fabio-ontology

name	fabio-ontology
description	Intent-scoped fabio skill for Fabric knowledge/graph and digital-twin modeling: ontology items (entity/relationship types and bindings), graph models, graph querysets, and Digital Twin Builder models/flows. Use to define/evolve ontologies, query graphs for agent grounding, and build operational digital twins. fabio can also export a tenant scan as OWL (context tenant --format owl) and import it. Triggers: "ontology", "fabric iq ontology", "knowledge graph", "graph model", "graph query", "entity type", "relationship type", "digital twin", "digital twin builder", "owl".
license	MIT

fabio-ontology — Ontology, Graph & Digital Twins — Fabric IQ ontologies, graph models, digital twin builder

Generated file — do not edit by hand. This intent-scoped sub-skill of the fabio skill is generated from fabio's command schema plus authored judgment. Regenerate with cargo test generate_subskills -- --ignored. For install, auth, output envelope, global flags, and agent-safety rules, see the root fabio skill.

Prefer runtime introspection. This index is a snapshot; the installed binary is always authoritative. Use fabio context agent --group <group> and fabio context describe <group> <command> for exact flags and output shapes.

When to use

• Creating/evolving an ontology item (entity types, relationship types, data bindings).
• Generating an ontology FROM a Power BI semantic model OR a lakehouse ('ontology generate') — client-side reproduction of the portal's 'Generate Ontology' (which has no REST API): with --semantic-model it reads the model's tables/columns/relationships; with --lakehouse (no --semantic-model) it reads the lakehouse SQL endpoint's INFORMATION_SCHEMA. Either way it synthesizes entity types + typed properties + (relationships, model source only) + keys + lakehouse bindings.
• Binding an entity to one or MULTIPLE data sources — Lakehouse Delta (--lakehouse) and/or Eventhouse KustoTable — with generated entity Documents + ResourceLinks and entity-type inheritance carried from the imported schema.
• Managing graph models and running graph querysets.
• Modeling IoT/operational digital twins (Digital Twin Builder models and flows).
• Grounding an agent in a knowledge graph over Fabric data.
• Exposing an ontology to external AI systems as an MCP server ('ontology mcp-url').
• Querying an ontology's data in natural language ('ontology search') — fabio consumes the ontology MCP server's search_ontology tool as an MCP client.
• Importing an OWL schema (e.g. one produced by 'fabio context tenant --format owl').

When NOT to use (route elsewhere)

• Relational T-SQL modeling -> use fabio-warehouse-sql.
• The Delta/lakehouse data the ontology binds to -> use fabio-lakehouse.
• Semantic (tabular) models for BI -> use fabio-bi.

Command index

Generated from fabio's command schema. For full flag details use fabio context agent --group <group> or fabio context describe <group> <command>.

fabio ontology

Manage ontologies (entity types, data bindings)

Command	Mutates	Description
fabio ontology bind	yes	Bind an existing ontology's types to data sources (no OWL re-import)
fabio ontology create	yes	Create an ontology
fabio ontology delete	yes	Delete an ontology
fabio ontology export	no	Export a Fabric Ontology to OWL format (RDF/XML or JSON-LD)
fabio ontology generate	yes	Generate an ontology from a semantic model or lakehouse (entity types, properties, relationships)
fabio ontology get-definition	no	Get the ontology definition (entity types, bindings)
fabio ontology import	yes	Import an OWL ontology (RDF/XML or JSON-LD) and convert to Fabric format
fabio ontology list	no	List ontologies in a workspace
fabio ontology list-entity-types	no	List the ontology's entity types and their properties (schema exploration)
fabio ontology mcp-url	no	Print the Model Context Protocol (MCP) server URL for consuming this ontology
fabio ontology search	no	Ask a natural-language question over the ontology's data (MCP search_ontology tool)
fabio ontology show	no	Show details of an ontology
fabio ontology update	yes	Update ontology properties (name and/or description)
fabio ontology update-definition	yes	Update the ontology definition (replaces current definition)

fabio graph-model

Manage graph models (knowledge graph)

