Loading...
Loading...
Found 17 Skills
Plan, design, author, preview, publish, and manage Power BI reports across requirements, page design, local PBIR/PBIP edits, validation, screenshots, Fabric upload/download, and rebinding. Use for report lifecycle work; use semantic-model-authoring for model or DAX changes and fabriciq for data questions. Triggers: plan Power BI report, design report page, edit PBIR, preview PBIP, publish report, rebind report
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.
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.
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.
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.
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.
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.
Standards and best practices for writing LookML tests to ensure data integrity, accuracy, and logic validation.
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.
Find and explore RevOS metrics — the measures of the org's semantic model, as the app's Metrics page lists them — through the RevOS MCP server: which metrics exist, what each one aggregates and how it's formatted, which tables, segments, and dashboard cards use it, and what its value is right now, counted over a segment or a few conditions and optionally broken down by a dimension. Use this whenever the user asks "what metrics do we have", "is there a metric for win rate / ARR / open pipeline", "where is this metric used", "what's open pipeline for the EMEA segment", "deal amount by stage", or wants a metric's value the same way a dashboard card would show it — even if they never say "metric". For putting a metric on a dashboard, use the dashboards skill; it builds on this one.
Create, edit, and troubleshoot RevOS segments — saved audiences defined over the org's semantic model — through the RevOS MCP server, and attach them to a table so its rows are scoped. Use this whenever the user wants to save, define, or change an audience or list ("companies with an active subscription", "deals over 50k in the EMEA pipeline", "users who ordered twice"), add or change a condition on an existing segment, show only some rows in a table ("only the stalled deals", "filter this table to…"), or asks why a segment is FAILED, empty, or showing the wrong rows — even if they never say the word "segment". Read it before the first api_write on the `segments` or `table-views` resource.