Automatically invoke this skill whenever the user asks about Fabric tenant settings or Power BI tenant settings or auditing tenant settings. You can use this skill if the user mentions "Fabric administration".
日本語の概要は準備中です。原文の説明を表示しています。
Deneb visual creation, Vega/Vega-Lite spec authoring, and Deneb best practices for PBIR reports. Automatically invoke whenever the user mentions "Deneb" in any context, or asks about Vega/Vega-Lite specs in Power BI, Deneb cross-filtering, Deneb interactivity, pbiColor theme integration, Deneb field name escaping, or Deneb rendering issues.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Use
pbirfor every report mutation. Read PBIR metadata only for diagnosis. Ifpbiris unavailable or lacks an operation, stop and report the gap; never edit report JSON directly.
Deneb is a certified custom visual for Power BI that enables Vega and Vega-Lite declarative visualization specs directly inside reports. Author specs using this skill.
Prefer Vega-Lite for new Deneb visuals unless specific Vega-only features are required (signals, event streams, custom projections, force/voronoi layouts). Vega-Lite is more concise, easier to maintain, and covers most chart types. For advanced Vega features, see references/vega-patterns.md and the Vega documentation.
deneb7E15AEF80B9E4D4F8E12924291ECE89Av6.json schema URLs)dataset role (all fields go into one "Values" well)dataLimit.override)vegaLite (default) or vega (when Vega-specific features needed)svg (default, sharp text) or canvas (better for large datasets)Copying a working Deneb visual with pbir cp carries its registration. For a new visual, inspect
publicCustomVisuals with pbir get and update the complete list through pbir set --json,
preserving any existing ids. Never edit report.json directly.
Create the visual and bindings through pbir:
pbir add visual deneb7E15AEF80B9E4D4F8E12924291ECE89A \
"Report.Report/Page.Page" --name RevenueByCategoryDeneb
pbir visuals bind "Report.Report/Page.Page/RevenueByCategoryDeneb.Visual" \
--add "dataset:Sales.Category" --type Column
pbir visuals bind "Report.Report/Page.Page/RevenueByCategoryDeneb.Visual" \
--add "dataset:Sales.Revenue" --type Measure
All fields bind to the single dataset role. Use Table.Column for columns and Table.Measure for measures. Field names in bindings must match those used in the Vega/Vega-Lite spec.
Create a Vega-Lite (or Vega) JSON spec file. Key difference:
"data": {"name": "dataset"} (object)"data": [{"name": "dataset"}] (array){
"$schema": "https://vega.github.io/schema/vega-lite/v6.json",
"data": {"name": "dataset"},
"mark": {"type": "bar", "tooltip": true},
"encoding": {
"y": {"field": "Category", "type": "nominal"},
"x": {"field": "Value", "type": "quantitative"}
}
}
See examples/spec/ for complete spec files (Vega and Vega-Lite) and examples/visual/ for full PBIR visual.json files. Field names in the spec must match the nativeQueryRef (display name) from the field bindings.
pbir visuals deneb "Report.Report/Page.Page/RevenueByCategoryDeneb.Visual" \
--spec-file chart.vl.json --provider vegaLite
The CLI handles PBIR encoding. Keep ordinary Vega or Vega-Lite JSON in the spec file.
Before presenting the spec to the user, dispatch the deneb-reviewer agent to validate syntax and provide design feedback.
pbir visuals bind "Report.Report/Page.Page/RevenueByCategoryDeneb.Visual" --show
pbir validate "Report.Report" --all
"data": [{"name": "dataset"}] (array form)"data": {"name": "dataset"} (object form)., [, ], \, ") become _"Order Lines")Escaping depends on whether the spec is standalone or injected into a PBIR visual.json:
Standalone spec files (in examples/spec/): use double quotes with JSON escaping:
{"calculate": "datum[\"Order Lines\"] - datum[\"Order Lines (PY)\"]", "as": "diff"}
Inside PBIR visual.json (in examples/visual/): the entire spec is a single-quoted DAX literal string. Field names with spaces use doubled single quotes (''):
datum[''Order Lines''] - datum[''Order Lines (PY)'']
Single quotes that are NOT part of field name escaping (e.g., string literals in filter expressions like datum.Series == 'Actuals') work as-is because they don't conflict with the outer single-quote wrapper.
