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    tomasonjo

    neo4j-cypher-guide

    tomasonjo/neo4j-cypher-guide
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    SKILL.md

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    About

    Comprehensive guide for writing modern Neo4j Cypher read queries. Essential for text2cypher MCP tools and LLMs generating Cypher queries...

    SKILL.md

    Neo4j Modern Cypher Query Guide

    This skill helps generate Neo4j Cypher read queries using modern syntax patterns and avoiding deprecated features. It focuses on efficient query patterns for graph traversal and data retrieval.

    Quick Compatibility Check

    When generating Cypher queries, immediately avoid these REMOVED features:

    • ❌ id() function → Use elementId()
    • ❌ Implicit grouping keys → Use explicit WITH clauses
    • ❌ Pattern expressions for lists → Use pattern comprehension or COLLECT subqueries
    • ❌ Repeated relationship variables → Use unique variable names
    • ❌ Automatic list to boolean coercion → Use explicit checks

    Core Principles for Query Generation

    1. Use modern syntax patterns - QPP for complex traversals, CALL subqueries for complex reads
    2. Optimize during traversal - Filter early within patterns, not after expansion
    3. Always filter nulls when sorting - Add IS NOT NULL checks for sorted properties
    4. Explicit is better than implicit - Always use explicit grouping and type checking

    Critical Sorting Rule

    ALWAYS filter NULL values when sorting:

    // WRONG - May include null values
    MATCH (n:Node)
    RETURN n.name, n.value
    ORDER BY n.value
    
    // CORRECT - Filter nulls before sorting
    MATCH (n:Node)
    WHERE n.value IS NOT NULL
    RETURN n.name, n.value
    ORDER BY n.value
    

    Query Pattern Selection Guide

    For Simple Queries

    Use standard Cypher patterns with modern syntax:

    MATCH (n:Label {property: value})
    WHERE n.otherProperty IS :: STRING
    RETURN n
    

    For Variable-Length Paths

    Consider Quantified Path Patterns (QPP) for better performance:

    // Instead of: MATCH (a)-[*1..5]->(b)
    // Use: MATCH (a)-[]-{1,5}(b)
    
    // With filtering:
    MATCH (a)((n WHERE n.active)-[]->(m)){1,5}(b)
    

    For Aggregations

    Use COUNT{}, EXISTS{}, and COLLECT{} subqueries:

    MATCH (p:Person)
    WHERE count{(p)-[:KNOWS]->()} > 5
    RETURN p.name, 
           exists{(p)-[:MANAGES]->()} AS isManager
    

    For Complex Read Operations

    Use CALL subqueries for sophisticated data retrieval:

    MATCH (d:Department)
    CALL (d) {
      MATCH (d)<-[:WORKS_IN]-(p:Person)
      WHERE p.salary IS NOT NULL  // Filter nulls
      WITH p ORDER BY p.salary DESC
      LIMIT 3
      RETURN collect(p.name) AS topEarners
    }
    RETURN d.name, topEarners
    

    Common Query Transformations

    Counting Patterns

    // Old: RETURN size((n)-[]->())
    // Modern: RETURN count{(n)-[]->()}
    

    Checking Existence

    // Old: WHERE exists((n)-[:REL]->())
    // Modern: WHERE EXISTS {MATCH (n)-[:REL]->()}
    // Also valid: WHERE exists{(n)-[:REL]->()}
    

    Element IDs

    // Old: WHERE id(n) = 123
    // Modern: WHERE elementId(n) = "4:abc123:456"
    // Note: elementId returns a string, not integer
    

    Sorting with Null Handling

    // Always add null check
    MATCH (n:Node)
    WHERE n.sortProperty IS NOT NULL
    RETURN n
    ORDER BY n.sortProperty
    
    // Or use NULLS LAST
    MATCH (n:Node)
    RETURN n
    ORDER BY n.sortProperty NULLS LAST
    

    When to Load Reference Documentation

    Load the appropriate reference file when:

    references/deprecated-syntax.md

    • Migrating queries from older Neo4j versions
    • Encountering syntax errors with legacy queries
    • Need complete list of removed/deprecated features

    references/subqueries.md

    • Working with CALL subqueries for reads
    • Using COLLECT or COUNT subqueries
    • Handling complex aggregations
    • Implementing sorting with null filtering

    references/qpp.md

    • Optimizing variable-length path queries
    • Need early filtering during traversal
    • Working with paths longer than 3-4 hops
    • Complex pattern matching requirements

    Query Generation Checklist

    Before finalizing any generated query:

    1. ✅ No deprecated functions (id, btree indexes, etc.)
    2. ✅ Explicit grouping for aggregations
    3. ✅ NULL filters for all sorted properties
    4. ✅ Appropriate subquery patterns for reads
    5. ✅ Consider QPP for paths with filtering needs
    6. ✅ Use COUNT{} instead of size() for pattern counting
    7. ✅ Variable scope clauses in CALL subqueries
    8. ✅ Unique variable names for relationships

    Error Resolution Patterns

    "Implicit grouping key" errors

    // Problem: RETURN n.prop, count(*) + n.other
    // Solution: WITH n.prop AS prop, n.other AS other, count(*) AS cnt
    //          RETURN prop, cnt + other
    

    "id() function not found"

    // Use elementId() but note it returns a string, not integer
    

    "Repeated variable" errors

    // Problem: MATCH (a)-[r*]->(), (b)-[r*]->()
    // Solution: MATCH (a)-[r1*]->(), (b)-[r2*]->()
    

    Performance Tips

    1. Start with indexed properties - Always anchor patterns with indexed lookups
    2. Filter early in QPP - Apply WHERE clauses within the pattern
    3. Filter nulls before sorting - Prevent unexpected results and improve performance
    4. Limit expansion depth - Use reasonable upper bounds in quantifiers
    5. Use EXISTS for existence checks - More efficient than counting
    6. Profile queries - Use PROFILE to identify bottlenecks

    Modern Cypher Features

    Label Expressions

    WHERE n:Label1|Label2  // OR
    WHERE n:Label1&Label2  // AND
    WHERE n:!Archived      // NOT
    

    Type Predicates

    WHERE n.prop IS :: STRING
    WHERE n.value IS :: INTEGER NOT NULL
    WHERE n.data IS :: LIST<STRING>
    

    Subquery Patterns for Reads

    • COUNT{} - Count patterns efficiently
    • EXISTS{} - Check pattern existence
    • COLLECT{} - Collect complex results
    • CALL{} - Execute subqueries for complex reads

    Quantified Path Patterns

    • Inline filtering during traversal
    • Access to nodes and relationships in patterns
    • Significant performance improvements (up to 1000x)
    • Support for complex, multi-hop patterns

    Always prefer modern syntax patterns for better performance and maintainability.

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    tomasonjo/blogs
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