
- Allocation ProfilingAttribute Java heap allocation to code and validate reductions in bytes per operation. Use when allocation or GC frequency regresses, JFR allocation events are empty or disagree with counters, large buffers trigger G1 humongous collections or ZGC stalls, or pooling, TLAB tuning, or assumed JIT elimination is proposed without measurements. Covers sampling semantics and allocation-specific triage; general capture selection belongs to jfr-and-async-profiler, retention diagnosis to heap-dump-anal...Votes: 0GitHub stars: 2
- Ambassador PatternChoose or review a local outbound proxy when discovery or routing changes require client releases, a canary or shadow needs routing outside the app, or retries overlap across app, proxy and mesh. Define the listener, policy ownership, deadlines and failure behavior. Covers shard-map consumption and experiment routing, not shard algorithms (sharding-and-partitioning), container lifecycle (sidecar-pattern), or output normalization (adapter-sidecar-pattern).Votes: 0GitHub stars: 2
- Architecture And PerformanceAttribute endpoint latency and throughput limits to architectural choices when query counts grow with result size, remote calls are chatty, connections are held across other work, or a cache, layer removal or service extraction is proposed as a performance fix. Compare fetching, call topology, resource occupancy and data movement across the whole request path. Does not replace investigation methodology (performance-methodology), profiling (jfr-and-async-profiler), individual SQL tuning (sql-q...Votes: 0GitHub stars: 2
- Architecture CharacteristicsDerive and prioritize architectural quality drivers when requirements say only scalable or reliable, too many qualities are called top priority, stakeholders disagree on their meaning, or one list is applied across unrelated services. Define scope, sources, observable scenarios, baseline obligations and reasons for deferring candidates. Covers terminology and quality-model interpretation; excludes choosing design options (architecture-trade-off-analysis), recording ADRs (architecture-decision...Votes: 0GitHub stars: 2
- Architecture Coupling And QuantaMap release and runtime coupling when services ship together, event-driven components still require coordinated changes, shared data obscures ownership, or a proposed architecture quantum boundary cannot be justified. Distinguish structural dependencies, workflow completion and connascence using contracts, deployment evidence and failure behavior. Does not choose service extractions (distribution-boundaries), diagnose architecture smells (enterprise-architecture-smells), or refactor package d...Votes: 0GitHub stars: 2
- Architecture Decision MakingWrite, review, reconstruct or supersede architecture decision records when rationale is missing, a decision is repeatedly reopened, a proposal needs an explicit outcome, or an accepted choice changes. Decide how much record is warranted; preserve evidence, alternatives, consequences, decision authority and revisit conditions. Covers ADR scope, lifecycle and traceability; option comparison belongs to architecture-trade-off-analysis, quality-driver elicitation to architecture-characteristics, a...Votes: 0GitHub stars: 2
- Architecture Fitness FunctionsDefine or review checks that preserve architectural qualities when a green pipeline misses incidents, inherited rules are skipped or unexplained, a characteristic lacks evidence, or a metric is being promoted to a blocking gate. Choose the measurement or rubric, threshold, execution site, owner and response policy; expose proxy limits and coverage gaps. Excludes selecting quality drivers (architecture-characteristics), implementing application tests (architecture-testing), pipeline compositio...Votes: 0GitHub stars: 2
- Architecture Refactoring PathsSequence a chosen enterprise architecture change into compatible, testable checkpoints: domain and persistence refactoring, remote boundaries, session state, locking or events. Use when old and new paths must coexist, a migration has stalled, code and data changes interact, consumers cannot upgrade together, or rollback and safe pause points are unclear. Does not select target patterns, diagnose the need for change (enterprise-architecture-smells), plan a whole modernization programme (legacy...Votes: 0GitHub stars: 2
- Architecture TestingWrite or review tests for architectural promises: dependency boundaries, transaction atomicity, persistence mappings, stale-write detection, query budgets and API/event compatibility. Use when green tests missed a lost update or N+1, a boundary exists only in documentation, or an integration test may hide the behavior it claims to verify. Does not choose the architecture or governance thresholds (architecture-fitness-functions), replace general unit-test design, or establish production capaci...Votes: 0GitHub stars: 2
- Architecture Trade Off AnalysisCompare architectural alternatives when quality goals conflict, a scorecard or case study is being used as a verdict, options mix abstraction levels, advocates disagree, or a benchmark needs a decision rule. Build comparable options, separate constraints from preferences, test domain scenarios and uncertainty, and recommend a choice or a bounded next step. Excludes ADR lifecycle (architecture-decision-making), quality-driver elicitation (architecture-characteristics), domain pattern selection...Votes: 0GitHub stars: 2
