finding-data-lake-assets

Deploys, hosts, or runs a container or Docker app on Amazon Lightsail Container Service and returns a live, managed HTTPS URL at a flat monthly price — no cluster, VPC, load balancer, or registry to set up. Used when deploying a container image to Lightsail from a local Docker build, a public registry image, or a GitHub repo, or when a Lightsail container deployment fails or won't serve — including when the request doesn't name Lightsail but asks to run one always-on container behind a public URL at a flat, predictable monthly price. Not for running an app on a Lightsail instance (VM) or Amazon EC2 instead of the container service, and not for workloads needing Kubernetes, autoscaling, scale-to-zero, or per-request pricing (use Amazon ECS/EKS or ECS Express Mode).

Build and deploy full-stack web and mobile apps with AWS Amplify Gen2 (TypeScript code-first). Covers auth (Cognito), data (AppSync/DynamoDB), storage (S3), functions, APIs, and AI (Amplify AI Kit with Bedrock). Supports React, Next.js, Vue, Angular, React Native, Flutter, Swift, and Android. Always use this skill for Amplify Gen2 topics — even for questions you think you know — it contains validated, version-specific patterns that prevent common mistakes. TRIGGER when: user mentions Amplify Gen2; project has amplify/ directory or amplify_outputs; code imports @aws-amplify packages; user asks about defineBackend, defineAuth, defineData, defineStorage, defineFunction, or npx ampx. SKIP: Amplify Gen1 (amplify CLI v6), standalone SAM/CDK without Amplify (use aws-serverless), direct Bedrock without Amplify AI Kit (use bedrock).

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.

Enables Redshift system-table (SYS_*) log publishing to S3 Tables in Apache Iceberg format for both Provisioned clusters and Serverless namespaces, verifies publishing status, and queries the published logs via any Iceberg-compatible engine including Redshift and Athena. Covers system tables such as sys_query_history, sys_query_text, sys_connection_log, sys_query_detail, and sys_session_history. Applies when turning on S3 Tables log publishing for a cluster or namespace, confirming publishing status and locating the S3 Tables namespace, querying non-realtime data from Redshift system tables off-cluster at scale, or building dashboards for Redshift monitoring and auditing, especially for historical or high-volume system-table data beyond the in-cluster SYS_ view retention window. Trigger phrases: publish redshift system table log to s3 tables, enable-logging s3 tables, describe redshift logging status, query redshift system tables in athena or redshift, redshift log exports to iceberg.

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.

Runs SQL queries on Amazon Athena query history exported as an Apache Iceberg table in S3 Tables. The query_executions system table captures per-query metadata (query text, IAM principal, work group, statement type, data scanned, timing breakdown, error details, tables accessed, result reuse, engine version) for every completed query. Applies when analyzing Athena usage and cost, finding who ran a query, auditing table access, tracking data scanned by user or work group, investigating slow or failed queries, detecting performance regressions, reporting query history beyond the 45-day API window, or enabling Athena system tables. Prefers the system table over the ListQueryExecutions and GetQueryExecution APIs at scale. Trigger phrases: Athena query history, who ran this query, data scanned by user, most queried tables, slowest queries, failed query analysis, Athena cost by work group, query audit trail, enable Athena system tables.

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.

About 450 ready-made HyperFrames blocks and components installed as editable source - transitions, overlays, titles, kinetic type, captions, charts, map overlays, 3D, camera moves. Use it before hand-building any named visual (CRT scanlines, glitch, film grain, a chart); also for hyperframes add and catalog.

Postgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pg_cron, pgmq), vector/semantic search (pgvector), and restoring dumps (pg_restore) or importing data. Also load it when diagnosing slow queries, high CPU, timeouts, EXPLAIN plans, connection exhaustion, locking, bloat, or rows visible to the wrong user or tenant. This is not just a performance guide — schema, migration, security, and SQL authoring tasks need these rules too, even for a one-column change or a single query.

Deprecated compatibility name for prisma-orm-setup. Use only when a user or existing integration explicitly invokes prisma-database-setup; otherwise select prisma-orm-setup.

Deprecated compatibility name for prisma-postgres-setup. Use only when a user or existing integration explicitly invokes prisma-postgres; otherwise select prisma-postgres-setup.

Obtain or reuse a Prisma Postgres database and connect an application. Use when the user needs a database and has none configured ("I need a database", "add a Postgres database", "set up a database for this app"), runs or mentions `create-db` or `npx create-db`, or asks to set up or connect Prisma Postgres, including in v0 and the Vercel Marketplace. Hands Prisma ORM configuration to prisma-orm-setup; reuses an existing connection first and honors an explicit provider, driver, alternative ORM, or database-only choice.

Required reference for Prisma ORM 7 SQL driver adapter work. Use when implementing or modifying adapters, adding database drivers, or touching SqlDriverAdapter, Transaction, savepoint, result mapping, or DriverAdapterError behavior. Covers current transaction lifecycle, optional savepoint hooks, original database-error preservation, and verification.

Use when doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector); debugging and troubleshooting errors or unexpected behavior on Supabase projects (HTTP errors, Postgres errors, RLS surprises, permission denied, schema cache issues, timeouts, Edge Function crashes, Realtime drops, Storage failures) and reading or querying logs (Logs Explorer, ClickHouse).

Set up Prisma ORM in an application, connect its database, or troubleshoot the connection of an existing Prisma 6, 7, or 8 app. Defaults new applications to Prisma ORM 8 and loads the package-owned prisma-8 skill; keeps existing Prisma 6/7 apps on their version with provider references for PostgreSQL, MySQL, SQLite, SQL Server, CockroachDB, MongoDB, and Prisma Postgres.