Conciseness

Quotes: "Recommend a database by matching the workload's access pattern and data model to an engine — not by defaulting to what is familiar. Ask for anything missing before recommending." The ~48-line body is lean and dense — a compact decision table, five pointed questions with concrete examples ("single-digit ms?", "strong vs eventual"), and no padding or explanation of concepts Claude already knows. Every line carries decision-relevant information, matching the anchor-5 standard.

Actionability

The fit-guide table gives fully concrete, lookup-ready mappings ("Known access patterns, massive scale, single-digit ms, serverless → DynamoDB", "Relational, spiky/intermittent, want true scale-to-zero SQL → Aurora DSQL") with reasons, the questions are specific enough to ask verbatim, and the Output section prescribes the exact deliverable ("State the recommended service, the one or two runner-up options, and why"). Per the rubric's instruction-only note, absence of code is not penalized when guidance is this actionable; this is the instruction-skill equivalent of anchor-5's 'specific examples cover the common cases' — the table covers all 10 services.

Workflow Clarity

The workflow is clearly sequenced: "Questions to resolve first" (an explicit checklist) → fit-guide matching → "Boundaries to call out" → "Output", with an explicit verification checkpoint: "Confirm quotas, item/row size limits, and regional availability against live documentation before committing." This is a single-purpose decision skill with no destructive or batch operations, so the anchor-3 cap does not apply, and the rubric's simple-skill note permits a 5 for an unambiguous, well-organized process.

Progressive Disclosure

The body is ~48 lines, self-contained, and organized into four clearly headed sections (Questions, Fit guide, Boundaries, Output) with no bundle files present and no content that warrants extraction to separate references. The rubric explicitly allows a 5 for skills under 50 lines with no need for external references when sections are well-organized, which this meets.

Specificity

Quotes: "Walks through access patterns, data model, consistency, scale, and cost tradeoffs across relational, key-value, document, wide-column, graph, time-series, and in-memory engines, and recommends a fit with rationale and Well-Architected considerations." It names the domain and several concrete third-person actions with broad scope coverage (10 services, 7 engine types), but the verbs remain analytic ('walks through', 'recommends') rather than enumerating the comprehensive set of concrete operations of the anchor-5 example. Not a 3 because coverage goes well beyond 1-2 actions; not a 5 because the actions themselves are fewer and more abstract than 'extract text, fill forms, merge documents'.

Completeness

Quotes: "Decision guide for choosing the right AWS database service for a workload" (explicit what) and "Use when the user is unsure which database to use, is comparing options, or asks whether to use [10 named services]" (explicit when with concrete trigger phrases). Both what and when are clearly and explicitly answered, matching the anchor-5 example structure.

Trigger Term Quality

Quotes: "Use when the user is unsure which database to use, is comparing options, or asks whether to use DynamoDB, Aurora, RDS, DocumentDB, ElastiCache, MemoryDB, Neptune, Keyspaces, or Timestream" — 10 exact service names users would mention, plus engine-category terms ("relational, key-value, document, wide-column, graph, time-series, and in-memory engines") and natural phrasings like "which database to use" and "comparing options". Not a 5 because common natural synonyms are missing: users often say "PostgreSQL/Postgres", "MongoDB", "Redis", "Cassandra", or "SQL vs NoSQL" rather than AWS product names. Clearly above a 3, which requires missing common variations outright.

Distinctiveness Conflict Risk

Quotes: "choosing the right AWS database service for a workload" and "asks whether to use DynamoDB, Aurora, RDS..." — a clear niche (AWS database selection among 10 named services) with decision-framed triggers ('whether to use', 'comparing options') that distinguish it from per-service usage or migration skills. Minimal conflict risk with the anchor-5 standard; not a 4 because the 'whether to use' framing removes the realistic overlap with service-specific skills.