Use Deneb's built-in signals for responsive container sizing:
"width": {"signal": "pbiContainerWidth - 25"},
"height": {"signal": "pbiContainerHeight - 27"}
The offsets account for padding. For absolute positioning of text marks, use {"signal": "width"} instead of hardcoded pixel values.
Always provide a config file for consistent styling. See the Standard Config section in references/vega-patterns.md. Key settings: autosize: fit, view.stroke: transparent, font: Segoe UI.
Use Power BI theme colors instead of hardcoded hex values:
| Function/Scheme | Purpose | Usage in Vega |
|---|---|---|
pbiColor(index) | Theme color by index (0-based) | {"signal": "pbiColor(0)"} |
pbiColor(0, -0.3) | Darken theme color by 30% | Shade: -1 (dark) to 1 (light) |
pbiColor("negative") | Sentiment colors | "min", "middle", "max", "negative", "positive" |
pbiColor("bad") | Aliases for sentiment | "bad" = "negative", "good" = "positive", "neutral" = "middle" |
pbiColorNominal | Categorical palette (distinct) | "range": {"scheme": "pbiColorNominal"} |
pbiColorOrdinal | Ordinal palette (ordered categories) | "range": {"scheme": "pbiColorOrdinal"} |
pbiColorLinear | Continuous gradient | "range": {"scheme": "pbiColorLinear"} |
pbiColorDivergent | Divergent gradient | "range": {"scheme": "pbiColorDivergent"} |
Enable interactivity via the vega objects in visual.json:
| Feature | Property | Default | Notes |
|---|---|---|---|
| Tooltips | enableTooltips | true | Use "tooltip": {"signal": "datum"} in encode |
| Context menu | enableContextMenu | true | Right-click drill-through |
| Cross-filtering | enableSelection | false | Requires __selected__ handling |
| Cross-highlighting | enableHighlight | false | Creates <field>__highlight fields |
When enableSelection is true, handle __selected__ ("on", "off", "neutral") in encode blocks. Selection modes: simple (auto-resolves, up to 250 data points) or advanced (Vega only; required for brush/lasso/region selection, supports up to 2500 via options.limit, exposes pbiCrossFilterApply and pbiCrossFilterClear signals). See references/vega-patterns.md for the simple pattern and references/advanced-patterns.md for the advanced signal API.
Use layered marks -- background at reduced opacity, foreground shows <field>__highlight values. See references/vega-patterns.md for details.
Deneb injects runtime fields into each dataset row. See references/capabilities.md for the full table.
Key fields: __row__ (zero-based row index, replaces removed __identity__), __selected__ (selection state), <field>__highlight + <field>__highlightStatus + <field>__highlightComparator (cross-highlighting), <field>__formatted (pre-formatted value string), <field>__format (Power BI format string).
Breaking change in 1.9:
__identity__and__key__were removed. Replace anydatum.__identity__withdatum.__row__.
autosize: fit in config for responsive Power BI sizingpbiContainerWidth/pbiContainerHeight signals for responsive Vega specspbiColor, pbiColorNominal) instead of hex valuesenter/update/hover encode blocks for clean state management (Vega only)"tooltip": {"signal": "datum"} on marksrenderMode: canvas for many marks, and only then raise dataLimit.override. See references/advanced-patterns.md for the full lever ordernativeQueryRef matches spec field referencesDeneb is the preferred choice for advanced custom visuals that need interactivity (cross-filtering, tooltips, hover effects) and go beyond what native Power BI visuals offer. Use Deneb when you need:
Use SVG measures instead for simple inline graphics in tables/cards (sparklines, data bars, progress bars) where interactivity is not needed. Use Python/R instead for statistical visualizations (distribution analysis, regression, correlation) where the focus is analytical rigor over interactivity.
