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neo4j-modeling-skill

Design, review, and refactor Neo4j graph data models. Use when choosing node labels vs relationship types vs properties, 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, or assessing an existing model against graph modeling best practices. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle Spring Data Neo4j entity mapping — use neo4j-spring-data-skill. Does NOT handle GraphQL type definitions — use neo4j-graphql-skill. Does NOT handle data import — use neo4j-import-skill.

72

Quality

88%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Discovery

100%

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 is an exemplary skill description that excels across all dimensions. It provides highly specific capabilities, rich natural trigger terms, complete what/when guidance, and outstanding distinctiveness through explicit boundary-setting with related skills. The negative boundary clauses ('Does NOT handle') are a particularly effective technique for disambiguation in a multi-skill environment.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: design/review/refactor data models, choosing node labels vs relationship types vs properties, migrating relational/document schemas, detecting anti-patterns (with examples), designing intermediate nodes, enforcing schema with constraints and indexes, assessing models against best practices.

3 / 3

Completeness

Clearly answers 'what' (design, review, refactor Neo4j graph data models with detailed sub-tasks) and 'when' (explicit trigger scenarios like choosing node labels vs relationships, migrating schemas, detecting anti-patterns). The 'Use when...' clause is present and comprehensive. Additionally, the 'Does NOT handle' exclusions further clarify when NOT to use it.

3 / 3

Trigger Term Quality

Excellent coverage of natural terms users would say: 'Neo4j', 'graph data model', 'node labels', 'relationship types', 'properties', 'relational schema', 'anti-patterns', 'supernodes', 'constraints', 'indexes', 'n-ary relationships'. These are terms a user working with Neo4j modeling would naturally use.

3 / 3

Distinctiveness Conflict Risk

Exceptionally distinctive — explicitly delineates boundaries with four related Neo4j skills (cypher, spring-data, graphql, import) using 'Does NOT handle' clauses with skill name references. This makes it nearly impossible to confuse with adjacent skills.

3 / 3

Total

12

/

12

Passed

Implementation

77%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a strong, highly actionable skill with excellent decision tables, executable Cypher examples, and a well-defined workflow from inspection through schema enforcement. Its main weakness is length — at 300+ lines with comprehensive inline content, it could benefit from splitting some reference material (migration tables, vector modeling, anti-patterns) into separate files. The conciseness is good but not exceptional, with some redundancy between sections.

Suggestions

Consider moving the Relational → Graph Migration Table and Vector/Embedding Modeling sections into referenced files to reduce the main document length and improve progressive disclosure.

Deduplicate guidance that appears in both the anti-patterns table and earlier sections (e.g., generic labels, supernode causes) by consolidating into one location and cross-referencing.

DimensionReasoningScore

Conciseness

The skill is comprehensive and mostly efficient, but some sections are slightly verbose — the anti-patterns table repeats guidance already covered in earlier sections (e.g., generic labels, supernode mitigation), and the `id` anti-pattern entry is overly hedged. The decision tables and naming conventions are lean and well-structured, but overall the document could be tightened by ~15-20% without losing information.

2 / 3

Actionability

Excellent actionability throughout: executable Cypher for schema inspection, constraint/index creation, supernode detection, and bucket patterns. Decision tables provide concrete 'if X then Y' guidance. The schema enforcement section is copy-paste ready with 8 distinct DDL examples covering all constraint/index types.

3 / 3

Workflow Clarity

Clear workflow: inspect schema first → define use cases → design model → create constraints/indexes → validate indexes are ONLINE. The 'Inspect Before Designing' section enforces a mandatory first step, the schema enforcement section includes a validation poll step, and the assessment output format provides a structured review workflow with severity-based action gates (ERROR = stop and fix).

3 / 3

Progressive Disclosure

References to external files (references/modeling-patterns.md, external Neo4j docs, GraphAcademy) are clearly listed in a 'References' section with 'load on demand' framing. However, no bundle files are provided, so the referenced `references/modeling-patterns.md` is unverifiable. The main document is quite long (~300+ lines) and some content like the full vector/embedding section or the relational migration table could arguably be split into reference files for better progressive disclosure.

2 / 3

Total

10

/

12

Passed

Validation

90%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Repository
neo4j-contrib/neo4j-skills
Reviewed

Table of Contents

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