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Found 10,428 Skills
Full inventory and audit of AWS Glue Data Catalog assets across S3 Tables, Redshift-federated, and remote Iceberg catalogs. Triggers on: inventory the catalog, audit databases, list all tables, catalog overview, data landscape, enumerate catalogs, data inventory, search the catalog. Do NOT use for finding specific data (use finding-data-lake-assets), running queries (use querying-data-lake), or creating tables (use creating-data-lake-table).
Import data into the AWS data lake from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, or existing Glue catalog tables (migration). Default target is S3 Tables; standard Iceberg on a general purpose bucket is supported where S3 Tables is not adopted. Handles one-time loads, recurring pipelines, migrations. Triggers on: import data, load data, ingest, sync database, migrate table, move data to AWS, set up pipeline, ETL, pull from Snowflake, query BigQuery into S3, export DynamoDB, CTAS, convert to Iceberg. Do NOT use for setting up or troubleshooting Glue connections (use connecting-to-data-source), creating empty tables (use creating-data-lake-table), running queries (use querying-data-lake), finding tables by fuzzy name (use finding-data-lake-assets), catalog audit (use exploring-data-catalog), or SaaS platforms like Salesforce, ServiceNow, SAP, MongoDB, Kafka.
Resolve data lake and lakehouse asset references across Glue Data Catalog, S3, S3 Tables, and Redshift. Triggers on: find the table, where is our data, which table has, locate dataset, find data for, search catalog, what tables match, Redshift table, lakehouse table, data lake table, warehouse table, reverse lookup S3 path. Do NOT use for: full catalog audits (use exploring-data-catalog), running queries (use querying-data-lake), creating tables (use creating-data-lake-table).
Create managed Iceberg tables using Amazon S3 Tables (s3tables API namespace) with automatic compaction and snapshot management. Sets up table bucket, namespace, table, schema, Glue catalog registration, partitioning, IAM access control. Triggers on: create table, data lake table, analytics table, structured data storage, S3 Tables, Iceberg, Athena table, partitioning strategy, access permissions. Do NOT use for: importing files (use ingesting-into-data-lake), vector storage (use storing-and-querying-vectors), querying existing tables (use querying-data-lake), or locating existing table (use finding-data-lake-assets).
Quick health checks for a Dockerized VPS. Use to verify services are running, check container status, view logs, or get a system overview (disk, memory, CPU). Read-only by design — anything that would change state is routed through the clipboard for the user to paste.
Interactive macOS system cleanup for any dev machine. Frees disk space by pruning caches, package managers, unused apps, stale dev artifacts, and more. Discovers what's installed rather than assuming a specific setup. Always consults the user before deleting anything. Use when the user asks to: clean up their Mac, free disk space, remove unused apps, prune caches, clean developer artifacts, or any disk space maintenance task.
Safely inspect .env files by showing key names and clearly non-sensitive values while redacting anything that looks like a secret. Best-effort heuristic redaction (keyword block + token-pattern blocklist + Shannon-entropy check + value allowlist) — not a cryptographic guarantee. Use when you need to understand a project's environment configuration without exposing credentials.
Interviews the user about a product idea or feature using structured questions, then generates a detailed spec document (SPEC.md). Use when the user wants to flesh out an idea, plan a feature, or create a buildable specification.
Create a personal GitHub coding retrospective from a date range and turn it into a short Markdown review. Research commit activity across accessible public and private repositories through the authenticated gh CLI, understand what the relevant repositories and subsystems are for, and write a prose retrospective with stats and highlights. Use when the user asks for a commit review, coding recap, engineering retrospective, GitHub activity story, weekly/monthly/yearly highlights, or a written summary of what their commits achieved.
Generate an offline-first dependency overview across services in a Docker-compose monorepo. Reports image tags & pinning quality, Dockerfile base images, runtime hints (Node/Python via .nvmrc, .python-version, package.json engines, pyproject.toml), and lockfile presence. Use when you want a single report of "what am I running and where are my update surfaces?" — no network calls, no pulls.
Configures Amazon Route 53 to route traffic to a CloudFront distribution using a custom domain. Use when setting up DNS alias records, alternate domain names (CNAMEs), ACM certificates for HTTPS, and IPv6 support for CloudFront.
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.