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openchart

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更新时间2026年7月17日 20:56

Generates OpenChart (https://github.com/tryopendata/openchart) chart, table, graph, sankey, tilemap, and geo map specs from data, and guides editorial design decisions. Use when creating visualizations, building charts, rendering data tables, generating VizSpec JSON, creating network graphs, building sankey/flow diagrams, building US state tile grid maps, building choropleth or symbol maps from TopoJSON, answering questions about OpenChart types and encoding rules, or making design decisions about chart type selection, color strategy, typography, annotations, and editorial framing. Also covers custom D3.js infographics for cases beyond declarative specs.

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Data Visualization with OpenChart

Note: SVG design capabilities (logos, icons, graphics) have moved to the opendesign plugin. Install with /plugin install opendesign@opendata-skills.

Source of truth: load the types first

Before authoring or modifying a spec, load the OpenChart type definitions. They are the canonical source for field shapes, enums, and defaults. This skill complements the types — it does not replace them. When this skill and the types disagree, the types win.

Try these locations in order; stop at the first one that resolves:

Installed package (most common): node_modules/@opendata-ai/openchart-core/dist/index.d.ts. The full chart, table, graph, sankey, tilemap, and map spec surface is rolled into this single bundled .d.ts.
Source repo (if you're working in the openchart monorepo): packages/core/src/types/spec.ts and packages/core/src/types/layout.ts. JSDoc comments here are richer than the bundled .d.ts.
Published CDN (no local install, network available): https://unpkg.com/@opendata-ai/openchart-core/dist/index.d.ts (redirects to the latest published version).
GitHub raw (if unpkg is unreachable, or you want the richer source JSDoc): https://raw.githubusercontent.com/tryopendata/openchart/main/packages/core/src/types/spec.ts. For version-exact types, pin to a release tag instead of main: https://raw.githubusercontent.com/tryopendata/openchart/core-v<version>/packages/core/src/types/spec.ts, matching <version> to the installed @opendata-ai/* package version. Note main may document unpublished surface.
Fallback: if none of the above are reachable (no filesystem, no network fetch), use the type sketches in this skill and flag the uncertainty in your response so the user knows you authored without canonical types.

The names worth grepping for once you have a types file open: ChartSpec, TableSpec, GraphSpec, SankeySpec, TileMapSpec, MapSpec (+ MapGeo, MapPointsLayer), MarkType (the 16-mark union), Encoding, EncodingChannel, MarkDef, Chrome, Metric, EndpointLabelsConfig, Annotation (union), TextAnnotation, RangeAnnotation, RefLineAnnotation, LegendConfig, LabelSpec, SeriesStyle, AnimationSpec, ThemeConfig, A11yConfig, SeriesSearchConfig, YouDrawItConfig.

Rendering via MCP

If you have access to the OpenData MCP openchart tool, use it to render specs interactively -- it handles rendering, theming, and responsive layout. Two ways to call it:

Quick chart: pass chartType (bar, line, area, point, arc, lollipop, circle, rect, tick) plus the field names (x, y, color). Good for the common x/y shapes.
Full control: pass a spec object (the OpenChart JSON described in this skill) -- required for marks the quick chartType list doesn't cover (range, waffle, calendar, parliament, beeswarm, text, rule) and for any encoding/chrome/annotation options.

Feed data with sql (the tool re-runs your previous query_sql -- preferred, don't copy rows) or inline data rows (keep under 1000). The tool's own description carries version-pinned links to the full schema for constrained generation.

When the openchart tool is not available, output the spec as JSON for the user to render with <Chart> / createChart() (see rendering reference).

Structured outputs (tool-use / constrained generation). OpenChart ships a published JSON Schema and a generated llms.txt, both derived from the spec types so they never drift:

JSON Schema for constraining an LLM tool call to a valid spec. Import from the core ./schema subpath (not the type barrel): @opendata-ai/openchart-core/schema is the full VizSpec union (usable directly as an Anthropic tool input_schema); @opendata-ai/openchart-core/schema/chart.schema.json is the chart-only subset covering all 16 marks; .../table.schema.json is the table subset. Files also live at packages/core/schema/*.schema.json and on unpkg/GitHub raw for fetch-only agents.
llms.txt at the repo root (https://raw.githubusercontent.com/tryopendata/openchart/main/llms.txt) is the compact narrative surface: install, core concept, the mark-encoding table, and validation notes. Prefer it as a quick primer when you can't load the full .d.ts.

