Conciseness

The body is largely efficient — dense routing tables, exact file paths, and no tutorial padding — but line 12's 'high-performance, secure, and reliable foundation to power agentic AI and data-driven applications' is marketing fluff, and the re-route-on-pushback rule is explained twice (Global rule 2 and 'How this skill works' step 1). These are minor over-explanations that could be trimmed, matching the 4 anchor rather than the lean-everywhere 5.

Actionability

Guidance is fully executable for an instruction-only skill: exact paths to read ('references/{sub-skill-id}.md', 'assets/{filename}'), named MCP tools (aws___read_documentation, aws___search_documentation), a prioritized lookup order (a)/(b)/(c), and a verbatim ambiguity question to ask the user. There is no pseudocode or vague direction left.

Workflow Clarity

The routing sequence is explicit (match request → read the sub-skill reference → follow its procedure) with a clearly defined no-match fallback path. Feedback loops are present: pushback matching 'report-issue' triggers forces a re-route instead of defending the prior answer, and facts must be verified against knowledge cards or documentation before being stated. No destructive or batch operations exist, so no validation cap applies.

Progressive Disclosure

The body is a true overview: three sub-skill references are one level deep and clearly signaled via the linked registry table, and 17 knowledge cards load on demand through the service reference table ('Load only the cards for services being actively considered'). All referenced paths (references/select.md, references/handoff.md, references/report-issue.md, and every assets/*.md card) were verified to exist, and no bulk detail is inlined.

Specificity

The description lists multiple concrete actions — 'Routes any task involving AWS databases — choosing, comparing, recommending, getting started with, or operating a database — to the correct service-specific skill' — and comprehensively enumerates the covered workload families and services (Aurora, DSQL, RDS, DynamoDB, Keyspaces, DocumentDB, Neptune, Timestream, ElastiCache, MemoryDB). Coverage is comprehensive for the routing niche rather than having minor gaps, so it matches the 5 anchor.

Completeness

It explicitly answers 'what' (routes database tasks to service-specific skills and supersedes stale training data) and 'when' ('Activates when a user describes building an application on AWS that will store, retrieve, or manage data, even if they do not mention database explicitly'). Both halves are concrete and explicit, matching the 5 anchor.

Trigger Term Quality

Natural trigger vocabulary is present — 'choosing', 'comparing', 'recommending', 'getting started with', 'operating', 'store, retrieve, or manage data' — plus all major AWS service names users would mention. A few common natural phrasings users actually say, such as 'which database should I use' or 'pick a database', appear only in the body and not in the description, so it falls just short of the comprehensive-synonym coverage of the 5 anchor.

Distinctiveness Conflict Risk

The niche is clear — AWS databases with named services and a routing role — giving minimal conflict with unrelated skills. However, the deliberate broadening to users who never say 'database' ('even if they do not mention database explicitly') slightly widens overlap with general AWS application-building or compute skills, which keeps it below the 5 anchor.