Conciseness

The body is dense decision tables, executable Cypher, and rules with zero explanation of concepts Claude already knows — e.g. "Nodes = entities (nouns) with identity; rels = connections (verbs) with direction" and the two-line bucket pattern example. Every section carries non-obvious domain guidance; matches the lean/efficient anchor, not the 4 anchor (which requires identifiable over-explanation to trim).

Actionability

Guidance is copy-paste ready throughout: inspection queries ("CALL db.schema.visualization()..."), supernode detection ("count{ (n)--() } AS degree ORDER BY degree DESC LIMIT 10"), full DDL catalog ("CREATE CONSTRAINT person_id_unique IF NOT EXISTS FOR (p:Person) REQUIRE p.id IS UNIQUE"), and a concrete output-format template with severity semantics. Matches the fully-executable anchor.

Workflow Clarity

The workflow has explicit sequencing and validation checkpoints: "run first — never propose changes without current state", "poll until ONLINE" with the exact SHOW INDEXES query and "Do NOT use an index until state = ONLINE", "show + confirm first" for write-cypher, and a severity table mapping ERROR/WARNING/INFO to required actions, plus a final checklist. Feedback loops are present for the database operations context where the rubric demands them.

Progressive Disclosure

Good structure: well-organized sections, a clearly signaled one-level "References — Load on demand" list with no nested references, and an MCP tool map. However it is a ~370-line monolithic file with no bundle files — the DDL catalog, migration table, and supernode mitigation material could plausibly live in reference files, so it fits the 'good structure, minor organization gaps' anchor rather than the 'content appropriately split' anchor.

Specificity

The description lists multiple concrete actions — "Design, review, and refactor Neo4j graph data models", "migrating relational/document schemas to graph", "detecting anti-patterns (generic labels, supernodes, missing constraints)", "designing intermediate nodes for n-ary relationships", "enforcing schema with constraints and indexes" — comprehensive coverage of the skill's capabilities, matching the score-5 anchor rather than the 4 anchor whose coverage has minor gaps.

Completeness

Both questions are answered explicitly: what ("Design, review, and refactor Neo4j graph data models") and when ("Use when choosing node labels vs relationship types vs properties, migrating...") with concrete trigger phrases. It also adds explicit negative scope ("Does NOT handle Cypher query authoring..."), exceeding the score-5 anchor's requirement.

Trigger Term Quality

Natural terms a user would actually say are comprehensively covered: "graph data model", "node labels", "relationship types", "properties", "relational/document schemas", "supernodes", "constraints", "indexes", "n-ary relationships". This matches the comprehensive synonym-level coverage anchor; the 4 anchor requires only good coverage with a few natural terms missing.

Distinctiveness Conflict Risk

The Neo4j graph-modeling niche is distinct, and four explicit "Does NOT handle" clauses (Cypher authoring, Spring Data Neo4j, GraphQL, import) redirect the most likely confusion targets to named sibling skills — minimal conflict risk, matching the clear-niche anchor.