Command	Mutates	Description
fabio graph-model create	yes	Create a new graph model
fabio graph-model delete	yes	Delete a graph model
fabio graph-model execute-query	no	Execute a graph query
fabio graph-model get-definition	no	Get the definition of a graph model
fabio graph-model get-queryable-graph-type	no	Get the queryable graph type
fabio graph-model initialize	yes	Initialize a graph model for querying (portal-only operation)
fabio graph-model list	no	List graph models in a workspace
fabio graph-model refresh-graph	yes	Trigger a graph refresh job
fabio graph-model show	no	Show details of a graph model
fabio graph-model update	yes	Update graph model properties (name and/or description)
fabio graph-model update-definition	yes	Update the definition of a graph model

fabio graph-query-set

Manage graph query sets

Command	Mutates	Description
fabio graph-query-set create	yes	Create a new graph query set
fabio graph-query-set delete	yes	Delete a graph query set
fabio graph-query-set get-definition	no	Get the definition of a graph query set
fabio graph-query-set list	no	List graph query sets in a workspace
fabio graph-query-set show	no	Show details of a graph query set
fabio graph-query-set update	yes	Update graph query set properties
fabio graph-query-set update-definition	yes	Update the definition of a graph query set

fabio digital-twin-builder

Manage Digital Twin Builder models

Command	Mutates	Description
fabio digital-twin-builder create	yes	Create a new Digital Twin Builder
fabio digital-twin-builder delete	yes	Delete a Digital Twin Builder
fabio digital-twin-builder get-definition	no	Get the definition of a Digital Twin Builder
fabio digital-twin-builder list	no	List Digital Twin Builders in a workspace
fabio digital-twin-builder show	no	Show details of a Digital Twin Builder
fabio digital-twin-builder update	yes	Update Digital Twin Builder properties
fabio digital-twin-builder update-definition	yes	Update the definition of a Digital Twin Builder

fabio digital-twin-builder-flow

Manage Digital Twin Builder flows

Command	Mutates	Description
fabio digital-twin-builder-flow create	yes	Create a new Digital Twin Builder flow
fabio digital-twin-builder-flow delete	yes	Delete a Digital Twin Builder flow
fabio digital-twin-builder-flow get-definition	no	Get the definition of a Digital Twin Builder flow
fabio digital-twin-builder-flow list	no	List Digital Twin Builder flows in a workspace
fabio digital-twin-builder-flow show	no	Show details of a Digital Twin Builder flow
fabio digital-twin-builder-flow update	yes	Update Digital Twin Builder flow properties
fabio digital-twin-builder-flow update-definition	yes	Update the definition of a Digital Twin Builder flow

Must / Prefer / Avoid

MUST

• Define entity/relationship types before adding data bindings.
• Use the item-definition format for ontology create/update (see 'fabio context schema ontology').

PREFER

• ontology generate --semantic-model --lakehouse to bootstrap an ontology from an existing semantic model (entity types + properties + relationships + bindings in one shot), OR ontology generate --lakehouse (no --semantic-model) to bootstrap directly from lakehouse tables (entity types + typed properties + first-column-key heuristic + bindings; no relationships); inspect the synthesized OWL first with --output-owl.
• context tenant --format owl to bootstrap an ontology schema from a real workspace scan, then ontology import.
• ontology list-entity-types to explore an ontology's schema (entity types, properties, timeseries/untyped, inheritance) WITHOUT parsing the raw definition — byte-for-byte the same answer as the ontology MCP server's list_ontology_entity_types tool (minus the server-only etag), computed offline from getDefinition.
• ontology import --lakehouse --bindings <map.json> to generate DataBindings + relationship Contextualizations in the same step, so the imported ontology is queryable rather than a bare schema.
• ontology bind --lakehouse --bindings <map.json> to add/update data bindings on an EXISTING ontology (e.g. portal-authored) without re-importing OWL; types are matched by name.
• Runtime introspection (context agent --group ontology|graph-model) for exact flags.

AVOID

• Binding to data sources that do not yet exist — create the underlying items first.
• Confusing an ontology (knowledge graph schema) with a semantic model (BI tabular model).

