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Knowledge Graph - Graph Constraint Generator

by Muhammad Asif · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install graph-constraint-generator
Description
Generate structural, semantic, and property constraints for knowledge graph schemas including RDF/OWL ontologies and property graph models.
README (SKILL.md)

Knowledge Graph Constraint Generator

Generate constraints for knowledge graph schemas to enforce data integrity.

This skill automatically creates structural, semantic, and property constraints suitable for RDF/OWL ontologies and Neo4j property graphs.

Quick Start

Use When

  • Designing constraints for graph schemas
  • Enforcing graph integrity rules
  • Generating SHACL validation rules
  • Creating Neo4j database constraints
  • Defining property requirements
  • Establishing data governance

Inputs

  • Graph schema definitions
  • Entity models
  • Relationship types
  • Property specifications
  • Cardinality requirements
  • Integrity rules

Outputs

  • Unique constraints
  • Required property constraints
  • Relationship constraints
  • Cardinality rules
  • SHACL shapes
  • Cypher constraint statements

Example

Input Schema:

Student: student_id (unique), name (required), email
Course: course_code (unique), title (required), credits
Relationship: (Student)-[:ENROLLED_IN]->(Course)

Generated Constraints:

Unique:
  Student.student_id UNIQUE
  Course.course_code UNIQUE

Required:
  Student.name (min 1)
  Course.title (min 1)

Relationships:
  (Student)-[:ENROLLED_IN]->(Course) [min 1]

Constraint Types

1. Unique Constraints

Ensure properties uniquely identify nodes

CREATE CONSTRAINT student_id_unique ON (s:Student) REQUIRE s.student_id IS UNIQUE

2. Required Property Constraints

Define mandatory properties

Student.name IS REQUIRED
Course.title IS REQUIRED

3. Relationship Constraints

Define allowed graph connections

(Student)-[:ENROLLED_IN]->(Course)
(Professor)-[:TEACHES]->(Course)

4. Cardinality Constraints

Define relationship occurrence limits

Student → ENROLLED_IN → Course (minimum: 1)
Professor → TEACHES → Course (maximum: 10)

5. Domain/Range Constraints (RDF/OWL)

Define semantic relationship constraints

:writes rdfs:domain :Researcher ;
        rdfs:range :Paper .

6. Data Type Constraints

Ensure property values match types

student_id: String
credits: Integer
gpa: Float

Execution Steps

  1. Analyze Schema – Extract entities, relationships, properties
  2. Identify Keys – Find unique identifiers
  3. Determine Required – Identify mandatory properties
  4. Analyze Relationships – Extract connection patterns
  5. Calculate Cardinality – Determine relationship bounds
  6. Generate Constraints – Create constraint definitions
  7. Format Output – Output as SHACL, Cypher, or RDF

Output Formats

Neo4j Cypher

CREATE CONSTRAINT student_id_unique ON (s:Student) REQUIRE s.student_id IS UNIQUE
CREATE INDEX ON (s:Student)(name)

SHACL Shapes

:StudentShape a sh:NodeShape ;
  sh:targetClass :Student ;
  sh:property [
    sh:path :student_id ;
    sh:minCount 1 ;
    sh:maxCount 1
  ] .

RDF/OWL

:writes rdfs:domain :Researcher ;
        rdfs:range :Paper ;
        rdf:type owl:ObjectProperty .

Recommended Libraries

  • RDF/OWL: rdflib, pyshacl, owlready2
  • Property Graph: neo4j, py2neo, networkx
  • Data Validation: pydantic, jsonschema

Best Practices

✓ Define unique identifiers early
✓ Avoid overly restrictive constraints
✓ Keep domain/range rules clear
✓ Validate data frequently
✓ Combine database and semantic constraints
✓ Document constraint reasoning
✓ Test constraints before production

References

See constraint-patterns.md for constraint design patterns and example-constraints.md for domain constraint examples.


Version: 1.0.0

Usage Guidance
This looks safe to install for generating graph schema constraints. Review generated Cypher or SHACL before applying it to a real database, because constraint and index statements can change database schema or affect existing data validation.
Capability Assessment
Purpose & Capability
The stated purpose is to generate Neo4j, SHACL, RDF/OWL, and related graph constraint examples; the documentation and Python helper match that purpose. Generated database DDL could affect a graph database if a user chooses to run it, but the skill itself only generates or displays those statements.
Instruction Scope
Runtime instructions are scoped to schema analysis and constraint generation. I found no prompt-injection text, role overrides, hidden directives, or instructions to access unrelated data.
Install Mechanism
The package contains markdown documentation and one Python script, with no declared dependencies, install hooks, package-manager commands, or startup behavior.
Credentials
The Python script uses only standard library dataclasses, enums, and typing, keeps data in memory, and prints output. Static review found no file writes, subprocess execution, network calls, credential access, or local profile/session use.
Persistence & Privilege
There is no persistence mechanism beyond normal skill files, no background worker, no privilege escalation, and no automatic mutation of user systems.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install graph-constraint-generator
  3. After installation, invoke the skill by name or use /graph-constraint-generator
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of Knowledge Graph Constraint Generator. - Generates structural, semantic, and property constraints for knowledge graph schemas (RDF/OWL and Neo4j property graphs). - Supports output as SHACL shapes, Cypher constraint statements, and RDF/OWL triples. - Provides quick start guide, example usage, and best practices for constraint definition. - Useful for enforcing data integrity and governance in knowledge graph modeling.
Metadata
Slug graph-constraint-generator
Version 1.0.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Knowledge Graph - Graph Constraint Generator?

Generate structural, semantic, and property constraints for knowledge graph schemas including RDF/OWL ontologies and property graph models. It is an AI Agent Skill for Claude Code / OpenClaw, with 39 downloads so far.

How do I install Knowledge Graph - Graph Constraint Generator?

Run "/install graph-constraint-generator" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Knowledge Graph - Graph Constraint Generator free?

Yes, Knowledge Graph - Graph Constraint Generator is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Knowledge Graph - Graph Constraint Generator support?

Knowledge Graph - Graph Constraint Generator is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Knowledge Graph - Graph Constraint Generator?

It is built and maintained by Muhammad Asif (@fisa712); the current version is v1.0.0.

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