Official agent skill

Querying AWS S3

by aws in aws/agent-toolkit-for-aws

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…

OfficialApache-2.0Auto-check passedBackend & APIs

Install Querying AWS S3

skills CLI
$ npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aws/agent-toolkit-for-aws querying-aws-s3 --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/specialized-skills/system-table-skills/querying-aws-s3 .claude/skills/querying-aws-s3 && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
querying-aws-s3
GitHub stars
2.8k
Token cost
~3.3k tokens
SKILL.md length
916 words
Files
1
Skills in repo
138
Repo updated
First seen
Licence
Apache-2.0

At a glance

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…

  • Works in 5 steps: Check If Configured → Enable (if not configured) → Verify Permissions → …
  • Phrases: bucket activity
  • SKILL.md covers Overview, Decision Tree, Common Tasks and Troubleshooting, plus 2 more sections
  • Calls aws

What it does

Querying AWS S3 is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. 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…

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Backend & APIs, covering File uploads and storage. It works with Amazon S3, Amazon Web Services and SQL. The repository describes itself as: Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS. The licence is Apache-2.0.

When your agent uses it

  • Phrases: bucket activity
  • Track deletions
  • Storage class breakdown
  • Search annotations

Example prompts

  • “Use the querying-aws-s3 skill to query S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage…”
  • “/querying-aws-s3”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Check If Configured
  2. Enable (if not configured)
  3. Verify Permissions
  4. Identify the Target Table
  5. Query

What it can do on your machine

Read from SKILL.md and the folder at commit 188af2f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • aws

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.aws.amazon.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Querying AWS S3 loads about 3.3k tokens when it runs. Until then it costs about 191 tokens; SKILL.md has 916 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~191
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aws/agent-toolkit-for-aws at commit 188af2f, republished under its Apache-2.0 licence (© aws). 916 words, ~3,291 tokens.

Download SKILL.mdSave it as .claude/skills/querying-aws-s3/SKILL.md (or your agent's skills folder).
name
querying-aws-s3
description
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.
version
1
argument-hint
[bucket-name|query|'configure BUCKET'|'status BUCKET']

Query 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-v2 paginates at 1000 objects/page — inefficient for large buckets (millions or billions of objects). The inventory table answers SELECT COUNT(*) in seconds at any scale.
  • list-objects-v2 cannot identify who uploaded an object, from which IP, or when something was deleted. Only the journal table has requester, source_ip_address, and delete event tracking.
  • Filtering by tag requires get-object-tagging per object. The inventory table has object_tags as a queryable map column.

Decision Tree

User intentUse this skill?TableAlternative
How many objects in my bucketYesinventory—
What was recently uploaded/deletedYesjournal—
Who wrote/deleted objects (audit)Yesjournal (requester, source_ip)—
Storage class breakdownYesinventory—
Find objects by tag or user metadataYesinventory—
Search annotation contentYesannotationSingle object → direct API get-object-annotation
Write/update an annotationNo—Direct API: put-object-annotation (tables are read-only)
Query data inside objectsNo—querying-data-lake
Bucket-level storage metrics/trendsYesStorage Lens tables—
Enable metadata trackingYessee Enable section—

Common Tasks

1. Check If Configured

Before querying, confirm S3 Metadata is enabled on the target bucket.

bash
aws s3api get-bucket-metadata-configuration --bucket <BUCKET> --region <REGION>

Interpret the response:

  • MetadataConfigurationNotFound error → 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:

bash
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:

bash
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):

bash
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:

bash
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):

bash
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>:

TableWhat it captures
journalEvent log — every CREATE, DELETE, UPDATE_METADATA, and annotation events. Near real-time.
inventoryCurrent state — one row per object (latest version). Updates within 1 hour.
annotationAnnotation payloads — text_value column holds the full content. Near real-time.