Validate before rendering. validateSpec(spec) from @opendata-ai/openchart-engine returns { valid, errors, normalized }. Each error carries a machine-readable code, the offending path, and a repair-friendly suggestion. Field references are checked against the columns in the provided data, and a misspelled field name gets a Levenshtein-based Did you mean "..."? clause pointing at the nearest real column -- use that clause to auto-repair typos in a generate-validate loop.

What this skill carries that the types don't

The types tell you the shape of a valid spec. This skill carries the things types can't express:

Behavioral defaults that live in the normalizer/compiler, not in the type signature. (E.g. bar and area both default to stacked when colored; grouped/overlap behavior requires explicit stack: null.)
Cross-field interactions and truth tables. (E.g. how legend.show, endpointLabels, and the legacy end-of-line labels interact.)
Runtime semantics. (E.g. legend toggle recompiles, rebalances the y-axis, locks the color scale, hides per-series UI, refuses to hide the last visible series.)
Editorial judgment. (E.g. when to pick a bar vs a line, color strategy, annotation density, data-resolution budgets.)
Worked examples for common stories.
Failure modes and gotchas that you'd only learn after rendering and looking at the result.

If you find yourself restating a field shape this skill already documents, prefer the types — they're authoritative and won't drift.

Core concept: Write a VizSpec JSON object, render with <Chart> / <DataTable> / <Graph> / <Sankey> / <TileMap> / <GeoMap> (React/Vue/Svelte) or createChart() / createTable() / createGraph() / createSankey() / createTileMap() / createMap() (vanilla JS). The engine validates, compiles, and renders. Specs are plain JSON, no imperative drawing. See https://github.com/tryopendata/openchart for the rendering engine.

CSS is required. OpenChart's stylesheet must be loaded for proper rendering (chrome, tables, tooltips, brand watermark). Framework imports handle this automatically, but CDN/standalone HTML needs an explicit <link>:

<link rel="stylesheet" href="https://esm.sh/@opendata-ai/openchart-vanilla/styles.css">

See rendering reference for details.

Chart Selection Decision Tree

Single KPI / KPI row         -> spec.metrics: Metric[] (label+value+delta, rendered between subtitle and chart)
Temporal x-axis column?      -> 1 series: line | 2-5 series: line + color | 6+: filter to top 5
Categorical + numeric?       -> Ranked list: bar (horizontal) | Periodic (Q1, Jan): bar (vertical) | 2-6 composition: arc
Two numeric columns?         -> point (optional size/color for 3rd/4th dims)
Categorical + series + num?  -> stacked bar (use color for series)
Distribution/spread?         -> circle (strip plot) | many observations per group: beeswarm
Change between two values?   -> range (dumbbell / arrow / floating bar per category)
Part-to-whole as counts?     -> waffle ("x of 100" unit grid)
Election / legislature seats?-> parliament (hemicycle) | half-donut result: arc + startAngle/endAngle
Daily value over a year?     -> calendar (GitHub-style heatmap)
Nodes + edges / network?     -> graph (force/radial/hierarchical layout)
Flow between stages?         -> sankey (source/target/value)
US state-level data?         -> tilemap (state codes + values, equal-weight grid)
Real geography / shapes?     -> map (TopoJSON choropleth; counties, countries, or points over a basemap)
Tabular data overview?       -> table (with sparklines, heatmaps, bars)
Scroll-driven narrative?     -> chart story (base spec + patch steps, see references/story.md)
Default                      -> bar

Visualization Types

Each type has a detailed reference with full spec, encoding rules, and examples. Load the reference when you need the details.

