Implement bounded, idempotency-aware API throttling, backoff, and retry handling for 429 and transient 5xx responses.
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
Implement bounded, idempotency-aware API throttling, backoff, and retry handling for 429 and transient 5xx responses.
日本語の概要は準備中です。原文の説明を表示しています。
Diagnoses GKE workload failures (CrashLoopBackOff, OOMKilled, ImagePullBackOff, Pending, etc.) via logs and events. Use when pods fail to start or crash repeatedly. Don't use for GKE cluster infrastructure provisioning, node pool creation, or non-Kubernetes Google Cloud services.
日本語の概要は準備中です。原文の説明を表示しています。
Unified guide for authoring dashboard panel components in vanilla TypeScript — covers the authoritative Panel base class (grid-span persistence, dual resize handles, radar loading animation, exponential-backoff error countdown, data/new badge helpers, full destroy() cleanup), localStorage state via loadMap/saveMap, exponential-backoff retry, and CircuitBreaker integration. Shows how to wrap any existing fetchX() service call with CircuitBreaker.execute() as a one-liner and clarifies when each resilience layer is appropriate.
日本語の概要は準備中です。原文の説明を表示しています。
Unified guide for authoring dashboard panel components in vanilla TypeScript — covers the Panel base class architecture, localStorage state persistence, exponential-backoff retry, and CircuitBreaker integration. Shows how to wrap any existing fetchX() service call with CircuitBreaker.execute() as a one-liner and clarifies when each resilience layer is appropriate.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when the user is hands-on deploying an in-bundle DOCA service container (Argus, DMS, Firefly, or UROM service) on a BlueField — kubelet standalone watching a static-pod manifests directory, YAML pod-spec drop, kubelet status / ENTRYPOINT logs / per-service liveness, smoke-before-bulk, and the layered error taxonomy (pod-spec, scheduling, image pull, runtime, mount, network, version, host). Trigger even when the user does not say "container deployment" — typical implicit phrasings include "how do I run my built service on the BlueField?", "where do I drop the pod-spec YAML?", "pod stuck in Pending / ImagePullBackOff / CrashLoopBackOff", "container Running but service isn't ready", "pod restart-loops after edit", or "DMS and Firefly together". Refuse and route elsewhere for per-service config schemas, DOCA install, library-API questions, external NVIDIA services (BlueMan, HBN, SNAP, Virtio-net), or full Kubernetes-cluster ops — those belong to other skills.
日本語の概要は準備中です。原文の説明を表示しています。
Debug live Azure Kubernetes Service (AKS) incidents with a read-only, evidence-first investigation. WHEN: pod crashes or Pending, CrashLoopBackOff, OOMKilled, ImagePullBackOff, node NotReady, DNS or ingress failure, connectivity timeout, network policy, SNAT exhaustion, node-pool scaling blocked by QuotaExceeded or InsufficientVCPUQuota, upgrade stuck, spot or zone disruption, a bare VMExtensionProvisioningError or AllocationFailed wrapper, an uncataloged capacity symptom, or 'investigate my AKS cluster'. DO NOT USE FOR: packet capture (use aks-network-capture); GPU or model-serving issues (use aks-gpu-inference); cluster creation or provisioning (use azure-kubernetes); cost (use cost-analysis from the optional azure-cost plugin); pod rightsizing (use azure-kubernetes); a fully qualified documented AKS signature with every required nested qualifier (use aks-known-issues); standalone failures on non-AKS Azure resources (use azure-diagnostics). Unqualified errors and open-ended incidents stay here only for AKS.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze and control AssemblyAI account request limits, concurrency, backoff, and admission queues. Use when handling 429s or planning throughput. Trigger with "AssemblyAI rate limit", "AssemblyAI concurrency", or "AssemblyAI backoff".
日本語の概要は準備中です。原文の説明を表示しています。
Implement Apollo.io rate limiting and backoff. Use when handling rate limits, implementing retry logic, or optimizing API request throughput. Trigger with phrases like "apollo rate limit", "apollo 429", "apollo throttling", "apollo backoff", "apollo request limits".
日本語の概要は準備中です。原文の説明を表示しています。
Handle Apify API rate limits with proper backoff and request queuing. Use when hitting 429 errors, optimizing API request throughput, or implementing rate-aware client wrappers. Trigger with "apify rate limit", "apify throttling", "apify 429", "apify retry", "apify backoff", "too many requests apify".
日本語の概要は準備中です。原文の説明を表示しています。
Implement Anthropic Claude API rate limiting, backoff, and quota management. Use when handling 429 errors, optimizing request throughput, or managing RPM/TPM limits across usage tiers. Trigger with phrases like "anthropic rate limit", "claude 429", "anthropic throttling", "claude retry", "anthropic backoff".
