| name | power-bi |
| description | Veteran-level reference for Power BI — PBIP project structure + git, semantic model design, DAX patterns + performance, deployment pipelines, refresh / gateway troubleshooting, integration with Power Platform solutions / ALM. Used by `power-bi-engineer` (primary). |
Power BI Skill
Purpose: Provide veteran-level reference and patterns for the new power-bi-engineer agent — semantic model design, DAX, PBIP git workflows with Azure DevOps, deployment, refresh troubleshooting, and integration with Power Platform solutions/ALM.
When to Use
- Designing or reviewing semantic models and DAX.
- Setting up or troubleshooting PBIP projects in git / Azure DevOps.
- Deployment pipeline or refresh/gateway issues.
- Coordinating Power BI artifacts with solution ALM or flows.
How to Use This Skill
- Start with this
SKILL.md for architecture and decision guidance.
- Dive into
resources/*.md for specifics (PBIP structure, git patterns, DAX, etc.).
- Combine with
solution-alm-engineer for end-to-end pipelines that include Power BI.
Core Principles
- PBIP is mandatory for anything going into source control or ADO. Binary .pbix files are not reviewable or mergeable.
- Treat the semantic model as code (model definition + measures).
- Parameters + Deployment Rules > hard-coded values or multiple branches.
- Test refresh and deployment in clean workspaces/environments.
- Keep models focused — prefer composite models over monolithic ones for large scenarios.
Key Areas
- PBIP folder structure and what to commit / .gitignore
- Git workflows and common ADO/PBIP issues (large JSON diffs, merge conflicts, parameter handling)
- DAX performance patterns and tools (DAX Studio, VertiPaq Analyzer, Tabular Editor)
- Deployment strategies (Power BI Deployment Pipelines vs custom ADO pipelines with service principals / REST / Tabular Editor CLI)
- Refresh, gateways, incremental refresh, and XMLA
- Integration with Dataverse sources and solution packaging
Recommended Resources
resources/pbip-structure-and-git.mdresources/dax-patterns-and-performance.mdresources/deployment-and-pipelines.mdresources/refresh-gateway-troubleshooting.md
Copilot-readiness (why reports come back generic)
Power BI Copilot output quality is a function of how well the semantic model is grounded for AI, not of the report visuals — an under-grounded model yields thin, generic narratives because Copilot has to guess the goal and the preferred metric. When the work is "make Copilot produce meaningful reports," the lever is Microsoft's Prep data for AI feature — author in Microsoft's recommended order: AI data schema → verified answers → AI instructions → descriptions, then mark the model Approved for Copilot. The single highest-leverage goal channel is AI instructions (model-level, ≤ 10,000 chars): it states the model's purpose, maps user vocabulary → model fields, and defines business terms Copilot can't infer. The fill-in-the-blanks authoring artifact lives at ../../templates/power-bi-copilot-ai-instructions.md — drop a copy next to the model, replace the placeholders, paste each block into the surface it names. The field-level grounding floor (description/format/folder + synonyms) is ../../best-practices/enforce-measure-metadata.md.
Knowledge bank pointers
For production-incident lessons (real customer engagements, with a decision tree + the workaround that resolved it), consult the plugin's knowledge/ directory in addition to the resources above. The full §8a table is in ../../CLAUDE.md; the Power BI–specific entry to know about:
knowledge/pbir-enhanced-report-loading.md — debug runbook. Read when a PBIR Enhanced report deploys but won't render. Covers the resourcePackages + version.json "infinite spinner" trap, the ~June 2026 Fabric breaking change rejecting prototypeQuery on visuals, and the correct nativeQueryRef + active projection shape. Verified against 7 real Enhanced repos 2026-06-02.knowledge/pbir-enhanced-reference.md — build reference. Read when authoring a new visual / page / report JSON. Full visual-type → queryState role catalog, filterConfig syntax (Categorical / Advanced / TopN / RelativeDate), slicer modes + pre-selection, objects vs visualContainerObjects split, literal-suffix rules, and verified real-file examples for KPI / Matrix / Scatter / Waterfall / Gauge / Multi-Row Card / 100% Stacked / Button Slicer. Synthesized 2026-06-02.knowledge/dax-category-name-mismatch-zero-scores.md — debug runbook + design pattern. Read when a scoring report deploys and renders fine but every measure returns 0 / BLANK across all entities — or proactively before writing any DAX measure that filters a dimension column by a hardcoded string. Captures the silent-zero failure shape, the SUMMARIZE diagnosis pattern, the Domain calculated-column fix (recommended) that decouples DAX from data-source category strings, and the score-scale gotcha. Production lesson from the BMA CSP Thematic Review (Contoso DEV, June 2026).knowledge/sempy-fabric-reference.md — Python-from-a-Fabric-notebook reference. Read when the work is semantic-model interrogation, DAX execution, refresh orchestration, TOM editing, or workspace / lakehouse / item enumeration via sempy.fabric. Inventory of every top-level function (workspace, dataset, refresh, TOM, lakehouse, item) + classes + submodules, with the ReadWrite-permission gate flagged. Distilled from the Microsoft Learn API reference 2026-06-02.
This skill directly supports the new power-bi-engineer and ties into the enhanced ALM coverage for git/ADO scenarios.
