Template Query Generator

Generate reusable graph query templates for common graph database operations.

This skill produces parameterized query templates that developers can quickly adapt to query graph databases without writing queries from scratch.

It supports template generation for common tasks such as:

• node lookup
• relationship traversal
• path discovery
• aggregations
• filtering
• graph exploration

Templates can be generated for graph query languages such as Cypher and SPARQL.

📋 Quick Start

When To Use This Skill

Use this skill when a user wants to:

• generate common graph queries
• create reusable query templates
• quickly scaffold Cypher or SPARQL queries
• explore graph data structures
• build starter queries for applications
• standardize query patterns
• document query patterns

Example Requests

• "Generate a query template for finding relationships."
• "Create a Cypher template to search nodes by property."
• "Generate a SPARQL query template for retrieving entities."
• "Create a reusable graph query."
• "Give me a template for path discovery."
• "Generate aggregation templates."

🎯 What This Skill Produces

The skill generates parameterized templates for:

• Node Queries - Finding nodes by label and properties
• Relationship Queries - Traversing relationships between nodes
• Path Queries - Discovering paths through the graph
• Aggregation Queries - Computing statistics and summaries
• Filtering Queries - Filtering nodes by conditions
• Graph Exploration - Discovering graph structure
• Multi-Hop Queries - Complex traversals across multiple hops
• Comparison Queries - Comparing entities and relationships

Templates typically include query parameters to allow easy reuse.

🔍 Template Categories

1. Node Lookup Templates (Basic)

Cypher template:

MATCH (n:$label {$property: $value})
RETURN n
LIMIT $limit

Example:

MATCH (p:Person {email: $email})
RETURN p

Parameters:

• label: Node label (e.g., Person, Company)
• property: Property name (e.g., email, id)
• value: Property value
• limit: Result limit (default: 10)

2. Relationship Traversal Templates

Cypher template:

MATCH (a:$sourceLabel)-[:$relationshipType]->(b:$targetLabel)
RETURN a, b
LIMIT $limit

Example:

MATCH (p:Person)-[:WORKS_AT]->(c:Company)
RETURN p, c

Parameters:

• sourceLabel: Starting node label
• relationshipType: Relationship type
• targetLabel: Target node label
• limit: Result limit

3. Multi-Hop Path Templates

Cypher template:

MATCH path = (start:$startLabel)-[*1..$depth]-(end:$endLabel)
RETURN path
LIMIT $limit

Example:

MATCH path = (p:Person)-[*1..3]-(target)
RETURN path
LIMIT 50

Parameters:

• startLabel: Starting node label
• endLabel: Ending node label
• depth: Maximum traversal depth
• limit: Result limit

4. Aggregation Templates

Cypher template:

MATCH (source:$sourceLabel)-[:$relationshipType]->(target:$targetLabel)
RETURN target.$property, COUNT(DISTINCT source) as count
GROUP BY target.$property
ORDER BY count DESC
LIMIT $limit

Example:

MATCH (p:Person)-[:WORKS_AT]->(c:Company)
RETURN c.name, COUNT(DISTINCT p) as employee_count
GROUP BY c.name
ORDER BY employee_count DESC
LIMIT 10

5. Filtering Templates

Cypher template:

MATCH (n:$label)
WHERE n.$property $operator $value
RETURN n
LIMIT $limit

Example:

MATCH (p:Person)
WHERE p.age > 30
RETURN p
LIMIT 100

Parameters:

• label: Node label
• property: Property to filter
• operator: Comparison operator (>, \x3C, =, !=)
• value: Filter value
• limit: Result limit

6. Property Filtering Templates

Cypher template:

MATCH (n:$label)
WHERE n.$property CONTAINS $value
RETURN n
LIMIT $limit

Example:

MATCH (p:Product)
WHERE p.description CONTAINS $search_term
RETURN p
LIMIT 20

7. Conditional Aggregation Templates

Cypher template:

MATCH (source:$sourceLabel)-[:$relationshipType]->(target:$targetLabel)
WHERE target.$filterProperty $operator $filterValue
RETURN target.$groupProperty, COUNT(source) as count
GROUP BY target.$groupProperty
ORDER BY count DESC
LIMIT $limit

8. Relationship Count Templates

Cypher template:

MATCH (n:$label)-[r:$relationshipType]->()
RETURN n, COUNT(r) as relationship_count
ORDER BY relationship_count DESC
LIMIT $limit

Example:

MATCH (p:Person)-[r:FOLLOWS]->()
RETURN p, COUNT(r) as follower_count
ORDER BY follower_count DESC
LIMIT 10