Storage Lens tables — namespace is lens_<config-id>_exp:

TableWhat it captures
default_storage_metricsPer-bucket/prefix: object count, size, storage class breakdown. Daily.
default_activity_metricsPer-bucket/prefix: GET/PUT/DELETE request counts. Daily.
bucket_property_metricsBucket config: versioning, encryption, lifecycle settings. Daily.
5. Query

Query syntax:

sql
"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-tables once 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:

sql
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:

sql
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:

sql
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:

sql
SELECT key, size, object_tags
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."inventory"
WHERE object_tags['environment'] = 'staging';

Annotation — search across payloads:

sql
SELECT object_key, name, text_value
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."annotation"
WHERE text_value LIKE '%error%';

Annotation — extract JSON fields:

sql
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:

sql
SELECT *
FROM "s3tablescatalog/aws-s3"."lens_<config-id>_exp"."default_storage_metrics"
LIMIT 20;
Show full SKILL.md (312 more words)Show less
Routing: Athena vs Direct API
ScenarioUse
Single known object + annotation nameDirect API: get-object-annotation
Aggregate/count across many objectsAthena on annotation or inventory table
Full-text search across annotation payloadsAthena with LIKE or json_extract_scalar
Write/update an annotationDirect API: put-object-annotation (table is read-only)
Feature not configured on bucketDirect API loop (list-objects-v2 + head-object); suggest enabling S3 Metadata

Troubleshooting

ErrorCauseFix
CATALOG_NOT_FOUNDS3 Tables not registered in GlueEnable integration: S3 console > Table buckets > Enable integration
Empty results from journalFeature just enabled; no events recorded yetUpload/delete an object and wait ~1 minute
Empty results from inventoryTable still BACKFILLINGCheck status; wait for ACTIVE (minutes to hours depending on object count)
AccessDenied querying tableMissing s3tables:GetTable or GetTableMetadataLocationSee Security Considerations below
Wrong namespaceBucket name has periodsPeriods are converted to underscores in namespace: my.bucket → b_my_bucket
No Storage Lens dataFirst delivery takes up to 48 hoursWait; no historical backfill

Security Considerations

Least-Privilege IAM Policy

Scope permissions to specific table bucket ARNs rather than using wildcards:

json
{
  "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 request
  • source_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:

json
{
  "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

© aws, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/specialized-skills/system-table-skills/querying-aws-s3 of aws/agent-toolkit-for-aws.

Open the folder on GitHubat commit 188af2f

Compare with similar skills

Querying AWS S3 next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Querying AWS S3 compared with similar skills
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Neon Object Storageneondatabase/agent-skills100—~3.5kAutomated safety check: NotesApache-2.0
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Remediating S3 Bucket Misconfigurationmukul975/Anthropic-Cybersecurity-Skills34k—~3kAutomated safety check: PassApache-2.0

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Questions about Querying AWS S3

What does Querying AWS S3 do?

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…. Querying AWS S3 is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. 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.

When should I use Querying AWS S3?

Querying AWS S3 fits situations like: phrases: bucket activity; track deletions; storage class breakdown; search annotations.

How do I install Querying AWS S3 in Claude Code?

Run `npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a claude-code`. Or copy the skill folder (skills/specialized-skills/system-table-skills/querying-aws-s3 in aws/agent-toolkit-for-aws) into .claude/skills/querying-aws-s3 in your project. Claude Code loads it when a task matches its description.

How do I install Querying AWS S3 in Codex?

Run `npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a codex`. Or copy the skill folder (skills/specialized-skills/system-table-skills/querying-aws-s3 in aws/agent-toolkit-for-aws) into .agents/skills/querying-aws-s3 in your project. Codex loads it when a task matches its description.

Can I use Querying AWS S3 in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/querying-aws-s3, .gemini/skills/querying-aws-s3, .github/skills/querying-aws-s3 and .opencode/skills/querying-aws-s3 in your project.

What does Querying AWS S3 need to run?

Going by SKILL.md and its folder, Querying AWS S3 needs the command-line tools its instructions call (aws).

Does Querying AWS S3 access the network?

SKILL.md names 1 domain. As links in the text: docs.aws.amazon.com. This is read from the text; nothing was executed.

Is Querying AWS S3 safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Querying AWS S3 use?

Querying AWS S3 is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Querying AWS S3 use?

About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Querying AWS S3?

Skills that share tags, products or a category with Querying AWS S3: AWS S3 (majiayu000/claude-skill-registry, 666 stars), Django Storages for S3 (Jeffallan/claude-skills, 12k stars), Neon Object Storage (neondatabase/agent-skills, 100 stars) and S3 (itsmostafa/aws-agent-skills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Querying AWS S3?

aws (a GitHub organization, an official publisher) maintains it in aws/agent-toolkit-for-aws, which has 2,825 GitHub stars. The repository holds 138 skills in this directory. The repository was last updated on October 7, 2026.

Source: aws/agent-toolkit-for-aws on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.