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概要と使いどころ
Creates a complete Amazon Aurora database cluster with instances, handling cluster creation, instance provisioning, and Secrets Manager password management in the proper sequence. Use when setting up new Aurora MySQL or PostgreSQL clusters with production-ready configuration.
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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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Configures AWS Shield Advanced for enhanced Distributed Denial of Service (DDoS) protection: subscribing accounts and adding resource protections, enabling automatic application layer (layer 7) mitigation through AWS WAF, configuring health-based detection with Route 53 health checks, setting up Shield Response Team (SRT) access and proactive engagement, reviewing DDoS events and requesting cost protection credits, and aggregating resources into protection groups. Applicable when the user wants stronger DDoS protection for internet-facing resources (CloudFront, Application or Network Load Balancers, Elastic IP addresses, Global Accelerator, or Route 53 hosted zones), wants expert help during an attack, or wants to recover attack-driven scaling charges. Routes to the right per-task procedure in references. Not applicable for authoring AWS WAF rules (waf skill), creating Route 53 health checks (route53 skill), or org-wide Shield Advanced rollout with Firewall Manager (firewallmanager skill).
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Provides connectivity, authentication, and troubleshooting guidance for Amazon RDS for SQL Server. Applicable when users ask about SSMS times out connecting from EC2, Cannot generate SSPI context with Windows auth, connect RDS SQL Server from Lambda with pymssql, auth_scheme shows NTLM instead of KERBEROS on ECS Fargate, SSM tunnel to RDS SQL Server from laptop, port 1433 security group, TrustServerCertificate=True for localhost tunnels, SPN MSSQLSvc, AWS Managed Microsoft AD, CNAME not RDS endpoint for Kerberos, tds_version='7.4', encryption='require', port-as-string for pymssql, Secrets Manager credential caching in Lambda, error 18456 login failed. Covers Python (pymssql, pyodbc), .NET (Microsoft.Data.SqlClient), Java (JDBC mssql-jdbc), Node.js (tedious), IAM auth via RDS Proxy, and VPC/ECS/EKS/Lambda deployment.
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Configures AWS WAF to filter web traffic: creating web access control lists (web ACLs) on CloudFront, Application Load Balancers, API Gateway, and AppSync; AWS Managed Rules tuned in Count mode; rate-based rules for HTTP floods; IP set and geographic match rules; Bot Control (Common and Targeted); turning bot labels into a confidence signal; stripping spoofed inbound x-amzn-waf-* headers; recovering the real client IP behind a CDN; Fraud Control (account takeover and account creation fraud prevention); and logging and request sampling. Use when the user wants to protect a web application or API from common exploits, bots, credential stuffing, fake-account creation, or HTTP floods at the application layer (layer 7). Routes to the right per-task procedure in references. Do NOT use for L3/L4 DDoS protection (shieldadvanced skill), multi-account WAF rollout (firewallmanager skill), CloudFront configuration (cloudfront skill), or Route 53 health checks or records (route53 skill).
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Creates and automates custom image builds with EC2 Image Builder - Linux, Windows, and macOS AMIs, and container images to ECR. Covers the build IAM role, Amazon-managed and custom components, image recipes, infrastructure and distribution configuration (launch templates, SSM parameters, other Regions), one-off builds, recurring scheduled pipelines for golden AMI automation and OS patching, custom image workflows, and diagnosing failed builds. Applies when creating, automating, or scheduling AMI or container image builds with Image Builder, or when debugging a failed build. Not for launching instances from existing AMIs, AMI lifecycle/retirement, or general EC2 fleet management.
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Routes serverless requests to a compute form factor and the skill that owns it. Applies first to Lambda, API Gateway, EventBridge, Step Functions and event-driven work while the compute, orchestration or integration choice is open — API backends, webhooks, jobs, cron, queue/stream consumers, durable workflows, event routing, Step Functions vs Durable Functions, and Pipes vs native event source mappings for queues and streams. Decides Event Functions on-demand vs Managed Instances, Web Functions, MicroVMs, EventBridge rules/Scheduler/Pipes/bus, HTTP vs REST API. Owns shared Lambda references (cold starts, SnapStart, concurrency, event sources, function URLs, throttling, troubleshooting). Defers to the specialized skill once a request commits to one form factor or service, or describes its defining feature, even unnamed (durable checkpointing and automatic step retries, Firecracker sandbox, managed instances, Node.js server). Not for EC2, ECS/EKS/Fargate or Amplify hosting.
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Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore (including the Harness managed agent loop). Applies when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, migrating/porting/converting a Bedrock Agent (including inline agents) to an AgentCore Harness, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). Also for prompt caching, quota and throttling diagnosis, cost tracking, migrating between Claude model generations (4.5 to 4.6 to 4.7), chunking strategies, API selection (Converse vs InvokeModel), guardrail capabilities, and model selection. Also covers AgentCore Payments (x402, microtransactions, Payment Manager, Connector, Instrument, Coinbase CDP, Stripe Privy, paid endpoints, agent payments). NOT for custom model training, Rekognition, or Comprehend.