- Async Profiler AdvancedConfigure and validate async-profiler when recordings are empty, idle-heavy, truncated, permission-blocked, containerized, multi-event, or version-sensitive. Choose event weights and engines, bound collection overhead, diagnose missing stacks, and verify conversions and differentials. Does not own initial profiler selection (jfr-and-async-profiler), visual interpretation (flame-graph-analysis), or JDK Flight Recorder configuration.Votes: 0GitHub stars: 2
- Blocking And Nonblocking IoFour things routinely conflated into one: a blocking API, a blocked OS thread, non-blocking I/O at the syscall, and an asynchronous programming model. Covers which JDK operations unmount a virtual thread and which capture the carrier, the difference between capture-with-compensation and pinning, the socket poller behind blocking socket calls, file I/O as the case Loom does not fix, and what blocking an event loop costs. Use when someone says virtual threads make I/O non-blocking, when a file-...Votes: 0GitHub stars: 2
- C2 Sea Of NodesHow HotSpot actually executes and compiles: the runtime-generated template interpreter, C2's sea-of-nodes IR, a release-scoped diagnostic map of compilation phases, and why a given transformation fired or did not. Use when a method is believed to be "not optimised", when an allocation that looks eliminable still shows up in allocation profiling, when a hot call site reports `too large` or stays non-inlined, when `made not entrant` repeats on the same method, when someone prescribes `-XX:Compi...Votes: 0GitHub stars: 2
- Cache Sharding And ReplicationTopology for a cache that no longer fits one node: client-side sharded, proxy-fronted, clustered, and fully replicated, compared on failure behaviour, cost and client complexity; and why a read after a write on a replicated cache is not read-your-writes. Estimates origin load when a cache node fails from its measured request share and the surviving copies, routing and capacity — mitigated by replication, warming, coalescing and admission control. Use when choosing between client sharding, a p...Votes: 0GitHub stars: 2
- Caching StrategiesDeciding whether to cache, then doing it safely: saved origin work and latency, bounded size or weight, TTL and jitter, stampede and its four distinct scopes, cache-aside versus refreshAfterWrite, immutable DTOs rather than JPA entities, invalidation across instances, Redis serialisation, and why hit rate alone is a misleading metric. Use when a cache is being added or reviewed, when @Cacheable is called from within the same bean, when a cache has no size limit or no TTL, when entries are pre...Votes: 0GitHub stars: 2
- Cancellation And InterruptionDesigning cooperative cancellation in Java across interruption, Future/CompletableFuture, executor/scope shutdown, deadlines, resource close/abort, CPU loops, blocking APIs, native calls, partial side effects and cleanup. Covers multiple cancellation sources, signal ownership, propagation/translation/restoration, noninterruptible regions, residual work, idempotency and bounded termination tests. Use when timeout/cancel returns but work or resources remain, or when `InterruptedException` handl...Votes: 0GitHub stars: 2
- Capacity PlanningEvidence-based capacity decisions for Java services: defining demand and failure scenarios, measuring feasible capacity envelopes, selecting replica and resource configurations, forecasting exhaustion with uncertainty, designing autoscaling headroom, and comparing cost per successful unit of work. Use when deciding pod or instance counts, minimum replicas, scaling signals, saturation dates, infrastructure budgets, rollout or failure-domain headroom, and downstream capacity constraints. Does n...Votes: 0GitHub stars: 2
- Cascading FailuresHow one slow dependency becomes a total outage: the amplification loop and the four points that close it — retry storms, unbounded queues, thread and connection exhaustion, an inner timeout longer than the outer one. Covers why cutting offered work is usually the first stabilization step in a cascade, metastability sustained by backlog, recovery herds and criticality separation. Use when one dependency's latency rise took down services that never call it, when the dependency recovered and the...Votes: 0GitHub stars: 2
- Circuit BreakersThe breaker as a state machine that stops calling a failing dependency: closed, open and half-open; choosing rate windows versus consecutive failures; recovery probe limits and in-flight work across state transitions; the failure predicate—classifying correlated dependency failures rather than blindly counting status classes—and the distinction between protecting caller resources by failing fast and providing a semantically valid fallback. Use when a breaker trips on consecutive failures, whe...Votes: 0GitHub stars: 2
