aws-aurora
AWS Aurora Serverless v2, RDS Proxy, Data API, connection pooling
40
40%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/aws-aurora/SKILL.mdQuality
Discovery
22%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is essentially a keyword list with no verbs, no actions, and no usage guidance. While the AWS-specific terms provide some searchability, the description fails to communicate what the skill does or when it should be selected. It needs significant improvement in both specificity and completeness.
Suggestions
Add concrete action verbs describing what the skill does, e.g., 'Configures Aurora Serverless v2 clusters, sets up RDS Proxy for connection pooling, and implements Data API queries.'
Add an explicit 'Use when...' clause, e.g., 'Use when the user needs to set up, configure, troubleshoot, or optimize AWS Aurora Serverless v2 databases, RDS Proxy connections, or Data API integrations.'
Include broader natural trigger terms users might say, such as 'serverless database', 'AWS database', 'database connections', or 'Aurora scaling'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description lists technology names (Aurora Serverless v2, RDS Proxy, Data API, connection pooling) but does not describe any concrete actions. There are no verbs indicating what the skill actually does—it's just a list of keywords. | 1 / 3 |
Completeness | The description answers neither 'what does this do' nor 'when should Claude use it'. There is no 'Use when...' clause and no description of capabilities—just a comma-separated list of technology names. | 1 / 3 |
Trigger Term Quality | It includes relevant AWS-specific terms like 'Aurora Serverless v2', 'RDS Proxy', 'Data API', and 'connection pooling' that users might mention, but it misses common variations like 'database', 'serverless database', 'AWS database', or broader terms users might naturally say. | 2 / 3 |
Distinctiveness Conflict Risk | The AWS-specific technology names provide some distinctiveness, but 'connection pooling' and 'Data API' are generic enough to potentially overlap with other database or API-related skills. The lack of action descriptions makes it harder to distinguish from a general AWS or database skill. | 2 / 3 |
Total | 6 / 12 Passed |
Implementation
57%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides highly actionable, executable code examples across multiple Aurora connection strategies and tools, which is its greatest strength. However, it suffers from being a monolithic document covering too many topics (proxy, Data API, Prisma, migrations, monitoring, security, CLI) without progressive disclosure or supporting files. Workflow clarity could be improved with explicit validation steps for setup and deployment processes.
Suggestions
Split content into focused sub-files (e.g., DATA_API.md, RDS_PROXY.md, PRISMA.md, MIGRATIONS.md) and keep SKILL.md as a concise overview with links to each
Add validation checkpoints to setup workflows, e.g., 'Verify proxy connectivity: aws rds describe-db-proxy-targets' after proxy creation, or 'Test Data API: aws rds-data execute-statement ...' after enabling it
Remove the introductory sentence explaining what Aurora is — Claude already knows this — and trim redundant examples (e.g., pick one language for Data API in the main file, put the other in a reference file)
Add a decision flowchart or quick-reference section at the top summarizing when to use each connection strategy, keeping detailed examples in sub-files
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is quite long (~400 lines) and includes some redundancy (e.g., the introductory sentence explaining what Aurora is, showing both TypeScript and Python Data API examples in full, Prisma setup that could be a separate reference). However, most content is code examples rather than prose, and the tables are efficient. It could be significantly tightened. | 2 / 3 |
Actionability | Excellent actionability throughout — fully executable CDK, TypeScript, Python, Prisma, bash, and docker-compose examples with real library imports, environment variables, and copy-paste-ready patterns. Connection strategies include concrete architecture diagrams and specific configuration values. | 3 / 3 |
Workflow Clarity | Connection strategies are clearly laid out with decision guidance, and the migration workflow has sequenced steps. However, there are no explicit validation checkpoints (e.g., verifying proxy connectivity, confirming migration success, testing Data API enablement). The retry logic for scale-to-zero is good but overall the skill lacks feedback loops for setup and deployment workflows. | 2 / 3 |
Progressive Disclosure | The entire skill is a monolithic document with no references to supporting files. Given the breadth of topics (RDS Proxy, Data API, Prisma, Serverless v2, migrations, monitoring, security, CLI), this content would benefit greatly from being split into focused sub-files. The lack of any bundle files and no cross-references makes this a wall of content. | 1 / 3 |
Total | 8 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 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 | 9 / 11 Passed | |
- Repository
- alinaqi/claude-bootstrap
- Commit
7e5f7a2
- Reviewed
Table of Contents
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