
Query AWS S3 System Tables
OfficialFreeEfficiently query and analyze S3 object metadata and activity.
Free · Opens the source repo
What Query AWS S3 System Tables does
The Query AWS S3 System Tables skill provides developers and data analysts with a powerful tool to efficiently query and analyze Amazon S3 object metadata. By utilizing S3 Metadata system tables and S3 Storage Lens tables via Amazon Athena SQL, users can gain insights into bucket activity, track object changes, and analyze storage metrics without the limitations of raw S3 APIs. This skill is particularly useful for those managing large datasets in S3, as it allows for quick access to object counts, recent uploads or deletions, and detailed storage class breakdowns.
This skill operates best in conjunction with the AWS MCP server, ensuring sandboxed execution and audit logging. Users can execute commands using the AWS CLI in any environment where AWS credentials are configured. The skill emphasizes the use of system tables over traditional S3 API calls, which can be inefficient for large buckets. For instance, the inventory table allows for rapid object counting and metadata retrieval, while the journal table captures detailed event logs, including who uploaded or deleted objects.
Ideal for data engineers, cloud architects, and anyone involved in managing S3 storage, this skill simplifies complex queries and provides a structured approach to accessing S3 metadata. Users can also enable S3 Metadata tracking and Storage Lens metrics to gain a comprehensive view of their storage usage and activity trends. With its focus on performance and usability, this skill is a valuable addition for anyone working extensively with Amazon S3.
However, it is important to note that this skill is read-only; it cannot be used for writing or updating annotations directly. Users looking to perform such actions will need to utilize the appropriate S3 APIs instead. Overall, this skill streamlines the process of querying S3 metadata, making it a practical choice for those needing to audit and analyze their S3 storage efficiently.
When to use it
Use this skill when you need to quickly analyze S3 object metadata, track bucket activity, or audit changes in your S3 storage.
When not to use it
This skill is not suitable for writing or updating annotations, as it only supports read operations on S3 metadata.
What you can build with it
Count Objects in a Bucket
Quickly retrieve the total number of objects in a large S3 bucket using the inventory table.
Track Recent Uploads or Deletions
Monitor recent changes in your S3 bucket by querying the journal table for the latest events.
Analyze Storage Class Breakdown
Gain insights into the distribution of storage classes across your S3 objects with a simple query.
How to install Query AWS S3 System Tables
View source1. Install with the skills CLI
npx skills add aws/agent-toolkit-for-aws/querying-aws-s3 --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by awsQuery AWS S3 System Tables
Overview
Works best with the AWS MCP server for sandboxed execution and audit logging. All commands below use the AWS CLI and work in any environment with configured AWS credentials. Use IAM roles or temporary credentials; avoid long-lived access keys.
Amazon S3 Metadata provides continuously-updated Apache Iceberg tables that capture
object-level metadata for general-purpose buckets. S3 Storage Lens exports aggregated
storage and activity metrics as Iceberg tables. Both are read-only, stored in the
AWS-managed aws-s3 table bucket, and queryable via Amazon Athena.
System tables are preferred over raw S3 APIs (list-objects-v2, head-object) because:
list-objects-v2paginates at 1000 objects/page — inefficient for large buckets (millions or billions of objects). The inventory table answersSELECT COUNT(*)in seconds at any scale.list-objects-v2cannot identify who uploaded an object, from which IP, or when something was deleted. Only the journal table hasrequester,source_ip_address, and delete event tracking.- Filtering by tag requires
get-object-taggingper object. The inventory table hasobject_tagsas a queryable map column.
Decision Tree
| User intent | Use this skill? | Table | Alternative |
|---|---|---|---|
| How many objects in my bucket | Yes | inventory | — |
| What was recently uploaded/deleted | Yes | journal | — |
| Who wrote/deleted objects (audit) | Yes | journal (requester, source_ip) | — |
| Storage class breakdown | Yes | inventory | — |
| Find objects by tag or user metadata | Yes | inventory | — |
| Search annotation content | Yes | annotation | Single object → direct API get-object-annotation |
| Write/update an annotation | No | — | Direct API: put-object-annotation (tables are read-only) |
| Query data inside objects | No | — | querying-data-lake |
| Bucket-level storage metrics/trends | Yes | Storage Lens tables | — |
| Enable metadata tracking | Yes | see Enable section | — |
Common Tasks
1. Check If Configured
Before querying, confirm S3 Metadata is enabled on the target bucket.
aws s3api get-bucket-metadata-configuration --bucket <BUCKET> --region <REGION>
Interpret the response:
MetadataConfigurationNotFounderror → not enabled. See Enable section below.TableStatus: ACTIVE→ ready to query.TableStatus: BACKFILLING→ queryable but inventory may be incomplete.TableStatus: FAILED→ check error field (usually IAM).
