From omni-analytics
Create and edit Omni Analytics semantic model definitions—views, topics, dimensions, measures, relationships, query views—using YAML via REST API. For adding fields, joins, metrics, or modifying data models.
npx claudepluginhub exploreomni/omni-claude-skillsThis skill uses the workspace's default tool permissions.
Create and modify Omni's semantic model through the YAML API — views, topics, dimensions, measures, relationships, and query views.
Create and edit Omni Analytics semantic model definitions — views, topics, dimensions, measures, relationships, and query views — using YAML through the Omni CLI. Use this skill whenever someone wants to add a field, create a new dimension or measure, define a topic, set up joins between tables, modify the data model, build a new view, add a calculated field, create a relationship, edit YAML, work on a branch, promote model changes, or any variant of "model this data", "add this metric", "create a view for", or "set up a join between". Also use for migrating modeling patterns since Omni's YAML is conceptually similar to other semantic layer definitions.
Guides creation and modification of dbt Semantic Layer components: semantic models, metrics (simple/derived/cumulative/ratio), dimensions, entities, time spines. Supports latest/legacy YAML specs and MetricFlow config.
Provides patterns for building dbt models, adding tests, and designing data models including dimensional modeling, staging/intermediate/marts organization, naming conventions, and testing strategies.
Share bugs, ideas, or general feedback.
Create and modify Omni's semantic model through the YAML API — views, topics, dimensions, measures, relationships, and query views.
Tip: Always use
omni-model-explorerfirst to understand the existing model.
export OMNI_BASE_URL="https://yourorg.omniapp.co"
export OMNI_API_KEY="your-api-key"
You need Modeler or Connection Admin permissions.
Omni uses a layered approach where each layer builds on top of the previous:
Schema Layer — Auto-generated from your database. Reflects tables, views, columns, and their types. Kept in sync via schema refresh.
Shared Model Layer — Your governed semantic model. Where you define dimensions, measures, joins, and topics that are reusable across the organization.
Workbook Model Layer — Ad hoc extensions within individual workbooks. Used for experimental fields before promotion to shared model.
Branch Layer — Intermediate development layer. Used when working in branches before merging changes to shared model.
Key concept: The schema layer is the foundation and source of truth for table/column structure. When your database schema changes (new tables, deleted columns, type changes), you refresh the schema to keep Omni in sync. All user-created content (dimensions, measures, relationships, topics) flows through the shared model layer.
Development workflow: When building or modifying the model, you work in branches (see "Safe Development Workflow" below). Branches are isolated copies where you can safely experiment before merging changes back to shared model. This skill covers creating and editing model definitions in both branches and shared models.
Before writing any SQL expressions, confirm the dialect from the connection — don't guess from the connection name:
# 1. Get the model's connectionId
curl -L "$OMNI_BASE_URL/api/v1/models/{modelId}" \
-H "Authorization: Bearer $OMNI_API_KEY"
# 2. Look up the connection's dialect
curl -L "$OMNI_BASE_URL/api/v1/connections" \
-H "Authorization: Bearer $OMNI_API_KEY"
# → find your connectionId and read the "dialect" field
# → e.g. "bigquery", "postgres", "snowflake", "databricks"
Use dialect-appropriate functions in your SQL (e.g. SAFE_DIVIDE for BigQuery, NULLIF(a/b) for Postgres/Snowflake).
The schema layer is auto-generated from your database. When your database schema changes (new/deleted/renamed columns, type changes), refresh Omni's schema layer to stay in sync.
When to trigger:
What it does:
Side effect: May auto-generate dimensions for columns you don't need. Suppress with hidden: true in your extension layer.
Trigger via API:
curl -L -X POST "$OMNI_BASE_URL/api/v1/models/{modelId}/refresh" \
-H "Authorization: Bearer $OMNI_API_KEY"
# With branch:
curl -L -X POST "$OMNI_BASE_URL/api/v1/models/{modelId}/refresh?branch_id={branchId}" \
-H "Authorization: Bearer $OMNI_API_KEY"
Requires Connection Admin permissions.