Key gotchas

• Ontology definitions use the item-definition (base64 parts) format; fetch the template with 'fabio context schema ontology'.
• fabio's context tenant graph can emit OWL/RDF that imports directly via 'fabio ontology import --file'.
• OWL carries no data-binding info (workspace/lakehouse/table/column). 'ontology import' generates only the type schema unless you pass a source: --lakehouse (Delta) or Eventhouse/KustoTable source flags (+ --bindings for relationship key columns). An entity can carry MULTIPLE data bindings, and import also emits entity Documents + ResourceLinks and preserves entity-type inheritance.
• Untyped properties (valueType Any) are NOT bindable — they live only under entityType.untypedProperties. Putting one in a DataBinding makes updateDefinition fail with a generic ALMOperationImportFailed. fabio import excludes them automatically; hand-authored parts must too.
• Time-series entities need a timestampColumn on their TimeSeries binding. Convention bind-all (import/bind with no per-entity timestamp) errors: 'Entity X has a TimeSeries binding but no timestampColumn'. Supply it via the --entities/bind config or use non-time-series entities.
• updateDefinition validates all parts together; a bad reference in ANY part fails the whole push. The generic ALMOperationImportFailed's real cause is in error.errorCode + error.moreDetails (fabio surfaces both and adds a self-correction checklist).
• Fabric does NOT check that a bound Lakehouse table/column exists at updateDefinition time (deferred to query time) — a missing table imports fine and is never the cause of an import failure.
• Ontology needs a capacity with the Ontology/Digital Twin Builder preview enabled; each create/import/getDefinition is an LRO taking ~60-100s.
• An ontology can be consumed as an MCP server by external agents. 'fabio ontology mcp-url --workspace --id ' prints the canonical endpoint ({fabricBase}/mcp/dataPlane/workspaces/{ws}/items/{id}/ontologyEndpoint) — a deterministic URL agents cannot guess. Distinct from grounding a fabio data-agent on the ontology; this exposes the ontology itself over MCP (HTTP transport, Fabric auth) to VS Code agent mode/Claude/Copilot Studio. Requires F2+/P1 capacity and the Ontology-item preview tenant setting.
• The ontology MCP server exposes two tools: list_ontology_entity_types (schema) and search_ontology (natural-language query over the ontology data estate). Both now have pure-fabio equivalents: 'fabio ontology list-entity-types' reproduces the first EXACTLY (offline, byte-for-byte), and 'fabio ontology search --prompt "..."' drives the second by consuming the ontology MCP server as an MCP CLIENT (fabio's first MCP-client feature). search returns raw JSON results + an optional derived NL answer; a successful answer needs the ontology bound to data AND server-side Fabric IQ NL reasoning provisioned on the capacity.

Troubleshooting

Symptom	Fix
ALMOperationImportFailed / generic 'import failed' on import/bind/update-definition	The top-level message is often an unfilled '{0} {1} {2}' template — read error.errorCode + error.moreDetails (fabio flattens these into the message + hint). Check in order: (1) no untyped property is bound, (2) every entityTypeId/propertyId/relationshipTypeId referenced by a binding or contextualization is defined in the same push and case-matches, (3) TimeSeries bindings have a timestampColumn, (4) contextualization source/target entity ids match the relationship endpoints. A missing Lakehouse table is NOT a cause.
'Entity X has a TimeSeries binding but no timestampColumn'	Provide a timestampColumn for that entity (import --entities map / bind config), or model it as a non-time-series entity.
Ontology import rejected before push	Validate the OWL/JSON-LD against the ontology schema (context schema ontology); ensure entity types precede bindings.
Ontology query returns no data although import succeeded	updateDefinition does not validate table/column existence — verify the bound Lakehouse table and columns actually exist and the binding names match (import success != queryable).

Safety

• Overwriting an ontology definition replaces its type system and bindings — confirm with the user.

Shared references

Cross-cutting operational guidance (the "common" layer) — consult the relevant topic before non-trivial work:

Reference	Covers
fabio context best-practices throttling	fabio transparently handles 429 (Too Many Requests) and gateway errors. Agents do NOT need to implement retry logic.
fabio context best-practices pagination	fabio handles pagination via --all (auto-fetch all pages), --continuation-token (resume), and --limit (truncate). Agents rarely need to paginate manually.
fabio context best-practices lro	Many Fabric operations are async (return 202). fabio polls them automatically. Use --wait for job operations.

See also

• fabio context schema ontology
• fabio context workflow ontology_tutorial
• fabio context persona data-engineer
• fabio ontology mcp-url --workspace --id (consume the ontology as an MCP server)
• fabio data-agent add-datasource --artifact-type Ontology (ground an agent on the ontology; scope with select-tables --elements)