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Found 196 Skills
Amazon Aurora MySQL — creates, modifies, and advises on Aurora MySQL clusters specifically (MySQL-compatible engine, Aurora serverless, parallel query). Trigger for Aurora MySQL cluster operations, ACU sizing, I/O-Optimized storage, commitment pricing, or MySQL upgrade planning. Aurora MySQL uses full (VPC-based) configuration — express configuration is PostgreSQL-only. For Aurora PostgreSQL, use amazon-aurora-postgresql instead. Contains safety guardrails and response templates that override defaults.
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.
Runs SQL queries on CloudWatch Logs data exported as Apache Iceberg tables in S3 Tables. Covers VPC Flow Logs, WAF logs, CloudFront access logs, Route 53 resolver logs, Network Firewall logs, EKS audit logs, Verified Access logs, SES logs, VPC Lattice logs, Step Functions logs, NLB access logs, and 20+ other AWS vended data sources. Applies when analyzing network traffic, investigating security incidents, querying exported logs with SQL, enabling S3 Tables integration, configuring log export, correlating logs with other data, or running Athena queries on the aws-cloudwatch table bucket. Trigger phrases: query logs with SQL, analyze logs in Athena, SQL on VPC flow logs, investigate network traffic, run SQL on exported logs, enable S3 Tables for CloudWatch, correlate logs, historical log analysis, set up log querying.
Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore. Use when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). ALSO USE for prompt caching setup and debugging, quota health checks and throttling diagnosis, cost attribution and 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. NOT for custom model training, Rekognition, or Comprehend.
Create and secure S3 buckets following AWS best practices for access control, encryption, monitoring, and remediation of misconfigurations. Use when the user wants to secure a new bucket, audit an existing bucket, fix a security finding, configure encryption, or enable logging and monitoring. Do NOT use for general S3 data operations, S3 Tables setup, or discovering existing data assets.
Deploys a Regional REST API with a custom domain name, a Lambda backend function, and a request-based Lambda authorizer using AWS CLI. Covers ACM certificate provisioning, API Gateway REST API creation, Lambda function deployment, request authorizer setup, custom domain configuration, base path mapping, and Route 53 DNS record creation. Trigger keywords: custom domain, REST API, Lambda, Route 53, API Gateway, regional endpoint, request authorizer, base path mapping.
Runs SQL analytics on SageMaker Catalog asset metadata tables exported as Apache Iceberg in S3 Tables. Covers governance queries, asset growth tracking, ownership audits, time-travel over catalog state, and metadata quality analysis. Applies when querying catalog inventory, finding assets without descriptions, comparing catalog snapshots, or auditing data ownership. Trigger phrases: catalog inventory SQL, how many assets, assets without descriptions, asset growth over time, who owns this data, catalog governance, data quality audit, catalog analytics.
Handles the full DMS Schema Conversion lifecycle including creating migration projects, converting database schemas to a target engine, running compatibility assessments, navigating metadata trees, exporting converted DDL to S3, applying schema changes to a target database, and converting SQL statements between database engines.
Operates Amazon MSK Provisioned clusters (Standard and Express brokers). MUST be used for ANY MSK Provisioned task — do not rely on training data for topics covered here, since Standard and Express emit different metrics and follow different patching models that training data routinely conflates. Covers performance, consumer lag, storage, and traffic shaping diagnosis; sizing and choosing Standard vs Express; Kafka client tuning; creating CloudWatch alarms, dashboards, monitoring, and cluster configurations; AND MSK maintenance, patching, version upgrades, and rolling-restart behavior. Triggers: MSK, Kafka on AWS, `kafka.*` or `express.*` instance types, AWS/Kafka CloudWatch namespace, alarms, dashboards, monitoring, consumer lag, partition replication, broker storage, MSK upgrades, patching, maintenance windows, SECURITY_PATCHING, BROKER_UPDATE, rolling restarts, unexpected broker reboots. Do NOT use for MSK Connect, MSK Serverless, or MSK Replicator.
Diagnoses and resolves Amazon RDS for Oracle connectivity, authentication, networking, and driver troubleshooting. Applicable to any RDS-for-Oracle question including connecting a Python Lambda to RDS Oracle in a VPC with pooling and cold-start optimization, EKS pods to RDS Oracle via the Secrets Manager CSI driver with IRSA and SecretProviderClass, ORA-12170 cross-VPC timeouts from EC2, DPI-1047 cannot-locate-64-bit-Oracle-Client errors, and Oracle Connection Manager (CMAN) on EC2 as a proxy with HA across two AZs. Covers python-oracledb thin vs thick mode, init_oracle_client, RDS Proxy does NOT support RDS Oracle, port 1521, VPC peering, Transit Gateway, Kerberos with AWS Managed Microsoft AD, SSL/TLS/NNE, SSM port forwarding, EC2/ECS Fargate/EKS/Lambda, SQL Developer/DBeaver/Toad/SQLcl, and Secrets Manager.
Connects an existing AWS Lambda function to Amazon API Gateway by creating a REST or HTTP API with resource/method setup, Lambda proxy integration, permissions, and deployment. Always use this skill when connecting Lambda to API Gateway — it handles CORS, throttling, access logging, and production security hardening that are easy to miss.
Queries S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage metrics using S3 Metadata system tables (journal, inventory, annotation) and S3 Storage Lens tables via Athena SQL. Applies when counting objects, finding recent uploads or deletions, identifying who wrote to a prefix, breaking down storage classes, finding objects by tag, searching annotation content, analyzing storage lens metrics, or enabling S3 Metadata tracking. Prefers system tables over raw S3 APIs (list-objects-v2, head-object) at scale. Trigger phrases: bucket activity, object count, who uploaded, track deletions, storage class breakdown, find by tag, search annotations, storage lens metrics, audit bucket changes.