🔗 SPARQL Template Examples

SPARQL Node Lookup

PREFIX ex: \x3Chttp://example.org/>
SELECT ?entity
WHERE {
  ?entity a ex:$class ;
          ex:$property $value .
}
LIMIT $limit

SPARQL Relationship Query

PREFIX ex: \x3Chttp://example.org/>
SELECT ?subject ?object
WHERE {
  ?subject ex:$predicate ?object .
}
LIMIT $limit

SPARQL Triple Pattern

PREFIX ex: \x3Chttp://example.org/>
SELECT ?resource
WHERE {
  ?resource a ex:$class .
  ?resource ex:$property ?value .
}
LIMIT $limit

💡 Template Generation Workflow

When generating query templates:

Step 1: Identify Query Goal

• Node lookup
• Relationship discovery
• Path exploration
• Aggregation
• Filtering

Step 2: Select Graph Pattern

• Choose appropriate pattern for goal
• Determine node labels/relationship types
• Identify parameterization points

Step 3: Insert Parameters

• Mark values as $parameter
• Choose meaningful parameter names
• Document parameter types

Step 4: Generate Target Syntax

• Cypher or SPARQL
• Validate syntax
• Include query explanation

Step 5: Create Usage Example

• Show concrete instantiation
• Document parameter values
• Provide integration guidance

📋 Output Formats

The skill returns:

1. Query Template

Parameterized Cypher or SPARQL query ready for reuse.

2. Parameter List

{
  "label": "string - Node label",
  "property": "string - Property name",
  "value": "any - Property value",
  "limit": "integer - Result limit (default: 10)"
}

3. Query Explanation

Plain English description of query purpose and behavior.

4. Usage Example

Concrete instantiation with sample parameter values.

5. Performance Notes

Index recommendations and optimization suggestions.

📈 Template Performance Guidelines

Node Lookup Templates

• Performance: O(1) with index on label + property
• Index Recommendation: Create index on queried property
• Typical Execution: \x3C 10 ms
• Best For: Single entity retrieval

Relationship Templates

• Performance: O(n) where n = source cardinality
• Index Recommendation: Index relationship type
• Typical Execution: 10-100 ms
• Best For: Specific relationship queries

Path Templates

• Performance: O(n^depth) exponential in depth
• Index Recommendation: Bound depth to ≤ 3
• Typical Execution: 100-1000 ms
• Best For: Discovery with bounded depth

Aggregation Templates

• Performance: O(n log n) with grouping
• Index Recommendation: Index group property
• Typical Execution: 50-500 ms
• Best For: Statistical summaries

✅ Best Practices

When designing query templates:

1. Use Clear Parameter Names

   • $email instead of $e
   • $depth instead of $d
   • $company_name instead of $c_n

2. Include Result Limits

   • Always add LIMIT $limit clause
   • Default limit to 10 or 50
   • Prevents memory issues

3. Avoid Unbounded Traversal

   • Use [*1..3] instead of [*]
   • Bound path depth to 3-5 hops
   • Document depth restrictions

4. Design for Reusability

   • Make templates work across datasets
   • Parameterize all variable values
   • Use standard naming conventions

5. Include Documentation

   • Parameter descriptions
   • Example values
   • Performance characteristics

6. Index Awareness

   • Recommend indexes for filtered properties
   • Consider composite indexes
   • Document index creation

7. Error Handling

   • Validate parameter types
   • Handle null values
   • Provide default behaviors

8. Template Versioning

   • Track template versions
   • Support template evolution
   • Document changes

🔗 Integration with Other Skills

This skill integrates with:

• graph-query-debugging-tool - Debug generated templates
• graph-query-optimization-assistant - Optimize templates further
• nl-to-graph-query-translator - Translate natural language to templates
• graph-schema-validation - Validate templates against schema
• multi-hop-reasoning-query-builder - Build complex path templates

📚 Template Usage Scenarios

Scenario 1: Web Application

Goal: Find user by email
Generated: SELECT ?user WHERE { ?user foaf:email $email }
Usage: Execute in REST API endpoint

Scenario 2: Analytics Dashboard

Goal: Aggregate employee counts by company
Generated: Match relationships, group by company, count
Usage: Update dashboard monthly

Scenario 3: Mobile App

Goal: Get person's network (friends and followers)
Generated: Multi-hop path template with depth limit
Usage: Paginated results in app

Scenario 4: Data Export

Goal: Export all entities of type with properties
Generated: Complete node projection template
Usage: Scheduled export job

📖 Summary

This skill generates reusable graph query templates for common database operations.

It helps developers quickly scaffold Cypher or SPARQL queries, improving productivity and reducing query-writing effort through standardized, production-ready templates.

Status: Enterprise-Grade Template Generation

Comprehensive template library and generation system for professional knowledge graph development.