querying-aws-s3

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.

Quality

88%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

77%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable with strong workflow sequencing and validation, but it is a dense single-file document that could shed generic security prose and split reference material into bundle files for better token efficiency and progressive disclosure.

Suggestions

Trim or move the generic Audit Trail / Data Sensitivity guidance, which restates security concepts Claude already knows, keeping only the S3-tables-specific least-privilege policy.

Split the full IAM policy, Athena workgroup encryption JSON, and the query-example catalog into reference files under ./references/ with one-level-deep links from SKILL.md to improve progressive_disclosure.

Move detailed enable/Storage-Lens setup steps into a separate SETUP.md and keep SKILL.md as an overview + decision tree + quick-query recipes.

Dimension	Reasoning	Score
Conciseness	Mostly efficient and domain-specific, but some passages teach things Claude knows (generic CloudTrail/audit-trail and data-sensitivity advice) and the long inline IAM/encryption JSON could be trimmed, so not every token earns its place.	2 / 3
Actionability	Copy-paste-ready bash commands, SQL queries with placeholders, and complete IAM/encryption JSON blocks give fully executable guidance throughout.	3 / 3
Workflow Clarity	A clearly numbered sequence (Check Configured -> Enable -> Verify Permissions -> Identify Table -> Query) with validation checkpoints (TableStatus interpretation, CATALOG_NOT_FOUND handling, MUST constraints) and a troubleshooting table; operations are read-only so no destructive-loop gap applies.	3 / 3
Progressive Disclosure	No bundle files exist and the skill is a monolithic ~300-line document with detail (full IAM policy, encryption config, full query catalog) inlined rather than split out; the only references are external AWS docs links, so structure is decent but disclosure is not progressive.	2 / 3
	Total	10 / 12 Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is exemplary: third-person voice, concrete actions, explicit 'when' triggers, and a distinct AWS S3-metadata niche with no fluff.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions ('Queries S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage metrics') rather than vague language.	3 / 3
Completeness	Clearly answers both 'what' (the opening action list and underlying system tables) and 'when' via an explicit 'Applies when...' clause plus trigger phrases, satisfying the explicit-trigger requirement.	3 / 3
Trigger Term Quality	Explicit 'Trigger phrases:' clause provides natural terms users would say ('bucket activity, object count, who uploaded, track deletions, storage class breakdown, find by tag, search annotations, storage lens metrics, audit bucket changes').	3 / 3
Distinctiveness Conflict Risk	A clear niche (S3 Metadata/Storage Lens system tables via Athena SQL) with distinct triggers unlikely to collide with other skills.	3 / 3
	Total	12 / 12 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: aws/agent-toolkit-for-aws
Path: skills/specialized-skills/system-table-skills/querying-aws-s3/SKILL.md
Commit: 222ce56

Reviewed: 3 days ago

Table of Contents

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