Automatically creates structural, semantic, and property constraints to enforce data integrity for RDF/OWL ontologies and property graph models.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install graph-constraint-generator
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install graph-constraint-generator using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Knowledge Graph Constraint Generator?
The Knowledge Graph Constraint Generator is a powerful tool designed to automate the creation of database validation rules and structural boundaries for complex graph data models. By parsing graph schema definitions, entity models, and relationship topologies, it produces precise restrictions that prevent data corruption and ensure compliance with strict data governance rules.
Integrating this tool via Openclaw Skills empowers developers to bridge the gap between high-level ontology design and practical database enforcement. It seamlessly handles both relational-semantic constraints for semantic web stacks and schema-optional or schema-mandatory configurations for modern property graphs, transforming plain descriptions into operational code.
Knowledge Graph Constraint Generator Use Cases
- Designing constraints for graph schemas to prevent structural erosion over time.
- Enforcing graph integrity rules programmatically across continuous integration pipelines.
- Generating SHACL validation rules for W3C-compliant RDF datasets and semantic web applications.
- Creating Neo4j database constraints using Cypher syntax directly from entity property mappings.
- Defining property requirements and data types to prevent structural drift.
- Establishing data governance frameworks by standardizing how domains and ranges interact.
How Knowledge Graph Constraint Generator Works
- Analyze Schema: Extracts core entities, complex relationships, and metadata properties from the provided input architecture.
- Identify Keys: Locates primary and secondary unique identifiers across the node labels.
- Determine Required: Evaluates mandatory property flags that must be present on every instance.
- Analyze Relationships: Scans edge distributions to extract connection patterns and valid direction paths.
- Calculate Cardinality: Determines lower and upper bounds for relationship occurrences.
- Generate Constraints: Translates compiled data into structural constraint declarations.
- Format Output: Serializes the definitions into destination syntaxes like SHACL, Cypher, or raw RDF/OWL.
Knowledge Graph Constraint Generator Setup
To deploy and configure this module within Openclaw Skills, prepare your pipeline environments by installing the recommended modeling dependencies:
# Install semantic web and SHACL verification tools
pip install rdflib pyshacl owlready2
# Install property graph drivers and structural networks libraries
pip install neo4j py2neo networkx
# Install validation utilities
pip install pydantic jsonschema
Knowledge Graph Constraint Generator Data Schema & Taxonomy
The component processes arbitrary text schemas and converts them into structured graph validation manifests. The generated schema metadata covers several core categories:
| Constraint Class | Purpose | Core Strategy |
|---|---|---|
| Unique Constraints | Ensures unique identifiers for nodes | Cypher IS UNIQUE commands |
| Required Property | Forces property presence | Presence validation statements |
| Relationship Bounds | Sets allowable node connections | Source-Edge-Target mapping matrices |
| Cardinality Controls | Governs minimum and maximum limits | Cardinality boundary bounds (minCount/maxCount) |
| Domain/Range | Sets semantic properties | rdfs:domain and rdfs:range Turtle predicates |
| Data Type Profiles | Standardizes variable types | Strict typing matching (String, Integer, Float) |
Knowledge Graph Constraint Generator Advanced Features
- Multi-Format Target Output: Emits production-ready Neo4j Cypher scripts, W3C SHACL Shapes, or raw RDF/OWL Turtle mappings out of the box.
- Semantic Web Compatibility: Supports
rdfs:domainandrdfs:rangeenforcement for advanced reasoning contexts. - Flexible Extensibility Hooks: Built for pairing database-level index rules with semantic-level validation rules for deep hybrid data governance workflows.
SKILL.md
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