aws-aurora

AWS Aurora Serverless v2, RDS Proxy, Data API, connection pooling

Quality

—

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

65%

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

This is a comprehensive, highly actionable Aurora reference with strong executable examples, but it is a monolithic single file and treats risky operations like migrations without explicit validation feedback loops. Conciseness and workflow structure are the main drags on an otherwise strong skill.

Suggestions

Trim the conceptual intro paragraph and section openers that restate what Claude already knows about Aurora, keeping only the decision-oriented guidance.

Add explicit validation/verification checkpoints to the migration and cluster-deletion workflows (e.g. verify migration applied, check cluster status before/after deletion) to lift workflow clarity.

Split large reference blocks (Data API, Prisma, Security, CLI reference) into separate files in references/ and link to them from SKILL.md to enable proper progressive disclosure.

Dimension	Reasoning	Score
Conciseness	The body is mostly dense, actionable code and tables, but the opening ("Amazon Aurora is a MySQL/PostgreSQL-compatible relational database...") and a few section openers restate concepts Claude already knows, and the ~640-line length could be tightened.	2 / 3
Actionability	It provides abundant executable TypeScript, Python, bash, CDK, and Prisma examples with concrete config values and CLI commands that are copy-paste ready, matching the fully-executable anchor.	3 / 3
Workflow Clarity	Content is well organized by topic with decision tables and strategy comparisons, but multi-step risky operations (schema migrations, cluster deletion) lack explicit validation/verification checkpoints, capping workflow clarity at 2 per the rubric.	2 / 3
Progressive Disclosure	Sections are clearly headed and organized, but the entire reference is a single monolithic SKILL.md with no bundle files or external references, so content that could be split (Data API, Prisma, Security) is inline rather than one level deep.	2 / 3
	Total	9 / 12 Passed

Description

50%

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 a compact, domain-specific keyword list rather than a sentence stating actions and triggers. It is specific to Aurora but lacks action verbs and an explicit use-when clause, capping most dimensions at 2.

Suggestions

Rewrite as a third-person action sentence, e.g. "Configures and deploys AWS Aurora Serverless v2, RDS Proxy, and the Data API, with connection-pooling guidance for Lambda."

Add an explicit trigger clause: "Use when working with AWS Aurora/RDS databases, serverless database scaling, or Lambda-to-Aurora connection management."

Include natural term variations users would say (PostgreSQL, MySQL, database, serverless database) to broaden trigger coverage.

Dimension	Reasoning	Score
Specificity	The description "AWS Aurora Serverless v2, RDS Proxy, Data API, connection pooling" names the domain and several concrete components, but it is a noun-list with no action verbs (e.g. configure, deploy), so it does not reach the multiple-concrete-actions bar of 3.	2 / 3
Completeness	It conveys "what" via the component list but has no explicit "Use when..." trigger clause (that guidance lives in a separate when-to-use field), so per the rubric completeness is capped at 2.	2 / 3
Trigger Term Quality	Terms like "AWS Aurora", "RDS Proxy", and "Data API" are natural for AWS users, but it misses common variations (database, PostgreSQL, MySQL) and reads as a terse keyword dump rather than broad natural-language coverage.	2 / 3
Distinctiveness Conflict Risk	The Aurora-specific niche is fairly distinct, but the bare keyword list could overlap with a generic RDS/PostgreSQL skill and lacks disambiguating trigger phrasing, keeping it below 3.	2 / 3
	Total	8 / 12 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (645 lines); consider splitting into references/ and linking	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: alinaqi/claude-bootstrap
Commit: 9dacc46

Reviewed: about 6 hours ago

Table of Contents

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