- Clean Delivery WorkflowThe order of work for a change, and how much of that order a given change actually warrants: understanding before editing, clarifying what is ambiguous, deciding the test approach, implementing in reversible steps, separating refactoring from behaviour where independently valid, running the gates the risk deserves, and verifying before declaring done. Also the entry point that routes a situation to the skill that owns it. Use when starting a change and the order is not obvious, when a change ...Votes: 0GitHub stars: 2
- Code Cache SegmentsThe JDK 17-25 segmented code cache, GC-driven unloading, fragmentation, segment sizing, and jcmd Compiler.codecache/CodeHeap_Analytics. Use when aggregate usage looks healthy but one CodeHeap is exhausted, compilation stops or restarts, GC logs show a CodeCache cause, startup rejects manual heap sizes, an OutOfMemoryError reports "Out of space in CodeCache", or a long-running service degrades while aggregate free space remains. Covers runtime-shape discovery so tools do not assume exactly thr...Votes: 0GitHub stars: 2
- Code ReviewReviewing a change as an engineering activity: setting review depth from the change's risk rather than its size, looking in the order that finds the expensive defects first, refusing to spend human attention on what a formatter or linter should own, writing a finding that can be acted on, separating blocking objections from preferences, and receiving review without either capitulating or defending. Use when reviewing a pull request or a diff, when a review has become a list of style comments,...Votes: 0GitHub stars: 2
- Coding Agent DisciplineThe reporting and restraint rules for an AI agent changing someone's codebase: never claiming a result that was not observed, saying which commands ran and what they printed, reporting what could not be verified rather than omitting it, keeping the diff to what was asked, preserving behaviour that was not in scope, checking APIs against the versions the project actually depends on, and refusing to make a test pass by weakening it. Use before reporting that work is complete, when about to writ...Votes: 0GitHub stars: 2
- Collaborative Feature DefinitionCo-authoring Product Features and Tech Features through focused question-and-revision rounds. For a Product Feature, separates the business definition from an optional engineering analysis owned by an architect or senior engineer, including PoCs, ADRs, contracts, and engineering premises. Use when an idea needs an agreed feature brief or an evidenced decision not to proceed, not implementation. Accepted features go to feature-engineering for validation and execution planning.Votes: 0GitHub stars: 2
- Compilation And Inlining LogsReading what the JIT actually did: the columns of -XX:+PrintCompilation and its flag characters, -XX:+PrintInlining and its verdict strings, -XX:+LogCompilation with JITWatch, the -Xlog:jit+compilation and JFR forms, targeted compiler directives, and turning a refusal into a code change. Use when a hot method is suspected of not reaching tier 4, when a call site shows "too big" or another inlining refusal, when a method never appears in the compilation log at all, when someone prescribes -XX:...Votes: 0GitHub stars: 2
- Completablefuture CompositionDesign and diagnose CompletionStage graphs with explicit execution, ownership, failure, timeout, cancellation, context and admission semantics. Use when a continuation runs on an I/O thread, a branch failure disappears, allOf or anyOf has the wrong policy, a timeout leaves work running, or asynchronous fan-out overloads a dependency. Distinguishes Java 17/21 APIs from Java 25 preview structured-concurrency alternatives.Votes: 0GitHub stars: 2
- Component And Release BoundariesDeciding what becomes an independently releasable component — a Maven module, a JPMS module, a published library — and what that costs: the tension between reusing code and being able to release it, why a shared jar couples every service depending on it, breaking cycles between components, and judging whether a component is stable enough to depend on. Use when a `common` or `shared` module is proposed or has grown, when extracting code into a library so two services can reuse it, when a depen...Votes: 0GitHub stars: 2
- Concurrency DiagnosticsEvidence-led diagnosis of deadlock, starvation, livelock, saturation, leaks and virtual-thread scheduler problems. Compares traditional platform-thread dumps, jcmd all-thread dumps, ThreadMXBean, VirtualThreadSchedulerMXBean, JFR, wall/CPU profiles and application telemetry, including each tool's visibility and consistency limits. Use when progress stops, CPU and latency disagree, tasks disappear, shutdown hangs, or a virtual-thread dump is inconclusive.Votes: 0GitHub stars: 2
- Concurrency Limiting And BulkheadsEngineer process-local concurrency limits and bulkheads around scarce resources, with explicit admission deadlines, permit ownership, weighted work, partitioning, fairness, observability and overload validation. Distinguishes concurrency, rate and queue limits and the assumptions behind Little's Law. Use after virtual-thread migrations, during downstream saturation, or when local limits leak, over-release, double-queue or fail to compose across replicas.Votes: 0GitHub stars: 2