Mark / Type	Best for	Data model	Reference
`mark: "line"`	Trends over time	x: temporal/ordinal, y: quantitative	references/line.md
`mark: "area"`	Trends with volume emphasis	x: temporal/ordinal, y: quantitative	references/area.md
`mark: "bar"`	Rankings (horizontal) or periodic/categorical (vertical)	Orientation inferred from encoding (see below)	references/bar.md
`mark: "arc"`	Part-to-whole (2-5 categories)	theta: quantitative, color: nominal/ordinal	references/pie-donut.md
`mark: "point"`	Correlation between two variables	x: quantitative, y: quantitative	references/scatter.md
`mark: "circle"`	Distribution, strip plots	x: quantitative, y: nominal/ordinal	references/dot.md
`mark: "text"`	Text labels positioned by x/y	x: any, y: any, text: nominal	-
`mark: "rule"`	Reference lines (horizontal or vertical)	x or y: quantitative/temporal	-
`mark: "tick"`	Tick marks for distributions	x: quantitative, y: nominal/ordinal	-
`mark: "rect"`	Rectangles for heatmaps	x: ordinal/nominal, y: ordinal/nominal, color: quantitative	-
`mark: "lollipop"`	Ranked categorical values (dot on a stem)	x: quantitative, y: nominal/ordinal	references/dot.md
`mark: "beeswarm"`	Distribution, one dot per observation	one axis quantitative, other optional nominal (lanes)	references/dot.md
`mark: "range"`	Change between two values (dumbbell / arrow / floating bar)	category + start + end (x/x2 or y/y2)	-
`mark: "waffle"`	Part-to-whole as counts ("x of 100")	color: nominal, theta: quantitative share	references/pie-donut.md
`mark: "calendar"`	Daily value over weeks/years (GitHub heatmap)	x: temporal (daily), color: quantitative	-
`mark: "parliament"`	Election / legislature seats (hemicycle)	color: nominal (party), theta: quantitative seats	-
`type: "table"`	Data tables with visual features	columns + data rows	references/table.md
`type: "graph"`	Networks, relationships, hierarchies	nodes + edges	references/graph.md
`type: "sankey"`	Flows between stages/processes	source + target + value	references/sankey.md
`type: "tilemap"`	US state-level data (equal-weight grid)	state codes + values	references/tilemap.md
`type: "map"`	Real geography: choropleth + symbol maps	TopoJSON + join key + color value; optional lat/lon points	references/map.md

Bar orientation: The engine infers orientation from encoding. x: nominal/ordinal + y: quantitative = vertical (column-style). x: quantitative + y: nominal/ordinal = horizontal bar. Override with mark: { type: "bar", orient: "horizontal" | "vertical" }.

Arc variants: mark: "arc" renders a pie chart by default. Add innerRadius > 0 to get a donut: mark: { type: "arc", innerRadius: 40 }. For an election-style half-donut, restrict the sweep with startAngle/endAngle in radians (mark: { type: "arc", innerRadius: 40, startAngle: -Math.PI/2, endAngle: Math.PI/2 }); the engine resizes a partial sweep to fill the chart area so a half-donut isn't drawn at half size.

New-mark behavior the types don't tell you:

range needs the second value channel: x + x2 (horizontal, the common editorial form with y as the category) or y + y2 (vertical). style picks the form: "dumbbell" (default, muted start dot + accent end dot + connector), "arrow" (arrowhead at the x2/y2 end, strongest "change over time" read), or "bar" (plain floating range bar). colorByDirection: true colors increases with the theme's positive color and decreases with negative; a field-based encoding.color wins over it. Use this mark for dumbbell/change plots rather than faking one with two overlaid point series.
waffle takes color (the category) and a quantitative share via theta (the same part-to-whole channel arc uses; y is still accepted as a deprecated alias). units (default 100) sets total cells, columns (default 10) the grid width. Shares normalize to units via largest-remainder rounding so cells always sum exactly; a small nonzero share can round to 0 cells (there's no minimum-one-cell floor), but it still appears in the legend.
calendar takes x (temporal, one row per day) and color (quantitative per-day value). Multi-year data stacks one band per year sharing a single color scale. Date math is UTC, so "2024-01-15" parses as UTC midnight. Days with no data render as empty achromatic cells, distinct from the scale minimum. weekStart ("monday" default / "sunday") sets the top row; cellRadius rounds the cells.
parliament takes color (party) and seat count via theta (y is still accepted as a deprecated alias). Only shape: "hemicycle" ships (concentric semicircular arcs). Parties fill left-to-right in data order, so sort your rows by political spectrum yourself. majorityLine (default true) draws the threshold line and "N to win" label; seatRadius defaults to "auto".
beeswarm takes one quantitative positional channel (the value axis) plus an optional nominal channel for grouped lanes; size scales dot area. The cross axis is pure pixel-space with no scale, so tall stacks can overflow a short container -- cap the size range or give it vertical room.
lollipop is a semantic alias for the dot/stem renderer (x quantitative, y category): a dot on a stem from the baseline. Negative values extend the stem left of the baseline.