For Storage Lens:
aws s3control get-storage-lens-configuration --account-id <ACCOUNT> --config-id <CONFIG_ID> --region <REGION>
Look for DataExport.StorageLensTableDestination.IsEnabled: true.
2. Enable (if not configured)
Enable S3 Metadata on a bucket:
aws s3api create-bucket-metadata-configuration \
--bucket <BUCKET> \
--region <REGION> \
--metadata-configuration '{
"JournalTableConfiguration": {"RecordExpiration": {"Expiration": "DISABLED"}},
"InventoryTableConfiguration": {"ConfigurationState": "ENABLED"}
}'
To also enable annotations (requires a service role):
aws s3api create-bucket-metadata-configuration \
--bucket <BUCKET> \
--region <REGION> \
--metadata-configuration '{
"JournalTableConfiguration": {"RecordExpiration": {"Expiration": "ENABLED", "Days": 90}},
"InventoryTableConfiguration": {"ConfigurationState": "ENABLED"},
"AnnotationTableConfiguration": {"ConfigurationState": "ENABLED", "Role": "<ROLE_ARN>"}
}'
Enable Storage Lens S3 Tables export:
aws s3control put-storage-lens-configuration \
--account-id <ACCOUNT> \
--config-id <CONFIG_ID> \
--region <REGION> \
--storage-lens-configuration '{
"Id": "<CONFIG_ID>",
"IsEnabled": true,
"AccountLevel": {"BucketLevel": {}},
"DataExport": {
"StorageLensTableDestination": {"IsEnabled": true}
}
}'
Register S3 Tables federated catalog in Glue (required for Athena access):
aws glue create-catalog --region <REGION> --cli-input-json '{
"Name": "s3tablescatalog",
"CatalogInput": {
"FederatedCatalog": {
"Identifier": "arn:aws:s3tables:<REGION>:<ACCOUNT>:bucket/*",
"ConnectionName": "aws:s3tables"
}
}
}'
For setup permissions and IAM role requirements, see Security Considerations below.
3. Verify Permissions
Querying requires:
- Athena execution permissions
- S3 Tables read permissions (see least-privilege policy in Security Considerations)
- The S3 Tables federated catalog registered in Glue (
s3tablescatalog) - Athena workgroup with SSE-KMS encryption configured on the output location
If CATALOG_NOT_FOUND errors occur, the Glue integration may not be enabled. See:
Integrating S3 Tables with AWS analytics services
4. Identify the Target Table
S3 Metadata tables — namespace is b_<bucket-name>:
| Table | What it captures |
|---|---|
journal | Event log — every CREATE, DELETE, UPDATE_METADATA, and annotation events. Near real-time. |
inventory | Current state — one row per object (latest version). Updates within 1 hour. |
annotation | Annotation payloads — text_value column holds the full content. Near real-time. |
Storage Lens tables — namespace is lens_<config-id>_exp:
| Table | What it captures |
|---|---|
default_storage_metrics | Per-bucket/prefix: object count, size, storage class breakdown. Daily. |
default_activity_metrics | Per-bucket/prefix: GET/PUT/DELETE request counts. Daily. |
bucket_property_metrics | Bucket config: versioning, encryption, lifecycle settings. Daily. |
5. Query
Query syntax:
"s3tablescatalog/aws-s3"."<namespace>"."<table>"
Constraints:
-
You MUST confirm workgroup and output location before executing
-
You MUST ensure the Athena workgroup enforces SSE-KMS encryption on query results
-
You MUST warn user that tables are read-only — no INSERT/UPDATE/DELETE
-
You SHOULD use the key columns documented in this skill to build queries. If you need the full schema (e.g., AWS has added new columns), run
get-tablesonce on any single namespace — schemas are identical across all instances of the same table type:aws glue get-tables --catalog-id "<ACCOUNT>:s3tablescatalog/aws-s3" --database-name "<namespace>" --region <REGION>
Journal — audit who changed what:
SELECT key, record_type, record_timestamp, requester, source_ip_address
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."journal"
WHERE record_type = 'DELETE'
AND record_timestamp > current_timestamp - interval '24' hour
ORDER BY record_timestamp DESC;
Journal — track annotation events:
SELECT key, record_type, annotation.name, record_timestamp
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."journal"