- Concurrency TestingTesting concurrent Java so failures appear in CI rather than in an incident: what a passing concurrency test does and does not prove, replacing sleeps with latches and deterministic executors, explicitly exercising cancellation, interruption and timeout, stress tests that assert invariants, and soak tests that catch permit and connection leaks. Use when a test uses Thread.sleep to wait for another thread, when a concurrency test is flaky and a retry is proposed, when cancellation or timeout p...Votes: 0GitHub stars: 2
- Concurrent Collections And SynchronizersChoosing between the members of java.util.concurrent once the family is settled, and the parameter that makes it correct: which BlockingQueue and which of its four insert and remove forms, which ConcurrentHashMap atomic replaces a compound action, copy-on-write's cost, latch versus barrier versus phaser versus semaphore, the Condition await loop, and ReentrantLock versus ReentrantReadWriteLock versus StampedLock. Use when computeIfAbsent loads from a database, when IllegalStateException "Recu...Votes: 0GitHub stars: 2
- Connection Pool SizingSizing and diagnosing a JDBC connection pool: L = λ × W where W is connection hold time rather than query latency, the database-side ceiling, HikariCP timeouts and lifetimes, transaction boundaries and idle-in-transaction, N+1 detection, JDBC batching, and what virtual threads change. Use when choosing maximumPoolSize, when connection-timeout is 0 or 30 s, when threads wait for connections under load, when HTTP or queue calls happen inside @Transactional, when connections die silently behind ...Votes: 0GitHub stars: 2
- Consensus And QuorumsCrash-fault consensus and quorum reasoning: FLP, safety versus liveness, majority 2f+1, R + W > N intersection and its limits, voter/failure-domain placement, Raft terms and why external fencing still requires resource enforcement, plus the differing read/watch contracts of etcd, ZooKeeper and Consul. Use when a cluster size is being chosen, when nodes are spread across AZs or regions, when application data or a queue is being put in etcd or ZooKeeper, when a coordination store sits on the re...Votes: 0GitHub stars: 2
- Consistency ModelsChoosing distributed consistency guarantees as an engineering decision: linearizability, sequential/causal ordering, session guarantees (read-your-writes, monotonic reads), bounded staleness and eventual convergence, stated as observable contracts rather than a false total ladder; CAP stated correctly—the choice between C and A exists only while partitioned—and PACELC, replica paths and transaction isolation boundaries. Use when a user cannot see their own write, when a read after a write ret...Votes: 0GitHub stars: 2
- Consistent HashingStable key-to-node placement across membership changes: modulo remapping, consistent-hash rings, virtual points, rendezvous and jump hashing, collision-safe Java implementations, hash contracts, replica selection, weighting, testing and membership handoff. Use when changing node count causes a miss storm or migration, ownership is uneven, or placement relies on Object.hashCode. Does not choose the shard key (sharding-and-partitioning), repair hot keys (hot-partitions-and-rebalancing), define ...Votes: 0GitHub stars: 2
- Container AwarenessWhat the JVM actually detects inside a container: cgroup v1 versus v2 detection, ActiveProcessorCount and how a CPU quota becomes a processor count, MaxRAMPercentage and every ergonomic derived from it, GC and JIT thread counts sized from the wrong number, and verifying all of it from inside the running container. Use when a pod is OOMKilled while heap usage is well below Xmx, when a Deployment has no resources.limits or sets limits.memory equal to Xmx, when MaxRAMPercentage is pushed to 90, ...Votes: 0GitHub stars: 2
- Continuous ProfilingDesigning and operating always-on production profiling: question-driven signal choice, permanent overhead and coverage budgets, in-process versus host collection, context-label propagation, profile schemas, storage and cardinality, retention and incident preservation, deploy-aware comparisons, trust boundaries, and evidence-quality SLOs. Use when historical CPU/allocation/lock evidence must survive an incident, when profile cost or tenant labels can grow without bound, when a backend or agent...Votes: 0GitHub stars: 2
- Coordinated OmissionCoordinated omission in depth: response-coupled sampling, open/closed/semi-open workload models, scheduled-versus-actual clocks, generator saturation, correction at recording time versus at generation time, HdrHistogram's recordValueWithExpectedInterval semantics, what wrk2, k6, Gatling, JMeter and Locust each actually do, and the effect on capacity numbers. Use when a load test's p99 is far better than production's for the same endpoint, when a generator misses its planned schedule, when som...Votes: 0GitHub stars: 2
- Cpu Cache And NumaHardware-aware Java: cache-line coherence and locality, false sharing and how it differs from lock contention, object layout measured with JOL, LongAdder versus AtomicLong, data locality in arrays and collections, and NUMA topology. Use when throughput gets **worse** as threads are added, when scaling efficiency collapses, when fields are being added to a class shared between threads, when volatile counters sit next to each other, when @Contended or padding is proposed, when -XX:+UseNUMA is b...Votes: 0GitHub stars: 2