When unsure whether an endpoint or parameter exists, fetch the OpenAPI spec:
curl -L "$OMNI_BASE_URL/openapi.json" \
-H "Authorization: Bearer $OMNI_API_KEY"
Use this to verify endpoints, available parameters, and request/response schemas before making calls.
Always work in a branch. Never write directly to production.
Omni branches are models with modelKind: "BRANCH". There is no dedicated branch-creation endpoint — create one via POST /api/v1/models:
curl -L -X POST "$OMNI_BASE_URL/api/v1/models" \
-H "Authorization: Bearer $OMNI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"modelKind": "BRANCH",
"baseModelId": "{sharedModelId}",
"connectionId": "{connectionId}",
"modelName": "my-feature-branch"
}'
The response model.id is your branchId — a UUID you'll pass to all subsequent API calls. To list existing branches at any time:
curl -L "$OMNI_BASE_URL/api/v1/models?include=activeBranches" \
-H "Authorization: Bearer $OMNI_API_KEY"
Git-connected models: If your model is connected to a git repo (
GET /api/v1/models/{modelId}/gitreturns ansshUrl), merging an Omni branch will automatically commit the changes back to your gitbaseBranch. Choose one workflow and stick to it — either edit via the Omni branch API (thengit pullto sync local files), or edit local files and push via git. Mixing both leads to conflicts.
curl -L -X POST "$OMNI_BASE_URL/api/v1/models/{modelId}/yaml" \
-H "Authorization: Bearer $OMNI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"fileName": "my_new_view.view",
"yaml": "dimensions:\n order_id:\n primary_key: true\n status:\n label: Order Status\nmeasures:\n count:\n aggregate_type: count",
"mode": "extension",
"branchId": "{branchId}",
"commitMessage": "Add my_new_view with status dimension and count measure"
}'
Note: The
branchIdparameter must be a UUID from the server (Step 0). Passing a string name instead will return400 Bad Request: Unrecognized key: "branchName".
curl -L "$OMNI_BASE_URL/api/v1/models/{modelId}/validate?branchId={branchId}" \
-H "Authorization: Bearer $OMNI_API_KEY"
Returns validation errors and warnings with message, yaml_path, and sometimes auto_fix.
Important: Always ask the user for confirmation before merging. Merging applies changes to the production model and cannot be easily undone.
curl -L -X POST "$OMNI_BASE_URL/api/v1/models/{modelId}/branch/{branchName}/merge" \
-H "Authorization: Bearer $OMNI_API_KEY"
If git with required PRs is configured, merge through your git workflow instead.
| Type | Extension | Purpose |
|---|---|---|
| View | .view | Dimensions, measures, filters for a table |
| Topic | .topic | Joins views into a queryable unit |
| Relationships | (special) | Global join definitions |
Write with mode: "extension" (shared model layer). To delete a file, send empty yaml.
Every view MUST have a
primary_key: truedimension. Without a primary key, queries that join to this view will produce fanout errors or incorrect aggregations. Use the table's natural unique identifier (e.g.,id,order_id,user_id). If the table has no single unique column, create a composite key with a SQL expression:sql: ${schema_name} || '-' || ${table_name}.
dimensions:
order_id:
primary_key: true
status:
label: Order Status
created_at:
label: Created Date
measures:
count:
aggregate_type: count
total_revenue:
sql: ${sale_price}
aggregate_type: sum
format: currency_2
When you create a view, Omni separates schema (database structure) from model (your business logic):
When both layers exist for a field with the same name, your extension definition wins but type information comes from the schema layer.
Example: Table has columns created_at (DATE) and revenue (NUMERIC).
# Schema layer (auto-generated)
dimensions:
created_at: {} # type: DATE, auto-generates timeframes
revenue: {} # type: NUMERIC
# Extension layer (your YAML)
dimensions:
created_at:
label: "Order Created"
description: "When the order was placed"
revenue:
hidden: true # Hide the raw column
measures:
total_revenue:
sql: SUM(${revenue})
aggregate_type: sum
format: currency_2
Result: created_at inherits its type from schema layer (DATE with automatic week/month/year granularities) but gets your label. The raw revenue column is hidden, only exposed through the total_revenue measure.