Collapsed mark types: These mark aliases no longer exist as separate values. Use the canonical marks instead:

Old mark	Use instead
`"column"`	`"bar"` (engine infers vertical from encoding)
`"pie"`	`"arc"`
`"donut"`	`{ type: "arc", innerRadius: 40 }`
`"scatter"`	`"point"`
`"dot"`	`"circle"`

Reference Routing

Always load when generating a new chart spec: encoding-channels.md, format-strings.md, color-strategy.md

When the task involves...	Load
Dual-axis charts, independent y-scales	See Layer Composition section above -- no extra reference needed
Adding annotations, callouts, reference lines	annotations.md
onEdit callback, selection, inline editing	editing.md
Responsive layout, mobile, breakpoint overrides	responsive.md
Theme customization (colors, fonts, spacing)	theme.md
Data transforms (window, filter, aggregate, etc.)	data-transforms.md
Rendering setup (React, Vue, Svelte, vanilla)	rendering.md
Choosing chart type for a story	chart-selection.md
Writing titles, subtitles, annotation text	editorial-writing.md
Font sizing, type hierarchy	typography.md
Per-series visual overrides (dashed lines, opacity)	series-styles.md
Gradient fills (linear, radial, per-mark)	gradients.md
Entrance animations, easing, stagger, reduced motion	animation.md
Sankey diagram (flows between stages)	sankey.md
US state tile grid map	tilemap.md
Geo map: choropleth, symbol/point layer, projections, TopoJSON joins	map.md
Scroll-driven chart story (scrollytelling)	story.md
Final design quality check	design-review.md
Checking rendered output for defects	visual-qa.md

Common reference bundles:

New chart: encoding-channels + format-strings + color-strategy + editorial-writing + (mark-specific ref)
Design polish: design-review + visual-qa + editorial-writing
D3 infographic: d3-core-patterns + infographic-design + (topic-specific D3 ref)

Spec discriminant

Charts use mark (16 marks: "bar", "line", "area", "point", "circle", "arc", "text", "rule", "tick", "rect", "lollipop", "beeswarm", "range", "waffle", "calendar", "parliament").
Tables, graphs, sankey, tilemap, geo maps use type ("table" | "graph" | "sankey" | "tilemap" | "map").

For the full top-level shape — every optional field, exact enum values, defaults — load ChartSpec, TableSpec, GraphSpec, SankeySpec, TileMapSpec, MapSpec from index.d.ts (see "Source of truth" above).

Behavior worth knowing that the types don't tell you:

animation is off by default. Set true for sensible per-mark entrance defaults; pass an AnimationConfig for per-phase control. See animation.md.
crosshair is off by default and only renders on line/area charts.
endpointLabels is auto-on for ≥2-series line/area and auto-suppresses the traditional legend in that case. See the "Endpoint Labels" section below for the full suppression truth table.
hiddenSeries on the spec hides series on first render. The vanilla adapter also maintains a separate runtime hidden set populated by legend clicks; that triggers full engine recompile (y-axis rebalance, locked color scale, per-series UI hide). See "Legend Toggle (Runtime)" below.
display: 'sparkline' strips chrome, axes, legend, watermark, animation, and crosshair for inline KPI-card use. Explicit per-field overrides still win (set chrome.title and you'll still get a title in sparkline mode).
seriesSearch (boolean | { placeholder }) renders a typeahead "find your country" input over a categorical color encoding; selecting values highlights them (multi-select chips). Mutually exclusive with edit mode (search wins).
youDrawIt ({ from, prompt?, revealLabel?, comparisonLine? }) is the NYT "draw your guess before the reveal" format. Line marks only, single-series only; mutually exclusive with edit mode and seriesSearch. The vanilla instance exposes resetDrawing() / revealDrawing() and an onReveal(guess) callback.
mark.fillPattern: 'auto' layers a per-series SVG pattern (hatch, dots, crosshatch) over each fill so filled marks (bar/area/arc) stay distinguishable without color vision; 'none' (default) is solid fills.
Accessibility is automatic: openchart generates alt text, ARIA labels, and a hidden screen-reader data table. Override the alt text with top-level description (Vega-Lite sugar) or a11y.description (a11y.description wins); set a11y.hidden: true to aria-hidden a purely decorative chart. The engine also emits console warnings when adjacent series or text fall below WCAG contrast, naming the nearest passing color.

