1,934 件 ・ 関連度順
概要と使いどころ
Run a deep root-cause investigation on the AWS DevOps Agent. Use when the user describes an incident, alarm, outage, or unexplained behavior — keywords like "5xx", "503", "OOM", "latency spike", "deployment failure", "rollback", "sev1", "investigate", "root cause", "debug", "alarm fired", "service down". Polls and streams progress, then surfaces recommendations.
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Diagnoses and resolves Amazon S3 Files issues including mount failures, permission errors, synchronization problems, and performance issues. Use when the user has an S3 file system that is not mounting, returning access denied, not syncing changes to S3, showing files in lost+found, or performing slower than expected.
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。
Debugs AWS Lambda function timeout failures by systematically analyzing function configuration, CloudWatch logs and metrics, VPC/networking, cold starts, memory constraints, and downstream dependencies to identify root causes with actionable fixes. Use when a Lambda function is timing out or approaching its timeout limit.
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Manages WhatsApp messaging through AWS End User Messaging Social. Covers managing templates (create, update, delete, library), sending messages (utility/marketing/auth templates and freeform), uploading and managing media, configuring event destinations for delivery tracking, and troubleshooting delivery failures. Applicable when a user needs to send WhatsApp messages, create or manage templates, upload media, configure delivery notifications, or diagnose messaging issues.
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Guides Amazon SES onboarding for domain-based email sending. Covers identity configuration, production access, an optional first test send, and troubleshooting setup, authentication, or sending failures. Use when setting up SES, resuming incomplete onboarding, or leaving the sandbox. Does not cover inbound email or Mail Manager, SMS/voice, WhatsApp, SNS, Pinpoint, or WorkMail.
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Sets up AWS Resilience Hub v2 from scratch: creates resilience policies with SLO targets, registers systems and user journeys, onboards services with input sources, and runs a first failure mode assessment. Applies when the user wants to get started with Resilience Hub v2, create a policy, onboard a service, or run an assessment — including creating one concrete policy with specific availability/RTO/RPO targets and a DR approach for a single service (even a tier-1 one). Does not apply to FIS experiments or ARC routing controls.
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。
Installs, configures, and troubleshoots Network Flow Monitor agents on EC2 instances to monitor network path health. Covers agent installation, IAM permissions, monitoring network paths, and troubleshooting agents reporting no metrics, HTTP 403 errors, or connectivity failures.
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Builds and deploys containerized workloads on Elastic Kubernetes Service (EKS), Elastic Container Service (ECS), Fargate, and ECR (Elastic Container Registry). Covers general EKS knowledge, Karpenter, AWS Load Balancer Controller and leveraging various open source Kubernetes projects with EKS. Covers general ECS knowledge, task definitions, Fargate services, ECS Exec, ECS Express Mode and ECS Managed Instances. Covers general Elastic Beanstalk knowledge, Elastic Beanstalk configuration and platforms supported by Elastic Beanstalk. Covers general ECR knowledge, ECR repository setup and lifecycle policies. Includes recommending, enabling, and reading Amazon ECS Action Logs to troubleshoot control-plane failures (deployment rollback/circuit-breaker, task placement, scaling, task replacement). Applies when deploying, debugging, or optimizing containers on AWS. Should be used instead of relying on internal knowledge for these 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。
Amazon Redshift is NOT PostgreSQL; corrects LLM mistakes; covers SQL, metadata, connectivity/auth, storage, query performance, and operations. Applies ONLY to Redshift (provisioned or Serverless). Pushes back on: CREATE INDEX, string_agg, pg_catalog, text type, SERIAL, stl_query. Triggers on: Redshift SQL, Redshift CREATE TABLE, Redshift COPY/UNLOAD, slow or suddenly slow Redshift query, EXPLAIN plan, queue wait, stale statistics/ANALYZE, result cache, Redshift permission denied, Redshift disk full, storage growth, snapshot/backup cost, ghost rows/bloat, VACUUM, spill to disk, distribution skew, Redshift system views, QUALIFY, PIVOT, MERGE, materialized views, Redshift Data API (Python/boto3), Redshift workload management (WLM), concurrency scaling, Redshift resize, Spectrum, awsdatacatalog, connection failures (SSL/TLS, ODBC/JDBC, connection limit), IAM/SAML federation, IAM Identity Center, datashares. Does NOT apply to: S3 policies, Athena, Glue/Iceberg outside Redshift, Aurora, RDS, DynamoDB.