Key insight: If your extension layer defines a dimension but there's no schema layer base dimension to provide type information, Omni can't infer granularities or types. Solution: trigger schema refresh to auto-generate the schema layer (see "Schema Refresh" section above).
See references/modelParameters.md for the complete list of 35+ dimension parameters, format values, and timeframes.
Most common parameters:
sql — SQL expression using ${field_name} referenceslabel — display name · description — help text (also used by Blobby)primary_key: true — unique key (critical for aggregations)hidden: true — hides from picker, still usable in SQLformat — number_2, currency_2, percent_2, idgroup_label — groups fields in the pickersynonyms — alternative names for AI matching (e.g., [client, account, buyer])See references/modelParameters.md for the complete list of 24+ measure parameters and all 13 aggregate types.
Measure filters restrict rows before aggregation:
measures:
completed_orders:
aggregate_type: count
filters:
status:
is: complete
california_revenue:
sql: ${sale_price}
aggregate_type: sum
filters:
state:
is: California
Filter conditions: is, is_not, greater_than, less_than, contains, starts_with, ends_with
See Topics setup for complete YAML examples with joins, fields, and ai_context, and Topic parameters for all available options.
Key topic elements:
base_view — the primary view for this topicjoins — nested structure for join chains (e.g., users: {} or inventory_items: { products: {} })ai_context — guides Blobby's field mapping (e.g., "Map 'revenue' → total_revenue")default_filters — applied to all queries unless removedalways_where_sql — non-removable filtersfields — field curation: [order_items.*, users.name, -users.internal_id]- join_from_view: order_items
join_to_view: users
on_sql: ${order_items.user_id} = ${users.id}
relationship_type: many_to_one
join_type: always_left
| Type | When to Use |
|---|---|
many_to_one | Orders → Users |
one_to_many | Users → Orders |
one_to_one | Users → User Settings |
many_to_many | Tags ↔ Products (rare) |
Getting relationship_type right prevents fanout and symmetric aggregate errors.
Virtual tables defined by a saved query. Like regular views, query views must include a primary_key: true dimension to be joinable:
schema: PUBLIC
query:
fields:
order_items.user_id: user_id
order_items.count: order_count
order_items.total_revenue: lifetime_value
base_view: order_items
topic: order_items
dimensions:
user_id:
primary_key: true
order_count: {}
lifetime_value:
format: currency_2
Or with raw SQL:
schema: PUBLIC
sql: |
SELECT user_id, COUNT(*) as order_count, SUM(sale_price) as lifetime_value
FROM order_items GROUP BY 1
| Error | Fix |
|---|---|
| "No view X" | Check view name spelling |
| "No join path from X to Y" | Add a relationship |
| "Duplicate field name" | Remove duplicate or rename (or suppress with hidden: true if one is auto-generated) |
| "Invalid YAML syntax" | Check indentation (2 spaces, no tabs) |
| Fanout / incorrect aggregations on joins | Add primary_key: true to the joined view — every view that participates in a join must have a primary key |
Column reference error (e.g., "Column X not found") | Check that the table exists and your Omni connection has access |
If your model doesn't reflect the database (missing columns, broken references, wrong types), trigger a schema refresh (see "Schema Refresh" section above). Then validate:
curl -L "$OMNI_BASE_URL/api/v1/models/{modelId}/validate" \
-H "Authorization: Bearer $OMNI_API_KEY"
Common issues and fixes:
| Issue | Cause | Fix |
|---|---|---|
| Broken column references | Column no longer exists in database | Remove or update the sql reference |
| Field name collision | Auto-generated dimension conflicts with your measure | Suppress with hidden: true or rename |
| Unknown field types | Type info not available from schema | Verify column exists and connection has access |
| Missing tables | Table not in schema after refresh | Verify table exists and connection includes its database/schema |