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neo4j-kafka-skill

Configure and operate the Neo4j Connector for Kafka (sink + source) and the native Neo4j CDC API. Covers Cypher/Pattern/CUD sink strategies, CDC-based and query-based source, exactly-once semantics, DLQ error handling, Confluent Cloud managed connector, schema registry (Avro/JSON), and native db.cdc.query cursor-loop patterns (Neo4j 5.13+ Enterprise/Aura BC/VDC). Use when streaming Kafka events into Neo4j, streaming Neo4j changes to Kafka, or querying Neo4j change events without Kafka. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle bulk CSV/file import — use neo4j-import-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.

72

Quality

88%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

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 concrete examples covering multiple connector strategies, native CDC API, and operational concerns like EOS and DLQ. The workflow clarity is good with explicit sequencing and a comprehensive checklist. The main weakness is that the SKILL.md tries to be both an overview and a detailed reference, inlining content (event structure, selector tables) that should live in the referenced files, making it longer than necessary for a top-level skill file.

Suggestions

Move the detailed Event Structure, Selector Reference table, and Schema Registry converter configs to the referenced files (references/cdc-api.md and references/sink-config.md) and keep only brief summaries with links in SKILL.md.

Ensure the referenced bundle files (references/sink-config.md, references/cdc-api.md) actually exist to support the progressive disclosure structure.

DimensionReasoningScore

Conciseness

The skill is generally efficient and avoids explaining basic concepts, but it's quite long (~350 lines). Some sections like the full event structure and the selector reference table could be offloaded to reference files. The decision table and checklist add value, but the overall length pushes it toward verbose for a SKILL.md overview.

2 / 3

Actionability

Excellent actionability throughout — every strategy has complete, copy-paste-ready JSON configs and executable Cypher/Python code. The cursor-loop Python pattern, EOS setup steps, and DLQ config are all fully concrete and immediately usable.

3 / 3

Workflow Clarity

Multi-step processes are clearly sequenced with explicit validation checkpoints. The EOS setup has numbered steps (create constraint first, then configure), the checklist provides a verification loop, and the common errors table serves as a troubleshooting feedback mechanism. The cursor-loop pattern includes proper cursor advancement logic.

3 / 3

Progressive Disclosure

References to supporting files (references/sink-config.md, references/cdc-api.md) are present and well-signaled, but no bundle files were provided, suggesting these references may be broken. More importantly, substantial reference material (event structure, full selector reference table, schema registry details) is inlined in the SKILL.md rather than being offloaded to the referenced files, making the main file heavier than ideal.

2 / 3

Total

10

/

12

Passed

Description

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 excellent skill description that thoroughly covers specific capabilities, includes natural trigger terms, explicitly states both what and when, and proactively prevents conflicts with related skills through negative boundary clauses. The description is information-dense without being padded, and uses proper third-person voice throughout. The inclusion of version requirements (Neo4j 5.13+ Enterprise/Aura BC/VDC) adds further precision.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions and strategies: Cypher/Pattern/CUD sink strategies, CDC-based and query-based source, exactly-once semantics, DLQ error handling, Confluent Cloud managed connector, schema registry (Avro/JSON), and native db.cdc.query cursor-loop patterns with version specifics.

3 / 3

Completeness

Clearly answers both 'what' (configure and operate Neo4j Connector for Kafka with detailed strategies and features) and 'when' (explicit 'Use when streaming Kafka events into Neo4j, streaming Neo4j changes to Kafka, or querying Neo4j change events without Kafka'). Also includes explicit negative boundaries with skill routing guidance.

3 / 3

Trigger Term Quality

Excellent coverage of natural terms users would say: 'Kafka', 'Neo4j', 'CDC', 'streaming', 'sink', 'source', 'Confluent Cloud', 'Avro', 'JSON', 'schema registry', 'DLQ', 'change events'. These are the exact terms a user working in this domain would use.

3 / 3

Distinctiveness Conflict Risk

Extremely distinctive with a clear niche (Neo4j-Kafka integration and CDC). The explicit 'Does NOT handle' clauses with skill routing to neo4j-cypher-skill, neo4j-import-skill, and neo4j-gds-skill actively prevent conflicts with related skills.

3 / 3

Total

12

/

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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