日本語の概要は準備中です。原文の説明を表示しています。
Debug live Azure Kubernetes Service (AKS) incidents with a read-only, evidence-first investigation. WHEN: pod crashes or Pending, CrashLoopBackOff, OOMKilled, ImagePullBackOff, node NotReady, DNS or ingress failure, connectivity timeout, network policy, SNAT exhaustion, node-pool scaling blocked by QuotaExceeded or InsufficientVCPUQuota, upgrade stuck, spot or zone disruption, a bare VMExtensionProvisioningError or AllocationFailed wrapper, an uncataloged capacity symptom, or 'investigate my AKS cluster'. DO NOT USE FOR: packet capture (use aks-network-capture); GPU or model-serving issues (use aks-gpu-inference); cluster creation or provisioning (use azure-kubernetes); cost (use cost-analysis from the optional azure-cost plugin); pod rightsizing (use azure-kubernetes); a fully qualified documented AKS signature with every required nested qualifier (use aks-known-issues); standalone failures on non-AKS Azure resources (use azure-diagnostics). Unqualified errors and open-ended incidents stay here only for AKS.
日本語の概要は準備中です。原文の説明を表示しています。
Implement bounded, idempotency-aware API throttling, backoff, and retry handling for 429 and transient 5xx responses.
日本語の概要は準備中です。原文の説明を表示しています。
Use when adding retries, backoff, or concurrency limits to Spring Boot 4 / Spring Framework 7 code with core Retryable and ConcurrencyLimit support. Covers enablement, backoff, proxy limits, and behavior after retries are exhausted.
日本語の概要は準備中です。原文の説明を表示しています。
World-class Kubernetes operations - deployments, debugging, Helm charts, and the battle scars from managing clusters that serve millions of requestsUse when "kubernetes, k8s, kubectl, helm, pod, deployment, service, ingress, configmap, secret, statefulset, daemonset, hpa, pvc, crashloopbackoff, imagepullbackoff, oomkilled, liveness probe, readiness probe, kubernetes, k8s, containers, docker, helm, deployment, devops, cloud-native" mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
Diagnoses GKE workload failures (CrashLoopBackOff, OOMKilled, ImagePullBackOff, Pending, etc.) via logs and events. Use when pods fail to start or crash repeatedly. Don't use for GKE cluster infrastructure provisioning, node pool creation, or non-Kubernetes Google Cloud services.
日本語の概要は準備中です。原文の説明を表示しています。
Building resilient distributed systems with circuit breakers, retries with full-jitter exponential backoff, retry budgets (per-request 3-attempt + per-client 10% ratio per Google SRE), deadline propagation, and the cascading-failure math (4 layers × 3 retries = 64x amplification). Grounded in Resilience4j, Microsoft Cloud Patterns, AWS Architecture Blog (Marc Brooker), and Google SRE Book.
日本語の概要は準備中です。原文の説明を表示しています。
Building resilient distributed systems with circuit breakers, retries with full-jitter exponential backoff, retry budgets (per-request 3-attempt + per-client 10% ratio per Google SRE), deadline propagation, and the cascading-failure math (4 layers × 3 retries = 64x amplification). Grounded in Resilience4j, Microsoft Cloud Patterns, AWS Architecture Blog (Marc Brooker), and Google SRE Book. NOT for server-side rate limiting, bulkhead isolation, backpressure protocols, or database-specific retry.
日本語の概要は準備中です。原文の説明を表示しています。
Kubernetesの設定ファイル作成・レビューと障害調査を支援します。稼働確認、権限、リソース制限、自動スケールの設定例と調査コマンドを参照できます。
Inspect and manage circuit-breaker states, connection cooldowns, quota limits, and backoff levels from the CLI. Reset stuck providers and configure resilience thresholds.
日本語の概要は準備中です。原文の説明を表示しています。
Python resilience patterns including automatic retries, exponential backoff, timeouts, and fault-tolerant decorators. Use when adding retry logic, implementing timeouts, building fault-tolerant services, or handling transient failures.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.
日本語の概要は準備中です。原文の説明を表示しています。
Configures alerting policies in Terraform for Google Kubernetes Engine (GKE) clusters, workloads, and services using PromQL and Google Cloud Managed Service for Prometheus. Use when writing, analyzing, validating, or deploying Terraform alerting policies to monitor GKE service latency, traffic, error rates using Multi-Window Multi-Burn-Rate SLO alerts, memory saturation, and cluster health such as CrashLoopBackOff and Node NotReady conditions. Don't use for non-GKE compute runtimes such as standalone Compute Engine VMs or standalone Cloud Run services without GKE.
日本語の概要は準備中です。原文の説明を表示しています。
Adaptive polling pattern with exponential backoff on failure, automatic recovery on success, and visibility-aware scheduling
日本語の概要は準備中です。原文の説明を表示しています。
Guides design and implementation of evolutionary modular-monolith platforms with DDD (strategic + tactical), flat-by-aggregate organization, an Anti-Corruption Layer for vendor independence, a transactional outbox for events, smart resilience (backoff with jitter, circuit breakers, idempotency), and a polished architecture HTML document with elegant SVG diagrams. Use when designing a platform or backend, defining bounded contexts, organizing modules and folders, choosing monolith vs microservices, decoupling from an external service (ERP, storage, AI), making calls resilient, adding real-time push, picking a 2026 TypeScript stack (Nx, NestJS, React), or producing an architecture document or diagram. Also triggers on 'modular monolith', 'bounded contexts', 'flat-by-aggregate', 'ports and adapters', 'architecture diagram'. Do NOT use for simple CRUD, NestJS-only deep implementation (use nestjs-modular-monolith), or pure domain-model review (use tactical-ddd).
日本語の概要は準備中です。原文の説明を表示しています。