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querying-data-lake

Execute and manage Athena SQL queries across default and federated catalogs (Glue, S3 Tables, Redshift). Triggers on phrases like: query data, run SQL, athena query, analyze table, SQL query, workgroup status, profile table, query Redshift catalog, query S3 Tables. Do NOT use for finding specific data assets (use finding-data-lake-assets), full catalog audits (use exploring-data-catalog), importing data (use ingesting-into-data-lake).

71

Quality

86%

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SecuritybySnyk

Low

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SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-5

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

A well-structured operational skill: clear sequenced workflow with strong validation and error-recovery loops, appropriately split one-level-deep references, and mostly executable commands. The main improvements are deduplicating repeated MUST constraints and adding the concrete result-retrieval commands for the final presentation step.

Suggestions

Add the concrete commands for step 7 (e.g., aws athena get-query-execution for cost/scanned-bytes statistics and get-query-results or the CSV output location for retrieving rows) so the present-results step is as executable as the submit step.

Deduplicate the MUST constraints: state output-location confirmation, abort-on-request, and workgroup-before-execute once each (e.g., in a single global constraints section) and remove the repeats in section 6 and Principles.

DimensionReasoningScore

Conciseness

The body is dense and operational — no explanations of concepts Claude already knows — but several constraints are duplicated: output-location confirmation appears three times ("MUST confirm the output S3 location" in the preamble and section 6, plus "confirm the output S3 location" elsewhere), "MUST respect the user's decision to abort" twice, and the workgroup-before-execute rule twice (section 2 and Principles). This matches anchor 4 (efficient with minor instances that could be trimmed) rather than 3, since the padding is repetition of genuinely critical rules, not conceptual filler.

4 / 5

Actionability

Concrete, executable guidance dominates: "aws sts get-caller-identity", a full example "aws athena start-query-execution --work-group <WORKGROUP_NAME> ..." tool call, exact catalog-qualified addressing rules ("\"awsdatacatalog\".database.table"), and a specific troubleshooting table. It falls short of anchor 5 because step 7 ("Present results with cost, data scanned, duration") gives no command for fetching query results or execution statistics (e.g., get-query-execution / get-query-results), leaving the final presentation step abstract.

4 / 5

Workflow Clarity

A clearly sequenced 1-7 workflow with explicit validation checkpoints: dependency verification and credential check up front, statement classification with a "Treat as destructive; confirm" rule before execution, confirmation required for destructive statements, and error-recovery paths (failure handling in step 7, the Troubleshooting table, and retry rules in workgroup-selection.md). This matches the anchor-5 pattern of explicit validation steps with feedback loops for error recovery.

5 / 5

Progressive Disclosure

The body stays at overview size with decision logic inline, while bulky material is split one level deep into two real, clearly signaled reference files — "see [workgroup-selection.md](references/workgroup-selection.md)" and "see [query-patterns.md](references/query-patterns.md)" — both confirmed present in references/ and neither nesting further. The Additional Resources section indexes both plus external AWS docs, matching the anchor-5 clear-overview pattern.

5 / 5

Total

18

/

20

Passed

Description

87%Weight 40%Scale 1-5

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

A strong description with an explicit what/when pair, natural trigger phrases, and unusually good negative boundary guidance against sibling skills. The only gaps are a handful of missing natural trigger variants and the broad verb "manage" where a more specific action list would help.

DimensionReasoningScore

Specificity

The description lists several concrete actions — "Execute and manage Athena SQL queries", "profile table", "workgroup status" — against named catalogs (Glue, S3 Tables, Redshift). It sits between anchor 3 (1-2 actions) and anchor 5 (comprehensive coverage) because "manage" is broad and secondary capabilities like error recovery or cost reporting are absent.

4 / 5

Completeness

It explicitly answers both questions: "Execute and manage Athena SQL queries across default and federated catalogs" (what) and "Triggers on phrases like: query data, run SQL, athena query, ..." (when), matching the anchor-5 example structure. It is not below 5 because the trigger guidance is explicit and concrete rather than implied.

5 / 5

Trigger Term Quality

Trigger phrases are natural and varied ("query data", "run SQL", "athena query", "analyze table", "profile table", "query Redshift catalog"), giving good synonym coverage for the primary action. A few natural variants users would say are missing (e.g., "data lake", "presto", "run a query against"), so it does not reach the comprehensive anchor 5.

4 / 5

Distinctiveness Conflict Risk

The negative boundary clause "Do NOT use for finding specific data assets (use finding-data-lake-assets), full catalog audits (use exploring-data-catalog), importing data (use ingesting-into-data-lake)" explicitly disambiguates all sibling skills, giving a clear niche with minimal conflict risk.

5 / 5

Total

18

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
aws/agent-toolkit-for-aws
Reviewed

Table of Contents

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