exploring-data-catalog
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).
下記のコマンドをコピーしてターミナル(Mac/Linux)または PowerShell(Windows)に貼り付けてください。 ダウンロード → 解凍 → 配置まで全自動。
mkdir -p ~/.claude/skills && cd ~/.claude/skills && curl -L -o exploring-data-catalog.zip https://jpskill.com/download/23345.zip && unzip -o exploring-data-catalog.zip && rm exploring-data-catalog.zip
$d = "$env:USERPROFILE\.claude\skills"; ni -Force -ItemType Directory $d | Out-Null; iwr https://jpskill.com/download/23345.zip -OutFile "$d\exploring-data-catalog.zip"; Expand-Archive "$d\exploring-data-catalog.zip" -DestinationPath $d -Force; ri "$d\exploring-data-catalog.zip"
完了後、Claude Code を再起動 → 普通に「動画プロンプト作って」のように話しかけるだけで自動発動します。
💾 手動でダウンロードしたい(コマンドが難しい人向け)
- 1. 下の青いボタンを押して
exploring-data-catalog.zipをダウンロード - 2. ZIPファイルをダブルクリックで解凍 →
exploring-data-catalogフォルダができる - 3. そのフォルダを
C:\Users\あなたの名前\.claude\skills\(Win)または~/.claude/skills/(Mac)へ移動 - 4. Claude Code を再起動
⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。
🎯 このSkillでできること
下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。
📦 インストール方法 (3ステップ)
- 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
- 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
- 3. 展開してできたフォルダを、ホームフォルダの
.claude/skills/に置く- · macOS / Linux:
~/.claude/skills/ - · Windows:
%USERPROFILE%\.claude\skills\
- · macOS / Linux:
Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。
詳しい使い方ガイドを見る →- 最終更新
- 2026-05-18
- 取得日時
- 2026-05-18
- 同梱ファイル
- 2
📖 Claude が読む原文 SKILL.md(中身を展開)
この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。
Structured inventory and cataloging across your AWS data landscape: Glue Data Catalog with S3 Tables, Redshift-federated, and remote Iceberg catalogs.
Overview
Maps data in an AWS account. Starts with catalog landscape (Glue, S3 Tables, federated), then drills into databases and tables. Read-only — no query execution.
Constraints for parameter acquisition:
- You MUST ask for the target AWS region upfront if not provided
- You MUST support a single optional argument: search term, catalog name, database name, S3 path, or table name
- You MUST accept the argument as direct input or a pointer to a file containing the spec
- You MUST confirm the scope (full landscape vs. targeted deep dive) before making API calls
- You MUST respect the user's decision to abort at any step
Common Tasks
Pagination: All list and search calls in this workflow may return paginated results. You MUST pass --next-token from the previous response until no more tokens are returned. You MUST NOT assume a single page contains all results.
1. Verify Dependencies
Check for required tools and AWS access before discovery.
Constraints:
- You MUST verify AWS MCP server tools are available (
aws___call_aws,aws___search_documentation) and fall back to AWS CLI if not - You MUST confirm credentials are valid:
aws sts get-caller-identity - You MUST inform the user about any missing tools and ask whether to proceed
2. Discover Catalogs
List catalogs in account:
aws glue get-catalogs --recursive --include-root
Classify each catalog by type:
| Field Present | Catalog Type | What It Contains |
|---|---|---|
Neither TargetRedshiftCatalog nor FederatedCatalog |
Default (Glue) | Standard Glue databases and tables |
FederatedCatalog.ConnectionName = aws:s3tables |
S3 Tables | Managed Iceberg table buckets |
TargetRedshiftCatalog |
Redshift-federated | Redshift databases exposed as Glue catalogs |
FederatedCatalog with ConnectionName ≠ aws:s3tables |
Remote Iceberg | External catalogs (Snowflake, Databricks, Iceberg REST) |
Constraints:
- You MUST include
--include-rootto capture default account catalog - You MUST present summary of catalog counts by type
- If only default catalog exists, You SHOULD skip catalog overview and go to step 3
3. Enumerate Databases and Tables
For each catalog (or the user-specified one):
aws glue get-databases --catalog-id <catalog-id>
aws glue get-tables --database-name <db> --catalog-id <catalog-id>
For S3 Tables catalogs, also enumerate via the S3 Tables API:
aws s3tables list-table-buckets
aws s3tables list-namespaces --table-bucket-arn <arn>
aws s3tables list-tables --table-bucket-arn <arn> --namespace <ns>
Constraints:
- You MUST flag S3 Tables not registered in Glue; You SHOULD suggest registration
- For sub-catalogs,
--catalog-idaccepts the catalog name (not the ARN) - For the default catalog, omit
--catalog-idor pass the account ID
4. Capture Details and Analyze
For each database, capture table count, formats, partitioning, and S3 locations. For each table of interest, capture column schemas, types, partition keys, SerDe format, and last access time.
You MUST report data formats in human-readable terms (Parquet, CSV, JSON), not raw SerDe class names.
See discovery-checklist.md for analysis framework.
Argument Routing
Resolve the argument in this order; stop at the first match:
- Starts with
s3://— S3 path (explore unregistered data, detect formats) - Matches a known catalog from step 2 (
get-catalogs) — deep dive into that catalog - Matches a known database (
get-databases) — deep dive into that database - Matches a known table (
get-tables) — detailed table analysis with schema and partitions - No match — treat as search term (Glue
search-tables) - No args — full landscape discovery (catalogs, then databases and tables)
Principles
- Start with catalog landscape, then narrow based on user interest
- Always report catalog types — users need to know where data lives
- Always report data formats — they drive cost and performance decisions
- Flag stale tables and missing descriptions
- Suggest partitioning for large unpartitioned tables
- Summary first, details on request
- You MUST NOT execute Athena queries (
start-query-execution) during discovery; query execution belongs toquerying-data-lake
Troubleshooting
| Error | Cause | Fix |
|---|---|---|
| Only sub-catalogs returned, default missing | --include-root omitted |
Re-run get-catalogs with --include-root |
| Federated catalog query slow or failing | Network call to remote source; connection misconfigured | Report connection errors clearly rather than silently skipping |
| S3 Tables not queryable via Athena | Tables exist in S3 Tables API but not registered in Glue | Flag as "not queryable"; suggest registration |
get-databases/get-tables fails with catalog-id |
Default catalog requires omit or account ID | Omit --catalog-id or pass account ID for the default catalog |
Additional Resources
同梱ファイル
※ ZIPに含まれるファイル一覧。`SKILL.md` 本体に加え、参考資料・サンプル・スクリプトが入っている場合があります。
- 📄 SKILL.md (6,097 bytes)
- 📎 references/discovery-checklist.md (2,931 bytes)