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Found 11 Skills
Use when creating or modifying dbt Semantic Layer components including semantic models, metrics, and dimensions leveraging MetricFlow.
Use Fabric CLI for Power BI operations — semantic models, reports, DAX queries, refresh, gateways. Activate when users work with Power BI items, need to refresh datasets, execute DAX, manage reports, or troubleshoot refresh failures.
Discover and inspect Omni Analytics models, topics, views, fields, dimensions, measures, and relationships using the Omni CLI. Use this skill whenever someone wants to understand what data is available in Omni, explore their semantic model, find specific fields or views, check how tables join together, see what topics exist, or asks any variant of "what can I query", "what fields are available", "show me the model", "what data do we have", or "how is this data modeled". Also use when you need to understand the Omni model structure before building or modifying anything.
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.
Core Power BI data modeling, source connectivity, and platform fundamentals. PROACTIVELY activate for: (1) Power BI data modeling and star-schema design, (2) relationships (active/inactive, bidirectional, USERELATIONSHIP), (3) data-source selection (DirectQuery vs Import vs Direct Lake vs composite), (4) incremental refresh setup, (5) gateway configuration (on-prem and VNet gateways), (6) streaming datasets and push-data scenarios, (7) Dataflow Gen2 basics, (8) Power BI common gotchas and pitfalls (bidirectional filtering, AutoExist, blank-row), (9) workspace identity and OAuth2 / service-principal auth, (10) semantic model architecture review. Provides: star-schema templates, mode-selection matrix, incremental refresh recipe, gateway setup steps, and a common-gotchas reference.
Standards and best practices for writing LookML tests to ensure data integrity, accuracy, and logic validation.
Salesforce Data 360 reports, dashboards, report types, reportability of DMOs and calculated insights, dashboard limits, consumption insights, and semantic model analytics. TRIGGER when: the user creates, reviews, packages, or debugs Data 360 reports, dashboards, report types, KPI dashboards, or analytics built on DMOs, CIOs, or semantic models.
Answer natural-language business questions over existing Power BI reports and semantic models through the FabricIQ MCP endpoint. Orchestrates artifact discovery, schema inspection, entity resolution, DAX generation, and query execution to return plain-language answers. Use when the user asks what, which, compare, rank, explain, or summarize questions about the data in a Power BI report or semantic model, including asking for a DAX query to be run against a named model. Triggers: "ask power bi", "PBI question", "discover my Power BI report", "report data", "dashboard data", "what are the top", "show me the power bi data", "which products sold", "compare sales in report", "which customers churned", "ask the Power BI report", "query a Power BI semantic model", "run a DAX query against a semantic model".
Search and inspect a Cube semantic model — cubes, views, measures, dimensions, joins, and the files they live in — using the Cube CLI. Use whenever someone wants to know what data is available in Cube, where a metric is defined, which cube a field belongs to, how two cubes join, or what a change would affect. Triggers on "what can I query", "what measures do we have", "where is revenue defined", "show me the data model", "what's in this deployment", "which cube has customer email", and impact questions like "what breaks if I rename this". Read the model with this skill before changing it. To edit the model use cube-build-model; to run a query and get numbers back use cube-run-query; to browse workbooks, dashboards and reports use cube-explore-content.
Inspect and tune Cube's in-product AI agent — its rules, certified queries and Agent Skills — by authoring markdown in the semantic model with the Cube CLI. Use whenever someone wants the Cube agent to answer better: teach it a business definition, stop it making a recurring mistake, certify a trusted query, capture a repeatable workflow as a skill, or find out why it answered the way it did. Triggers on "the agent keeps getting X wrong", "teach the agent that", "make the agent always", "add a certified query", "create an agent skill", "why did the agent say that", "what rules does the agent have". To change the underlying model use cube-build-model; to explore what is queryable use cube-explore-model.
Author and change a Cube semantic model — add or edit cubes, views, measures, dimensions, joins and pre-aggregations in YAML — using the Cube CLI, on a dev-mode branch, then commit and build. Use whenever someone wants to add a metric, define a measure or dimension, create a cube or view, join two cubes, fix a model error, rename a field, or expose a field to business users. Triggers on "add a metric", "define revenue", "create a view for", "expose this field", "join orders to customers", "fix the model", "add a pre-aggregation". Read the model first with cube-explore-model. To run a query against the result use cube-run-query; to deploy or check build status use cube-deploy.