Agent Skills › microsoft/rayfin › visuals

visuals

GitHub

指导在项目中集成图表、图形和数据网格等数据可视化组件。提供VegaVisual和DataGrid的使用规范,包括包导入、DataTable统一数据格式及主题处理。

samples/data-app/.agents/skills/visuals/SKILL.md microsoft/rayfin

Trigger Scenarios

用户需要创建图表或折线图 用户需要展示表格数据 用户询问数据可视化实现

Install

npx skills add microsoft/rayfin --skill visuals -g -y
More Options

Non-standard path

npx skills add https://github.com/microsoft/rayfin/tree/main/samples/data-app/.agents/skills/visuals -g -y

Use without installing

npx skills use microsoft/rayfin@visuals

指定 Agent (Claude Code)

npx skills add microsoft/rayfin --skill visuals -a claude-code -g -y

安装 repo 全部 skill

npx skills add microsoft/rayfin --all -g -y

预览 repo 内 skill

npx skills add microsoft/rayfin --list

SKILL.md

Frontmatter
{
    "name": "visuals",
    "description": "Use when user wants to incorporate charts, graphs, data grid,  or other visual representations of data into their project. Use VegaVisual and DataGrid components to create these visuals,  utilizing the shared data types, formatting, theme, and interactivity hooks."
}

Visuals

Types of visuals

There are 2 different types of visuals that can be used in a project:

  1. Charts and Graphs: These are used to represent data in a visual format, such as bar charts, line charts, pie charts, etc. These are built using vega-lite, see references/vega-lite-visual.md for more details.
  2. Data Grids: These are used to display tabular data in a structured format, allowing for sorting, filtering, and pagination. See references/data-grid-visual.md for more details.

Packages & Imports

The visual components are provided by three packages. Always use these package imports when creating visuals.

Package Primary exports Example import
@microsoft/fabric-visuals VegaVisual, types: VisualizationSpec, VegaLiteConfig, VegaVisualProps import { VegaVisual } from "@microsoft/fabric-visuals"
@microsoft/fabric-datagrid DataGrid, types: GridColumnDef, Row, CellValue, DataGridProps, DataGridTheme, SortConfig import { DataGrid } from "@microsoft/fabric-datagrid"
@microsoft/fabric-visuals-core isDataTable, convertDataTableToRows, design tokens import { isDataTable } from "@microsoft/fabric-visuals-core"

The DataTable type (used by both components) is defined in @microsoft/fabric-visuals-core and re-exported by the visual packages' type definitions.

Data Format

The chart and data grid components share a unified data prop of type DataTable (from @microsoft/fabric-visuals-core). This structured format carries column metadata (displayName, format, semanticType) that the components use for axis titles, grid headers, number formatting, and tooltips.

Using DataTable: Pass a DataTable via the data prop. The visual uses its column metadata for formatting, axis titles, and tooltips.

Static/inline data: For static data, transformed data, or plain arrays, put data: { values: [...] } directly in the Vega-Lite spec and omit the data prop.

Multiple tables in one visual: the data prop also accepts a Record<string, DataTable> for specs that need to reference more than one dataset by name. See references/multi-data-input.md for the syntax and caveats.

import { VegaVisual, useCssTheme } from "@microsoft/fabric-visuals";
import { DataGrid } from "@microsoft/fabric-datagrid";
import type { DataTable } from "@microsoft/fabric-visuals-core";

// useCssTheme() reads --color-* vars from the page and updates automatically
// when the theme changes (e.g. dark-mode toggle adds/removes the .dark class).
const theme = useCssTheme();

// Charts — pass a DataTable and Vega-Lite spec
<VegaVisual spec={vegaLiteSpec} data={dataTable} theme={theme} />

// Grids — displayName becomes column headers, format applies to cells
<DataGrid data={dataTable} theme={theme} />

// Static/inline data — no data prop needed
const inlineSpec = {
  data: { values: [{ x: 1, y: 2 }, { x: 3, y: 4 }] },
  mark: "point",
  encoding: { ... },
};

<VegaVisual spec={inlineSpec} theme={theme} />

For the DataTable schema and ColumnDef fields, see references/data-table.md.

Formatting & Theme

  • Formatting rules: Number formatting, color palettes, chart-specific encoding rules, highlighting guidelines, and a default theme. See references/formatting.md.

Custom visuals

Always use the above mentioned ways to create visual when possible. If the user's request doesn't allow creation using the above methods, ask the user if they are ok with using another library for creating the visual. If they are ok with it, use the library to create the visual. If they are not ok with it, then build that visual from scratch using HTML, CSS, and JS/TS. Make sure to ask the user for any specific requirements they have for the visual, such as colors, labels, etc.

Container Layout

  • DataGrid — the direct parent must apply overflow-auto so content remains scrollable when it exceeds the container bounds (many rows).

Interactivity

Both VegaVisual and DataGrid expose an onInteraction prop that emits structured, predicate-based events when the user clicks a data point or row.

Always use the onInteraction prop on VegaVisual and DataGrid to handle user interactions such as selections, cross-highlighting, and cross-filtering.

import type { InteractionEvent } from "@microsoft/fabric-visuals-core";

function handleInteraction(source: string, events: InteractionEvent[]) {
    for (const event of events) {
        if (event.action === "select") {
            // event.selections describes the clicked data as predicates
        } else if (event.action === "clear") {
            // user deselected (re-clicked same item or clicked empty space)
        }
    }
}

<VegaVisual spec={spec} data={dataTable} theme={theme}
    onInteraction={(events) => handleInteraction("salesChart", events)} />
<DataGrid data={dataTable} theme={theme}
    onInteraction={(events) => handleInteraction("detailTable", events)} />

Key concepts:

  • Clicking a different data point emits a new select (replaces the prior selection — no preceding clear).
  • Re-clicking the same item or background space in a vega-lite visual emits clear.
  • Predicates include all fields from the datum; consumers filter to the ones that are relevant to them.

Version History

  • 0979439 Current 2026-10-18 22:49

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