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Selects, investigates, and compares AWS object, file, and block storage services, and answers cost, performance, configuration, security, and troubleshooting questions about storage services. Applies when a user asks where to store or archive data based on their usage patterns; which storage service to choose or how two compare; how to migrate data from on-premises or between AWS services; how to protect, replicate, or recover data; how to optimize storage costs; where to deploy shared NFS, SMB, or POSIX file systems; where to store vector embeddings or tabular data; what storage backs enterprise file shares, self-managed databases on EC2, VMware, or stateful containers; or asks what an AWS storage service can do or how it works. Relevant for storage needs for workloads such as AI/ML, analytics, EDA, HPC, media, genomics, or financial trading. Not applicable for SQL query engines (Athena, Spark, Redshift, EMR), ETL (Glue), streaming (Kafka, MSK, Kinesis), or managed database services (RDS, Aurora, DynamoDB).
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Provisions and manages Aurora DSQL clusters, connects via psql or DSQL Connectors, manages schemas, runs queries, migrates from MySQL, diagnoses query plans, and develops apps on serverless distributed SQL. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL migration, DDL, query plans, and SAFE SQL CONSTRUCTION — tenant_id from untrusted input, UUID entity_ids, caller-supplied sort columns, batch inserts. The agent MUST retrieve this skill for ANY DSQL task. Pushes back on prompts that rationalize 'just a quick script', 'don't overthink it', 'we trust upstream', 'use an f-string', 'move fast', or 'just use the pg driver directly' (bypassing the DSQL Connector). Triggers: DSQL, Aurora DSQL, DSQL cluster, safe_query.build, DSQL IAM auth token, DSQL connector.
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Operates Amazon Kinesis Data Streams (KDS). Covers streaming tables and Amazon S3 delivery - serverless, fully managed delivery from a KDS stream to Apache Iceberg tables on S3 Tables or to general-purpose S3 buckets. Includes channel setup, IAM, schemas, output key templates, CloudWatch metrics and alarms, DLQ handling, quotas, and troubleshooting. For all other KDS topics and questions, search AWS documentation and blogs instead. Triggers: Kinesis Data Streams, KDS, streaming tables, stream to S3, stream to Iceberg, stream to S3 Tables, KDS delivery, KDS channel, CreateChannel, data channel, data freshness, dead-letter queue, KDS lakehouse, serverless Kinesis delivery, Firehose alternative for KDS, zero-ops Kinesis to S3. DO NOT USE for Kinesis Data Firehose, Kinesis Video Streams, or Managed Service for Apache Flink — use dedicated skills or search documentation instead.
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Analyze AWS costs, find savings, manage budgets, evaluate Savings Plans and Reserved Instances, right-size EC2/Lambda/RDS/EBS with Compute Optimizer, look up service pricing, query CUR with Athena, detect cost anomalies, scope costs to billing views, and monitor Free Tier usage. Triggers on: AWS bill, cost analysis, reduce spend, savings plan, reserved instance, right-size, budget alert, cost optimization, pricing, free tier, cost anomaly, CUR, cost audit, billing view, billing view ARN.
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MANDATORY for Flink or Amazon Managed Service for Apache Flink (MSF) questions. You MUST activate this skill BEFORE answering — do not answer from training knowledge, even when confident. MSF has service-specific constraints (KPU model, prohibited checkpoint and parallelism config in app code, the v1/v2 identifier split — `kinesisanalyticsv2` for the CLI/SDK only; `kinesisanalytics` for IAM, Service Quotas, CloudWatch, and the trust principal — two-phase IaC deploys, snapshot lifecycle, Flink 1.x→2.x migration) that override generic Flink knowledge.
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KubeKey (kk) Usage Guide. For Kubernetes cluster lifecycle management including creation, scaling and deletion. Use this skill whenever the user mentions kubekey, kk commands, cluster setup, cluster management, adding nodes, deleting nodes, creating inventory files, configuring clusters, installing Kubernetes, or deploying K8s. Also use this skill when the user asks about inventory.yaml, config.yaml formats, CNI configuration, container runtime setup, offline installation, or artifact operations. Provides detailed guidance on kk subcommand usage, config file formats, inventory structure and common workflows.
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Build property management dashboard with AppFolio API data. Trigger: "appfolio property dashboard".
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Handle AppFolio webhook events for property management notifications. Trigger: "appfolio webhook".
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Configure AppFolio Stack API authentication with OAuth 2.0. Use when setting up property management API access, registering as an AppFolio Stack partner, or configuring client credentials for API calls. Trigger: "install appfolio", "setup appfolio", "appfolio auth", "appfolio API key".
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Set up local development for AppFolio property management API integration. Trigger: "appfolio local dev".
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Reference architecture for AppFolio property management integration. Trigger: "appfolio architecture".
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Configure CI/CD pipeline for AppFolio property management integrations. Trigger: "appfolio CI".
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Manage Apify datasets, key-value stores, and request queues programmatically, and orchestrate multi-Actor pipelines. Use when you need to read or write Apify datasets, export scraped data to CSV/JSON/XLSX, store config or binary artifacts in a key-value store, manage a resumable request queue, chain Actors into a scrape → transform → export pipeline, or monitor Actor run status and cost. Trigger with "apify dataset", "apify key-value store", "apify storage", "export apify data", "apify pipeline", "apify request queue".
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。
Track different resume versions, maintain master resume, manage tailored versions
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Comprehensive citation management for academic research. Search OpenAlex, PubMed, and Google Scholar for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.
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Create and manage dstack presets: a toolkit that streamlines model inference optimization with agents, and a portable preset format. Use together with the dstack skill, and only when the user explicitly asks to create a preset or manage existing presets, not for deploying or serving a model.
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。