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Found 415 Skills
This skill guides writing cloud-init configurations for VM provisioning. Use when creating user_data blocks in Terraform/OpenTofu, or cloud-init YAML for AWS, DigitalOcean, GCP, or Azure instances.
Route53 Record Manager - Auto-activating skill for AWS Skills. Triggers on: route53 record manager, route53 record manager Part of the AWS Skills skill category.
Guides FinOps analysis on AWS, GCP, and Azure—cost visibility and allocation, tagging and showback/chargeback models, rightsizing and waste removal, RI/Savings Plan/CUD recommendations, budgets and forecasts, anomaly detection, unit economics (cost per service/customer), and FinOps cadence with engineering accountability. Use when optimizing cloud spend, analyzing CUR/billing exports, building cost dashboards, explaining bill spikes, or improving allocation—not for GL mapping, capex, depreciation, or month-end ledger close (compute-accounting-manager), enterprise EA negotiation (enterprise-cloud-architect), hands-on resource provisioning (cloud-engineer), or hardware supply efficiency (data-center-compute-supply-efficiency).
Cloud security posture management and container security assessment for AWS, Azure, GCP, and Kubernetes.
Guide for using Miso Apps SDKs (@misoapps/mail-sdk and @misoapps/shop-sdk) in Shopify apps. Use this skill when the user needs to send emails via SMTP or AWS SES, manage SMTP configurations, retrieve email logs, manage shop installations, or access shop/app data through Miso Apps services.
Execute use when generating infrastructure as code configurations. Trigger with phrases like "create Terraform config", "generate CloudFormation template", "write Pulumi code", or "IaC for AWS/GCP/Azure". Produces production-ready code for Terraform, CloudFormation, Pulumi, ARM templates, and CDK across multiple cloud providers.
This skill guides development of full-stack features on EdgeOne Pages — Edge Functions, Cloud Functions (Node.js / Go / Python runtimes), Middleware, KV Storage, and local dev workflows. It should be used when the user wants to create APIs, serverless functions, middleware, WebSocket endpoints, or full-stack features specifically on EdgeOne Pages — e.g. "create an API", "add a serverless function", "write middleware", "build a full-stack app", "add WebSocket support", "set up edge functions", "use KV storage", "create a Go API", "build a Python backend", "use Flask/FastAPI/Gin on EdgeOne Pages". Do NOT trigger for framework-native features (Next.js API routes, Next.js middleware, Nuxt server routes) or generic Express/Koa development outside an EdgeOne Pages project. Do NOT trigger for deployment — use edgeone-pages-deploy instead. Do NOT trigger for other platforms (Cloudflare Workers, Vercel Functions, AWS Lambda).
Provides authoritative compatibility checks, pricing estimates, connection troubleshooting, pre-warming guidance, and infrastructure mutations for Amazon Keyspaces (for Apache Cassandra). Covers LWT/batch operations, secondary indexes, materialized views, capacity modes, TTL, PITR, CDC, auto-scaling, multi-region keyspaces, UDTs, nodetool diagnostics parsing, SQL-to-Cassandra migration, and Cassandra-to-Keyspaces migration scenarios. Agents frequently produce incomplete or incorrect answers about Keyspaces feature support without this skill loaded.
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.
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.
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.
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.