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。
Troubleshoots and debugs AWS Clean Rooms collaboration issues related to IAM roles, S3 bucket policies, KMS keys, Lake Formation permissions, and CloudWatch logging for custom ML model training and inference jobs. Use when a customer reports permission failures, access errors, or log publishing issues in Clean Rooms.
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。
Provisions, scales, and operates Amazon EC2 virtual-machine workloads: instance-type selection (Graviton/Arm64, burstable T credits, GPU, instance store vs EBS), launch templates, Auto Scaling groups (scaling policies, instance refresh, mixed instances, Spot, warm pools, lifecycle hooks), IMDSv2, placement groups, Elastic IPs, AMI lifecycle, and Systems Manager fleet operations (Session Manager, Run Command, Patch Manager). Applies to EC2 instance and fleet questions, InsufficientInstanceCapacity, CPU-credit/surplus charges, IMDSv2 401s, instances stuck in Pending:Wait, ASG not replacing unhealthy instances, status-check failures, SSH refused/timed out, or instances missing as SSM managed nodes. For a single secure instance launch, the launching-ec2-instance-with-best-practices skill is more appropriate; for instance profiles, see setting-up-ec2-instance-profiles; for Image Builder, see amazon-ec2-image-builder. Does NOT cover Lambda, ECS/Fargate, EKS, VPC/ALB/NLB design, or IAM policy authoring.
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。
Selects, deploys, and customizes AI models on Amazon SageMaker. Training or Processing jobs, fine-tuning (SFT/DPO/RLVR/RLAIF), model selection, dataset preparation, evaluation, SageMaker or Bedrock deployment, inference optimization and endpoint diagnostics. Covers the full lifecycle from planning through production. Use when fine-tuning models on SageMaker, choosing which base model to customize, fine-tune, or deploy from SageMaker JumpStart or Hub, SageMakerPublicHub, or the SageMaker public model catalog, transforming or validating training data, evaluating model quality, deploying or optimizing endpoints, configuring IAM/S3 for training, or managing SageMaker Managed MLflow. Use for endpoint health, failures, latency, logs, metrics, errors. Covers Serverless Model Customization, Nova and OSS deployment paths, and PySDK v3. NOT for Ground Truth labeling, Feature Store, or general-purpose AWS infrastructure.
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。
Authors and deploys MWAA workflow artifacts: Python Airflow DAGs for provisioned environments or YAML workflow files for Serverless. Covers operator selection, timeout design, retry strategy, scheduling, failure notifications, idempotency, and MWAA Serverless schema compliance. Deploys the artifact (S3 DAG upload or Serverless CreateWorkflow/UpdateWorkflow), creates an environment inline when approved, and redeploys fixes, then optionally hands off to testing-mwaa-workflow. Triggers on: create a DAG, write a pipeline, build a workflow, orchestrate tasks, Airflow DAG, data pipeline, schedule a job, deploy a DAG, deploy a workflow, YAML workflow. Not applicable to converting or migrating existing DAGs between provisioned and serverless (conversion is out of scope), running or smoke-testing a deployed workflow (handled by testing-mwaa-workflow) or diagnosing a failed run (handled by debugging-mwaa-workflow).
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。
Tests Amazon MWAA workflow execution end-to-end: trigger a run and monitor it to completion for Provisioned (Python DAG, via Airflow REST API) and Serverless (YAML workflow, via StartWorkflowRun). Verifies the artifact is deployed and parse-ready, triggers with confirmation, polls to terminal state, and on failure delegates diagnosis to debugging-mwaa-workflow and artifact/redeploy fixes to authoring-mwaa-workflow, then retests up to a capped number of attempts. Triggers on: test my DAG, test my workflow, run my DAG, trigger a test run, does my DAG work, smoke-test the pipeline, verify my workflow runs, execute my DAG to check it. Not applicable to writing or deploying a new workflow (handled by authoring-mwaa-workflow), or for diagnosing why a run failed or root-causing an error (handled by debugging-mwaa-workflow).
