Nvidia Ontology Management

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Auto Ontology management and modeling

Purpose

Inspect and change Auto Ontology's semantic layer without confusing a successful API call with correct business meaning or durable publication. The machine-readable inputs, outputs, statuses, gates, and handoffs are in runtime-contract.yaml.

Choose the focused workflow before acting:

• routine inspection or metadata edits: continue below and use write-api.md;

• concepts, relationships, measures, units, grain, or policies: use modeling.md;

• model promotion or reusable analytical results: use publication.md.

MCP tools only read. Create, patch, import, and compile-reset go through the Next.js /api/... gateway. Governed result rows require an approved source writer; Auto Ontology has no generic result-row writeback endpoint. Request bodies and field types live in docs/openapi/auto-ontology-api.json; this skill names operations and permissions only.

Prerequisites

Use a running, authenticated Auto Ontology deployment. Use nvidia-ontology-setup when the deployment or semantic layer is not ready.

Limitations

MCP is read-only, Auto Ontology has no generic result-row writeback endpoint, and current model import and certification APIs do not prove atomic promotion. Follow the publication gates below and fail closed when exact readback is unavailable.

Auth

Scripts use an API token (x-api-key or Authorization: Bearer). Mint it in the UI (user menu → API Tokens). A token acts as its owner — a viewer's token cannot do admin things. Creating and revoking tokens requires a signed-in session; a token cannot mint another token.

Writes below need catalog:edit unless noted. 403 means the owner's role lacks that permission, not that the path is wrong.

Instructions

1. Discover current meaning via MCP (search_terms, get_term, get_term_columns, get_term_sql_attributes, describe_table) or REST if MCP is absent (GET /api/terms, GET /api/terms/{term_id}, GET /api/exploration/tables/{table_id}/details).

2. Resolve the semantic contract when meaning changes. Record source binding, identity, population, relationship cardinality, measure expression, unit, grain, denominator, time, validity, and counterexamples; see modeling.md.

3. State the proposed change to the user (term rename, new SQL attribute, import, and so on). Do not silently rewrite the glossary.

4. Validate SQL before create/update: POST /api/sql-attributes/validate. A parse failure is HTTP 422, not valid: false.

5. Apply the smallest write that matches the request (see write-api.md).

6. Compilation is not a hidden side effect. Check GET /api/semantic-compilation/status. Do not call POST /api/semantic-compilation/reset as cleanup — it is an asynchronous, destructive rebuild of every database's compiled layer, returns 202, and requires semanticCompilation:manage.

7. Verify the persisted change, not merely request success. Model imports require a scoped backup and exact re-export comparison; see publication.md. Then use MCP check_answerable / ask_question (or REST POST /api/question-entity-coverage and POST /api/chat/completions) for positive and negative behavior checks.

Semantic relationships and "what does this dataset mean"

Stay on the semantic layer. Do not browse raw schemas to answer meaning.

• Term → columns: MCP get_term_columns or GET /api/terms/{term_id}/column-attributes

• Term → derived SQL: MCP get_term_sql_attributes

• Table → terms and SQL attributes: MCP describe_table or GET /api/exploration/tables/{table_id}/details

• Semantic hop chain between two terms: GET /api/exploration/terms/{term_id}/path/{other_term_id}

• Semantic graphs: GET /api/exploration/graph, GET /api/exploration/semantic-graph

These are semantic relationship paths, not generation provenance, source revision, certification history, or version lineage.

Bulk import / export

• POST /api/model/export — YAML of catalog + semantic layer. Permission modelInterchange:export. Body may set catalog database IDs in databases (empty = all) and format (auto_ontology or ossie).

• POST /api/model/import — multipart YAML; native Auto Ontology (data_layer / semantic_layer) or Apache Ossie (version, name, datasets at the root). Query replace (default true) and embed (default true). Permission modelInterchange:import. Can replace existing data — confirm with the user before replace=true, apply first in isolation, and use the exact readback workflow in publication.md.

Examples

• To define a run-grain measure, follow the evidence and counterexample workflow in modeling.md.

• To revise and promote a model, back up the exact scope and follow the staged readback workflow in publication.md.

Troubleshooting

For write failures, verify the authenticated owner's permission, distinguish HTTP 422 parse failures from validation results, and inspect compilation status before changing the model or resetting compilation.

See also

• write-api.md

• modeling.md

• publication.md

• nvidia-ontology-query — how to call Auto Ontology and validate query results

• nvidia-ontology-setup — deployment not ready

• mcp/auto_ontology_mcp/tools.py — live read-tool allow-list