WHERE record_type IN ('CREATE_ANNOTATION', 'DELETE_ANNOTATION', 'UPDATE_ANNOTATION_METADATA')
ORDER BY record_timestamp DESC LIMIT 20;
Inventory — find objects by storage class:
SELECT key, size, storage_class, last_modified_date
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."inventory"
WHERE storage_class = 'GLACIER'
ORDER BY size DESC LIMIT 50;
Inventory — find objects by tag:
SELECT key, size, object_tags
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."inventory"
WHERE object_tags['environment'] = 'staging';
Annotation — search across payloads:
SELECT object_key, name, text_value
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."annotation"
WHERE text_value LIKE '%error%';
Annotation — extract JSON fields:
SELECT object_key, json_extract_scalar(text_value, '$.status') as status
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."annotation"
WHERE name = 'pipeline_status'
AND json_extract_scalar(text_value, '$.status') = 'FAILED';
Storage Lens — storage distribution:
SELECT *
FROM "s3tablescatalog/aws-s3"."lens_<config-id>_exp"."default_storage_metrics"
LIMIT 20;
Routing: Athena vs Direct API
| Scenario | Use |
|---|---|
| Single known object + annotation name | Direct API: get-object-annotation |
| Aggregate/count across many objects | Athena on annotation or inventory table |
| Full-text search across annotation payloads | Athena with LIKE or json_extract_scalar |
| Write/update an annotation | Direct API: put-object-annotation (table is read-only) |
| Feature not configured on bucket | Direct API loop (list-objects-v2 + head-object); suggest enabling S3 Metadata |
Troubleshooting
| Error | Cause | Fix |
|---|---|---|
CATALOG_NOT_FOUND | S3 Tables not registered in Glue | Enable integration: S3 console > Table buckets > Enable integration |
| Empty results from journal | Feature just enabled; no events recorded yet | Upload/delete an object and wait ~1 minute |
| Empty results from inventory | Table still BACKFILLING | Check status; wait for ACTIVE (minutes to hours depending on object count) |
AccessDenied querying table | Missing s3tables:GetTable or GetTableMetadataLocation | See Security Considerations below |
| Wrong namespace | Bucket name has periods | Periods are converted to underscores in namespace: my.bucket → b_my_bucket |
| No Storage Lens data | First delivery takes up to 48 hours | Wait; no historical backfill |
Security Considerations
Least-Privilege IAM Policy
Scope permissions to specific table bucket ARNs rather than using wildcards:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"s3tables:GetTable",
"s3tables:GetTableMetadataLocation",
"s3tables:GetTableData",
"s3tables:GetNamespace",
"s3tables:ListTables",
"s3tables:ListNamespaces",
"s3tables:GetTableBucket"
],
"Resource": [
"arn:aws:s3tables:<REGION>:<ACCOUNT>:bucket/aws-s3",
"arn:aws:s3tables:<REGION>:<ACCOUNT>:bucket/aws-s3/*"
]
}
]
}
Data Sensitivity
Journal query results may contain sensitive fields:
requester— AWS account ID or service principal that made the requestsource_ip_address— IP address of the requester
Query results containing these fields should be stored in encrypted, access-controlled locations. Avoid logging or sharing raw query output that contains IP addresses or principal identifiers.
Encryption for Query Results
Configure the Athena workgroup with EncryptionConfiguration to encrypt query results at rest:
{
"ResultConfiguration": {
"EncryptionConfiguration": {
"EncryptionOption": "SSE_KMS",
"KmsKey": "arn:aws:kms:<REGION>:<ACCOUNT>:key/<KEY_ID>"
}
}
}
Audit Trail
Enable CloudTrail logging for Athena (StartQueryExecution, GetQueryResults) and S3 Tables (s3tables:GetTableData) API calls to maintain an audit trail of who queried what metadata. Ensure CloudTrail logs are encrypted with SSE-KMS and stored in a bucket with access logging enabled.
Additional Resources
Frequently asked questions about Query AWS S3 System Tables
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