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。
Upgrades an MWAA environment to a newer Airflow version — within 2.x, within 3.x, or across the 2.x-to-3.x boundary. Computes the version-jump path, inserting the 2.11.x stepping-stone and Python-transition step when needed. Chooses an approach by whether run history and the same environment (URL/ARN) must be kept: a new-environment upgrade (blue-green), a rehearsed in-place upgrade validated on a test copy, or a direct in-place upgrade. Runs Ruff scanning and deprecation-warning log scans for 3.x moves, plus Docker validation, batched deployment, and switchover. Saves a resumable upgrade plan for multi-session work. Triggers on: upgrade MWAA, upgrade Airflow, migrate to Airflow 3, MWAA Airflow 3, Airflow 2 to 3, preserve Airflow history, keep same MWAA environment, blue-green cutover, validation environment before cutover. Not for authoring new DAGs (authoring-mwaa-workflow), debugging unrelated DAG failures (debugging-mwaa-workflow), or MWAA Serverless YAML workflows (provisioned Python DAGs only).
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。
Deploys, queries, and debugs AWS Marketplace usage-based (PAYG) metering — the pipeline (ResolveCustomer, BatchMeterUsage, EventBridge via SAM) and querying/debugging metering records, statuses, failures, discrepancies. Covers Concurrent Agreements (CustomerAWSAccountId + LicenseArn), multi-product, CloudTrail Event History (90 days; never CloudTrail Lake), Seller Reports (Billed Revenue/Usage columns + CSV/SDDS parsing), existing-stack detection, metering region for BatchMeterUsage/MeterUsage (DisabledApiException), metered AMI/Container + IAM roles, where registration data lives (customer-profile table), legacy ProductCode + CustomerIdentifier, DuplicateRecord/CustomerNotSubscribed, bad LicenseArn. Also SCOPES adjacent asks — flat-rate/SaaS-Subscription "do I still meter", CCP included-units + overage, contract term/annual renewal, forecasting future bills/usage — with the right answer or a one-line redirect. Use for any BatchMeterUsage/ResolveCustomer or SaaS usage-billing question.
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。
Diagnose Attio REST API failures from status, structured error fields, endpoint contract, and request context without exposing customer data. Use when an Attio request returns 400, 401, 403, 404, 409, 422, 429, or 5xx. Trigger with "Attio error", "Attio request failed", or "debug Attio API".
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 triage AssemblyAI REST, transcript, Streaming v3, webhook, and LLM Gateway failures without leaking customer content. Use when an integration errors or stalls. Trigger with "AssemblyAI error" or "failed transcript".
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。
Assemble a minimal redacted Attio diagnostic bundle with request fingerprints, schema context, retry evidence, and environment metadata. Use when escalating an Attio integration failure without leaking CRM data or secrets. Trigger with "Attio debug bundle", "Attio support evidence", or "collect Attio diagnostics".
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。
Incident response runbook for Apple Notes automation failures. Trigger: "apple notes incident".
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。
Apollo.io incident response procedures. Use when handling Apollo outages, debugging production issues, or responding to integration failures. Trigger with phrases like "apollo incident", "apollo outage", "apollo down", "apollo production issue", "apollo emergency".
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。
Diagnose and fix common Anima SDK design-to-code errors. Use when encountering Figma token errors, code generation failures, node not found issues, or output quality problems. Trigger with: "anima error", "anima not working", "anima debug", "figma to code error".
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 complex Claude API issues including context window overflow, tool use failures, streaming corruption, and response quality problems. Trigger with phrases like "anthropic advanced debug", "claude complex issue", "claude tool use failing", "claude context overflow".
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Diagnose Algolia request, credential, index, task, and query failures from concrete evidence. Use when an integration returns 4xx or 5xx responses, stale results, or unexpected empty hits. Trigger with "debug Algolia error", "Algolia 403", or "Algolia search failed".
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。