references/community-examples.md -- 170+ community templates organized by chart type, with author citations and direct linksreferences/vega-patterns.md -- Vega chart patterns (bar, line, scatter, donut, stacked, heatmap, area, lollipop, bullet, KPI card), standard config, transforms and scales referencereferences/vega-lite-patterns.md -- Vega-Lite chart patterns (for editing existing Vega-Lite visuals only)references/pbir-structure.md -- PBIR JSON structure (literal encoding, query state, interactivity example)references/capabilities.md -- Full Deneb object properties reference and template format (usermeta schema)references/advanced-patterns.md -- Advanced cross-filtering signals (Vega pbiCrossFilterApply/pbiCrossFilterClear), performance engineering lever order, and community template round-trip from the terminalexamples/visual/bullet-chart.json -- PBIR visual.json: faceted bullet chart with conditional indicators and cross-filtering (Vega-Lite)examples/visual/kpi-card.json -- PBIR visual.json: KPI card with layered text and conditional % change coloring (Vega-Lite)examples/visual/trend-line.json -- PBIR visual.json: dual-series line chart with fold transform and color/legend mapping (Vega-Lite)examples/visual/ytd-comparison.json -- PBIR visual.json: YTD vs target with dashed lines, endpoint labels, number formatting, and rank-based filtering (Vega-Lite)examples/spec/vega/ -- Standalone Vega spec files (bar-chart, line-chart) -- ready to inject into visual.json after escapingexamples/spec/vega-lite/ -- Standalone Vega-Lite spec files (bullet-chart, kpi-card) -- ready to inject after escapingexamples/standard-config.json -- Standard config for all Deneb specsTo retrieve current Power BI custom visual docs, use microsoft_docs_search + microsoft_docs_fetch (MCP) if available, otherwise mslearn search + mslearn fetch (CLI). Search based on the user's request and run multiple searches as needed to ensure sufficient context before proceeding. Note: Vega/Vega-Lite docs live at vega.github.io (not MS Learn) -- use WebFetch for those.
pbir-format (pbip plugin) -- PBIR JSON format referencepbi-report-design -- Layout and design best practicesr-visuals -- R Script visuals (ggplot2)python-visuals -- Python Script visuals (matplotlib)svg-visuals -- SVG via DAX measures (lightweight inline graphics)まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Automatically invoke this skill whenever the user asks about Fabric tenant settings or Power BI tenant settings or auditing tenant settings. You can use this skill if the user mentions "Fabric administration".
日本語の概要は準備中です。原文の説明を表示しています。
Interactive BPA rule generation for Power BI semantic models; guided discovery, model investigation, and expert rule authoring. Automatically invoke when the user mentions "BPA rule", "Best Practice Analyzer", or asks to "create a BPA rule", "audit BPA rules", "recommend BPA rules", "set up BPA for my team", "check model for best practices", "validate BPA rules", "improve a BPA expression".
日本語の概要は準備中です。原文の説明を表示しています。
Writing and executing C# scripts and macros against Power BI semantic models using Tabular Editor 2/3. Automatically invoke when the user mentions "C# script", "Tabular Editor script", "TOM scripting", "MacroActions.json", "XMLA", or asks to "automate model changes", "bulk update measures", "create calculation groups", "write a macro", "format DAX expressions", "manage model metadata".
日本語の概要は準備中です。原文の説明を表示しています。
TOM and ADOMD.NET guidance via PowerShell for connecting to Power BI Desktop's local Analysis Services instance. Covers model enumeration, DAX queries, metadata modification, annotations, calendar definitions, field parameters, query tracing, DAX library package management (daxlib.org), and the Desktop Bridge for reloading and screenshotting the report canvas. Automatically invoke when the user mentions "Power BI Desktop", "Analysis Services port", "TOM", "ADOMD", "daxlib", "DAX library", "DAX UDF package", or asks to "connect to PBI Desktop", "query PBI Desktop with DAX", "modify PBI Desktop model", "add a measure to PBI", "capture visual queries", "create a field parameter", "validate DAX", "intercept DAX queries", "install daxlib", "add DAX SVG", "add IBCS", "reload the report canvas", "screenshot a report page", "Desktop Bridge", or to work with the model and report in Power BI Desktop together.
日本語の概要は準備中です。原文の説明を表示しています。
Step-by-step workflow for creating complete Power BI reports from scratch using pbir CLI. Covers model discovery, report creation, page layout, theme setup, visual placement, field binding, filtering, formatting, validation, and publishing. Automatically invoke when the user asks to "create a new report", "build a report from scratch", "make a dashboard", "set up a report with KPIs", "create an executive dashboard", "add pages and visuals to a new report".
日本語の概要は準備中です。原文の説明を表示しています。
DAX performance optimization for semantic models. Automatically invoke when the user asks to "optimize DAX", "fix slow DAX", "DAX performance", "tune a measure", "debug a measure", "DAX anti-patterns", or mentions slow queries, server timings, or DAX authoring.
日本語の概要は準備中です。原文の説明を表示しています。