Chrome elements (chrome.eyebrow / title / subtitle / source / byline / footer / brand): each takes string | ChromeText. The eyebrow is a tracked, accent-tinted kicker above the title. The brand is a right-anchored block on the footer row paired with a small accent dot — setting it suppresses the default tryOpenData.ai watermark. All chrome text supports \n for explicit line breaks and auto-wraps at the container width. Exact field shape: see Chrome and ChromeText in index.d.ts.

KPI metric row (charts only): metrics: Metric[] at the top level (not inside chrome) renders a horizontal row of label+value cells between the subtitle and the chart area. Each cell can carry a delta and a secondary value. Auto-stripped in sparkline mode and at narrow/short containers, or when value text would overflow its cell. Exact field shape: see Metric in index.d.ts.

Mark (Charts Only)

mark is either a string (one of the 16 marks: "bar", "line", "area", "point", "circle", "arc", "text", "rule", "tick", "rect", "lollipop", "beeswarm", "range", "waffle", "calendar", "parliament") or an object — see MarkDef in index.d.ts for the full field set (type, point, interpolate, orient, innerRadius, startAngle, endAngle, fill, stroke, strokeWidth, opacity, fillPattern, plus per-mark fields like style/colorByDirection for range, units/columns for waffle, weekStart for calendar, shape/seatRadius/majorityLine for parliament, etc.).

Behavior the types don't tell you:

Bar orientation is inferred from encoding types. x: nominal/ordinal/temporal + y: quantitative = vertical column. x: quantitative + y: nominal/ordinal = horizontal bar. Override with mark: { type: "bar", orient: "horizontal" | "vertical" } only when the inference is wrong.
mark: "arc" is a pie by default. Pass innerRadius > 0 to get a donut.
mark.fill accepts a GradientDef for linear or radial gradients. Gradients can also appear as conditional color values in encoding.color. See gradients.md.
Default entrance animation depends on mark type when animation: true. Bars clip-reveal from the baseline; lines draw progressively; areas draw + fade; arcs scale from center; points pop in with scale + fade; text/rules/ticks fade in. See animation.md for per-mark defaults and per-phase overrides.

Collapsed mark aliases (don't use these):

Old mark	Use instead
`"column"`	`"bar"` (engine infers vertical from encoding)
`"pie"`	`"arc"`
`"donut"`	`{ type: "arc", innerRadius: 40 }`
`"scatter"`	`"point"`
`"dot"`	`"circle"`

Examples:

{ "mark": { "type": "line", "point": true, "interpolate": "monotone" } }
{ "mark": { "type": "arc", "innerRadius": 40 } }
{ "mark": { "type": "bar", "fill": { "gradient": "linear", "stops": [{"offset": 0, "color": "#1b7fa3"}, {"offset": 1, "color": "#1b7fa3", "opacity": 0.4}] } } }

Encoding Channels (Charts Only)

Charts map data to visuals via encoding channels: x, y, color, size, detail, key, x2, y2, opacity, strokeDash, angle, text, tooltip, theta, facet. Each channel is an EncodingChannel (field, type, aggregate, axis, scale, bin, timeUnit, sort, format, title, stack, condition, value). For the full shape and enum values: load Encoding and EncodingChannel from index.d.ts.

Behavior the types don't tell you:

field + type is the minimum for any channel. type must be one of "quantitative" | "temporal" | "nominal" | "ordinal" — picking the wrong one is the most common spec authoring bug (see Spec Anti-Patterns below).
axis.format is d3-format with a literal-suffix extension (e.g. ".1f%"). The literal suffix is OpenChart's add-on; native d3 doesn't support it. See format-strings.md and the Format Strings section below for the percent-form pitfall.
scale.nice: true is the default for quantitative and temporal scales — it rounds the domain outward to clean tick values. On temporal scales this can shift the domain by years; set nice: false when you need precise control.
stack defaults to stacked ("zero") when colored for both bar and area; line = n/a. Set stack: null for grouped/overlap behavior. See the per-mark default table in encoding-channels.md.
See encoding-channels.md for conditional encoding examples and the full per-channel guide.

Data Transforms (Charts Only)

Apply transforms (filter, bin, calculate, timeUnit, aggregate, fold, window) to data before encoding. Transforms run in array order. Filters support data-relative time references for temporal fields. See data transforms reference.

