aws-aurora
AWS Aurora Serverless v2, RDS Proxy, Data API, connection pooling
44
32%
Does it follow best practices?
Impact
Pending
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 it names specific AWS technologies that provide some distinctiveness, it fails to communicate what the skill does or when it should be selected. It needs a complete rewrite to function as an effective skill description.
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 integrates Data API for serverless database access.'
Add an explicit 'Use when...' clause, e.g., 'Use when the user needs to set up, configure, or troubleshoot AWS Aurora Serverless v2, RDS Proxy, or Data API connections.'
Include common natural language variations users might say, such as 'AWS database', 'serverless database', 'Aurora cluster', 'database connection management', or 'RDS configuration'.
| 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 reads like a keyword list rather than a capability description. | 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. However, it misses common variations like 'database', 'serverless database', 'AWS database', 'Aurora', or 'RDS' on its own. | 2 / 3 |
Distinctiveness Conflict Risk | The AWS Aurora and RDS Proxy terms are fairly specific to a niche, which helps with distinctiveness. However, 'connection pooling' and 'Data API' are generic enough to potentially overlap with other database or API-related skills. | 2 / 3 |
Total | 6 / 12 Passed |
Implementation
42%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is highly actionable with excellent, executable code examples covering multiple Aurora access patterns, but it suffers significantly from being a monolithic reference document rather than a lean, well-structured skill. At 400+ lines with inline content for multiple languages and tools, it wastes token budget on material Claude largely already knows (basic pg pooling, Prisma schemas, boto3 patterns). The mention of separate typescript.md/python.md files in the header contradicts the fact that all language-specific content is included inline.
Suggestions
Split language-specific code (TypeScript RDS Proxy, Python Data API, Prisma setup) into the referenced typescript.md and python.md files, keeping only the connection strategy decision table and core principle in the main skill
Remove content Claude already knows well - basic pg Pool configuration, standard Prisma schema syntax, basic boto3 client usage - and focus only on Aurora-specific patterns and gotchas
Add explicit validation steps to workflows: verify RDS Proxy connectivity before deploying Lambda, check migration status after running prisma migrate deploy, validate Data API is enabled before attempting queries
Consolidate the monitoring, security, and CLI sections into a separate reference file linked from the main skill to reduce the main document to under 100 lines
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~400+ lines, including extensive code examples for multiple languages, ORMs (Prisma), connection strategies, monitoring, security, CLI reference, and more. Much of this is reference material Claude already knows (e.g., basic pg Pool usage, Prisma schema syntax, boto3 client patterns). The content tries to be a comprehensive Aurora reference rather than a lean skill. | 1 / 3 |
Actionability | The code examples are concrete, executable, and copy-paste ready across TypeScript, Python, CDK, CLI, and Prisma. Connection patterns include complete working examples with IAM auth, Data API transactions, retry logic, and Lambda handler patterns. | 3 / 3 |
Workflow Clarity | Connection strategies are clearly laid out with decision guidance, and the migration section has a reasonable sequence. However, there are no explicit validation checkpoints - for example, the migration workflow lacks verification steps (checking migration status, validating schema), and the RDS Proxy setup doesn't include steps to verify the proxy is working before deploying. | 2 / 3 |
Progressive Disclosure | Despite the header mentioning 'Load with: base.md + [typescript.md | python.md]', the skill itself is a monolithic wall containing everything inline - TypeScript, Python, Prisma, CDK, Docker, CI/CD, monitoring, security, and CLI reference. The language-specific content should be in the referenced files rather than all in one document. | 1 / 3 |
Total | 7 / 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 (646 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
d4ddb03
- Reviewed
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