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exporting-rds-to-s3

Exports Amazon RDS or Aurora database snapshots to Amazon S3 in Apache Parquet format for analytics, backup, or data migration. Handles snapshot selection or creation, IAM role setup, KMS encryption, S3 bucket preparation, export task execution, progress monitoring, and data verification. Use when exporting RDS/Aurora data to S3 for Athena, Glue, or Redshift Spectrum consumption.

70

Quality

86%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

72%

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

The body is well-organized and lean, with a clear single-level reference carrying the detailed SOP and a useful inline troubleshooting section. Its main gap is that the executable workflow and validation steps are offloaded to the reference, leaving the body's own actionability and workflow sequencing somewhat incomplete.

Suggestions

Add a short inline ordered checklist (snapshot → IAM → KMS → S3 → start export → monitor → verify) with a validation checkpoint after export completion so the body's core workflow is actionable without opening the reference.

Include one or two concrete executable commands in the main procedure section (e.g., the start-export-task and describe-export-tasks calls) so the body is copy-paste ready for the most common path.

Surface the key validation step from the reference (verify Parquet object count / sample query against S3) inline so the destructive/batch database export has an explicit feedback loop in the body.

DimensionReasoningScore

Conciseness

The body is lean with no padding and does not re-explain what RDS/S3/Parquet are; the overview briefly restates scope but every section earns its place. Not a 2 because nothing reads as unnecessarily padded.

3 / 3

Actionability

The core export procedure is delegated to the reference file ('See [RDS to S3 export procedure]') rather than given inline, though troubleshooting subsections do provide concrete API names and policy conditions. Not a 1 because guidance is specific, not vague; not a 3 because the body lacks copy-paste-ready executable steps for the main workflow.

2 / 3

Workflow Clarity

The Overview enumerates the workflow stages but the numbered sequence and validation checkpoints live in the referenced file rather than in the body; for a database/export operation the body's own checkpoints are implicit. Not a 1 because stages are named; not a 3 because no explicit validation feedback loop appears in the body itself.

2 / 3

Progressive Disclosure

A concise overview in SKILL.md points via well-signaled links to a single one-level-deep, verified-to-exist reference (references/export-rds-to-s3.md), with detail appropriately split out and no nested references.

3 / 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 concise, specific, and complete: it names the full workflow of actions, includes natural trigger terms, and gives an explicit 'Use when' clause. Third-person voice is used throughout.

DimensionReasoningScore

Specificity

Lists multiple concrete actions in third person — 'snapshot selection or creation, IAM role setup, KMS encryption, S3 bucket preparation, export task execution, progress monitoring, and data verification' — matching the comprehensive-actions anchor.

3 / 3

Completeness

Explicitly answers both 'what' (exports RDS/Aurora snapshots to S3 in Parquet) and 'when' via the 'Use when exporting RDS/Aurora data to S3...' clause, matching the top anchor.

3 / 3

Trigger Term Quality

Uses the natural terms a user would say ('RDS', 'Aurora', 'S3', 'Parquet', 'Athena, Glue, or Redshift Spectrum'), giving good coverage rather than jargon.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche (RDS/Aurora snapshot → S3 Parquet export) with distinct triggers, making it unlikely to fire for unrelated skills.

3 / 3

Total

12

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

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
Reviewed

Table of Contents

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