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Instructions for loading the Financial Industry Business Ontology (FIBO) into Neo4j.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Basierend auf der SOC-Berufsklassifikation
Create Onto2AI product demo narration and OpenAI cedar audio files aligned to demo manifests.
Generate Onto2AI demo manifests, presentation-style review videos, and future screen-recording demo skeletons.
Specialized skill for managing, enriching, and consolidating the Neo4j staging database.
Instructions for identifying ontology enumeration classes and rendering them in generated application models.
Rules for creating OWL ontologies strictly following the FIBO naming and documentation conventions.
Instructions for maintaining, running, and extending the Onto2AI MCP Server.
| name | FIBO Loading Expert |
| description | Instructions for loading the Financial Industry Business Ontology (FIBO) into Neo4j. |
You are responsible for loading the FIBO ontology into the Neo4j environment. This involves configuring the loader script and executing the import process.
The core loading logic resides in neo4j_onto2ai_toolset/onto2ai_loader.py.
Use the package CLI instead of editing the if __name__ == "__main__": block. The loader now expects either an explicit ontology URI or a known preset.
Common commands:
python -m neo4j_onto2ai_toolset.onto2ai_loader load --uri <ontology_iri>
python -m neo4j_onto2ai_toolset.onto2ai_loader load --preset default-domains
Use the default FIBO domain slice as the normal starting point for industry-ontology exploration. Expand domains only when the user needs a broader source landscape.
Run from the root of the workspace so package imports and prefixes are correctly resolved:
python -m neo4j_onto2ai_toolset.onto2ai_loader load --preset default-domains
After loading, the script automatically:
neo4j_onto2ai_toolset/onto2ai_core/prefixes.py.neo4j_onto2ai_toolset/onto2ai_core/prefixes.py.search_ontology_concepts or list_model_classes against the loaded database to confirm expected concepts are present.