- Data Source PatternsChoosing how code reaches the database — Table Data Gateway, Row Data Gateway, Active Record or Data Mapper — from the shape of the domain logic rather than from framework habit, and knowing what each one couples together. Use when a new module's persistence approach is being chosen, when entities carry both business rules and save() methods, when JPA is being applied to a schema that fights it, when SQL is scattered through service classes, when a "DAO" layer duplicates what the ORM already ...Votes: 0GitHub stars: 2
- Database Bulk LoadingDesigning and diagnosing high-volume database ingestion from the JVM across PostgreSQL, MySQL, and SQL Server: JDBC batching and statement rewrite, native COPY/LOAD DATA/Bulk Copy, staging, transaction and partial-error semantics, idempotent restart, upsert races, logging, parallelism, and post-load validation. Use when a backfill, import, migration, or batch window is too slow or unsafe. Not routine ORM fetch/write tuning, which belongs to orm-fetch-and-batching-performance.Votes: 0GitHub stars: 2
- Database Engine Selection And MigrationChoosing among SQL Server, MySQL/InnoDB, and PostgreSQL for a greenfield system, or planning a migration between them, from explicit semantic, workload, operational, JVM-driver, DDL, cost, and team constraints. Use when an ADR, proof of concept, compatibility inventory, shadow validation, or reversible cutover is needed. Not a generic product ranking or live query-tuning workflow.Votes: 0GitHub stars: 2
- Database Index DesignDesigning and governing an index portfolio across SQL Server, MySQL/InnoDB, and PostgreSQL: deriving composite keys from a workload, equality/range/order trade-offs, covering and partial indexes, write amplification, redundant-index consolidation, engine-specific semantics, and safe production creation or removal. Use when changing schema indexes for several queries or reviewing a table's index set. Not the diagnosis of one slow statement, which belongs to sql-query-performance.Votes: 0GitHub stars: 2
- Database PerformanceEvidence-first triage and routing for database performance questions across SQL Server, MySQL/InnoDB, PostgreSQL, JDBC pools, ORM behavior, index portfolios, and bulk loading. Use when the symptom spans layers, the owning mechanism is unclear, or a database choice or migration needs structured comparison. This is a router; it does not replace the specialist skills that own a confirmed engine or mechanism.Votes: 0GitHub stars: 2
- DebuggingFinding the cause of a fault instead of a change that makes the symptom go away: reproducing before diagnosing, shrinking the reproduction until nothing is removable, stating a hypothesis that predicts an observation, changing one variable at a time, bisecting, and choosing which evidence to collect from a running production system before it is destroyed. Use when a fix is being guessed at, when a change "seems to work", when the same bug keeps coming back, when a fault cannot be reproduced, ...Votes: 0GitHub stars: 2
- Delivery SemanticsPrecise end-to-end delivery and processing semantics: acknowledgement placement, loss and duplicate windows, Kafka transactions, visibility leases, ambiguous outcomes and external side effects. Use when reviewing "exactly once", consumer commits, publisher confirms, redelivery or a handler that writes outside its broker. Idempotent handler design belongs to idempotency; retries, ordering, poison messages and fault assumptions have their own skills.Votes: 0GitHub stars: 2
- DeoptimizationDeoptimisation and recompilation on HotSpot: uncommon traps and their reason codes, the none / maybe_recompile / reinterpret / make_not_entrant / make_not_compilable actions, jdk.Deoptimization in JFR, -XX:+TraceDeoptimization, the per-method trap limits and recompilation cutoffs, and diagnosing a method that never stabilises. Use when a method repeatedly shows "made not entrant" in the compilation log, when latency spikes correlate with class loading or a deploy, when a burst of "marked for ...Votes: 0GitHub stars: 2
- Distributed Aggregation And BarriersCorrect and recoverable aggregation across workers: algebraic laws, duplicate attempts, numeric reproducibility, mergeable summaries, barriers, joins, skew, checkpointing and partial results. Use when totals drift between runs, stragglers set job latency, worker percentiles are averaged, cardinality exhausts memory, or a join stalls on one task. It excludes request fan-out, streaming windows, percentile theory, message ordering and the broader hot-key repair catalogue.Votes: 0GitHub stars: 2
- Distributed Failure CatalogueEvidence-oriented recognition index for recurring distributed failure shapes: overload amplification, gray and asymmetric failure, split ownership, stale work, mixed versions, correlated faults, silent stagnation, missing effects and destructive automation. Use to turn incident observations into discriminable hypotheses and route each to the skill owning diagnosis and remediation. It is not a substitute for the owner skill or causal evidence.Votes: 0GitHub stars: 2