finding-data-lake-assets
An agent skill by aws, from aws/agent-toolkit-for-aws. Tags: analysis, data, glue, s3, search.
What it does
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).
Install
With the skills CLI, which installs into Claude Code, Codex, Cursor and other agents:
npx skills add aws/agent-toolkit-for-aws --skill finding-data-lake-assetsOr copy the skill folder into Claude Code's skills directory by hand (~/.claude/skills for every project, or .claude/skills inside one):
git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws
cp -r agent-toolkit-for-aws/plugins/aws-data-analytics/skills/finding-data-lake-assets ~/.claude/skills/finding-data-lake-assetsSafety box score
Not rated yet. A safety box score grades what a skill and its scripts can reach on the machine of whoever installs it, across eight categories from shell execution to secrets access. Anyone can request one from this page; it is saved for everyone. How the score works.
Source
- Repository
- aws/agent-toolkit-for-aws (all skills from this repository)
- Path
- plugins/aws-data-analytics/skills/finding-data-lake-assets/SKILL.md
- Branch
- main
- Collection
- aws-data-analytics
- Updated
- 2026-09-19
Related skills
- exploring-data-catalog — Full inventory and audit of AWS Glue Data Catalog assets across S3 Tables, Redshift-federated, and remote Iceberg catalogs.
- prospecting — When the user wants to find, qualify, and build a list of prospects to reach out to — across B2B SaaS, general B2B, or local small businesses.
- creating-data-lake-table — Create managed Iceberg tables using Amazon S3 Tables (s3tables API namespace) with automatic compaction and snapshot management.
- ingesting-into-data-lake — Import data into the AWS data lake from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift.
- competitor-profiling — When the user wants to research, profile, or analyze competitors from their URLs. ' Input is a list of competitor URLs.
- competitors — When the user wants to create competitor comparison or alternative pages for SEO and sales enablement.