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aws-storage

Selects, investigates, and compares AWS object, file, and block storage services, and answers cost, performance, configuration, security, and troubleshooting questions about storage services. Applies when a user asks where to store or archive data based on their usage patterns; which storage service to choose or how two compare; how to migrate data from on-premises or between AWS services; how to protect, replicate, or recover data; how to optimize storage costs; where to deploy shared NFS, SMB, or POSIX file systems; where to store vector embeddings or tabular data; what storage backs enterprise file shares, self-managed databases on EC2, VMware, or stateful containers; or asks what an AWS storage service can do or how it works. Relevant for storage needs for workloads such as AI/ML, analytics, EDA, HPC, media, genomics, or financial trading. Not applicable for SQL query engines (Athena, Spark, Redshift, EMR), ETL (Glue), streaming (Kafka, MSK, Kinesis), or managed database services (RDS, Aurora, DynamoDB).

75

Quality

92%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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.

The content is a well-structured routing skill: clear multi-step workflow with explicit verification checkpoints, excellent progressive disclosure via real one-level-deep reference files, and strong actionable guidance. Its only weakness is moderate verbosity in the Storage Options characteristic tables.

Suggestions

Tighten the Storage Options characteristic tables: trim service descriptions that restate general knowledge Claude already has, keeping only the discriminating characteristics needed for routing decisions.

Consider collapsing the Cross-Service Overlap detail into the per-service reference files or a single dedicated reference, so the SKILL.md body stays a lean decision/routing overview.

DimensionReasoningScore

Conciseness

The body is mostly efficient and free of beginner-level padding, but the lengthy Storage Options characteristic tables restate some service details a knowledgeable model already knows and could be trimmed slightly.

4 / 5

Actionability

Highly actionable with intent/decision-factor tables and concrete MUSTs (retrieve named reference files, include pricing links, ask specific clarifying questions), though per-service specifics are deferred to external reference files rather than inlined.

4 / 5

Workflow Clarity

Clear sequenced workflow (Classify Intent -> SELECT/INVESTIGATE paths) with explicit validation checkpoints ('MUST verify current numbers') and a feedback loop for retrieval failure ('name the value you could not verify rather than citing one from memory').

5 / 5

Progressive Disclosure

SKILL.md is a clear overview/router with well-signaled one-level-deep references to the 12 existing reference files (verified to have no nested references), with decision logic kept inline and per-service detail split out appropriately.

5 / 5

Total

18

/

20

Passed

Description

100%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.

The description is exemplary: it states concrete capabilities, surfaces natural user trigger phrases, explicitly answers both what and when, and sharply distinguishes itself from neighboring analytics and database skills via an explicit exclusion list.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('Selects, investigates, and compares', 'answers cost, performance, configuration, security, and troubleshooting questions') with comprehensive coverage across the storage domain, matching the highest anchor rather than the 'minor gaps' of 4.

5 / 5

Completeness

Explicitly answers both what ('Selects, investigates, and compares AWS... storage services, and answers... questions') and when ('Applies when a user asks...') with concrete trigger phrases and a clear 'Not applicable for' boundary.

5 / 5

Trigger Term Quality

Uses natural user phrasings such as 'where to store or archive data', 'which storage service to choose', and 'where to deploy shared NFS, SMB, or POSIX file systems', giving comprehensive coverage of natural trigger terms.

5 / 5

Distinctiveness Conflict Risk

Scoped to AWS object/file/block storage with an explicit exclusion list (Athena, Spark, Redshift, EMR, Glue, Kafka, MSK, Kinesis, RDS, Aurora, DynamoDB), giving a clear niche with minimal conflict risk.

5 / 5

Total

20

/

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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