Layer Composition (Charts Only)

Overlay multiple marks in a single chart using layer. Each layer is a standalone spec with its own mark, data, and encoding.

{
  "layer": [
    { "mark": "bar", "data": [...], "encoding": { ... } },
    { "mark": "line", "data": [...], "encoding": { ... } }
  ]
}

Layers share the same coordinate space. Use this for combo charts (bar + line), adding reference lines, or overlaying annotations.

Dual-Axis Charts (Independent Y-Scales)

When two series have incompatible value ranges (e.g., revenue in millions vs. headcount in thousands), use resolve: { scale: { y: "independent" } } on the layer spec. Layer 0 gets the left y-axis; layer 1 gets the right y-axis. Both share the x-axis.

{
  "resolve": { "scale": { "y": "independent" } },
  "layer": [
    {
      "mark": { "type": "bar", "opacity": 0.85 },
      "data": [
        { "year": "2022", "revenue": 8000000 },
        { "year": "2023", "revenue": -5000000 }
      ],
      "encoding": {
        "x": { "field": "year", "type": "ordinal" },
        "y": {
          "field": "revenue",
          "type": "quantitative",
          "axis": { "title": "Net Revenue ($)", "format": "~s", "labelColor": "#3E7CB1" }
        }
      },
      "labels": { "density": "none" }
    },
    {
      "mark": { "type": "line", "stroke": "#E07B39", "strokeWidth": 2.5, "point": true, "interpolate": "monotone" },
      "data": [
        { "year": "2022", "enrollment": 52800 },
        { "year": "2023", "enrollment": 51600 }
      ],
      "encoding": {
        "x": { "field": "year", "type": "ordinal" },
        "y": {
          "field": "enrollment",
          "type": "quantitative",
          "axis": { "title": "Enrollment", "format": "~s", "labelColor": "#E07B39" }
        }
      },
      "labels": { "density": "none" }
    }
  ]
}

Dual-axis rules:

Max 2 layers -- there are only left and right y-axes.
Both layers must have compatible x-field types (both ordinal, both temporal, etc.).
Use axis.labelColor on each layer's y-encoding to color the axis labels to match the series -- this is the standard dual-axis pattern (Datawrapper, Highcharts style).
Use labels: { density: "none" } on both layers to avoid label collisions between the two series.
The engine zero-aligns both y-scales so zero sits at the same pixel height on both axes. Annotations target the primary (left) y-scale.
Works with any combination: bar + line, bar + area, area + line.

Legend Configuration (Charts Only)

legend accepts position, show, columns, symbolLimit, maxRows, offset, exclude. Full shape: LegendConfig in index.d.ts.

Behavior: Position is responsive by default — the engine picks top / right / bottom / bottom-right / inline based on container width. Set position to override. Use show: false when the legend is redundant (e.g. bar charts where the y-axis already labels each category). For multi-series line/area, leaving show unset triggers auto-suppression in favor of the endpoint chip column — see the truth table below.

Endpoint Labels (Multi-Series Line/Area)

For multi-series line/area charts, the engine renders a column of chip+swatch labels at the trailing edge of each series (rounded pill with a colored bar swatch + label + last value). Auto-on for ≥2 series; off for single-series and non-line/area.

endpointLabels accepts boolean | EndpointLabelsConfig (show, valueField, format, width, showMarker, showLeader, markerStyle). Full shape: EndpointLabelsConfig in index.d.ts.

Suppression truth table (≥2-series line/area). The traditional legend, the endpoint column, and the legacy end-of-line labels are three knobs that interact. The implementation lives in packages/engine/src/legend/suppression.ts and is the single source of truth — if this table ever drifts, the engine wins.

`legend.show`	`endpointLabels`	Traditional legend	Endpoint column	End-of-line labels
unset	unset	hidden (auto-suppressed)	shown (default)	hidden
`true`	unset	shown	shown	hidden
unset	`false`	shown (auto-suppress revoked)	hidden	hidden
`false`	`false`	hidden	hidden	shown (last-resort)
`true`	`false`	shown	hidden	hidden
`false`	`true`	hidden	shown	hidden
`true`	`true`	shown	shown	hidden

Single-series charts: column hidden by default (nothing to identify).

Common patterns:

Default multi-series: leave both unset -- you get the endpoint column, no traditional legend.
"I want a top legend instead": legend: { position: 'top' }, endpointLabels: false.
"Both legend and endpoint column": legend: { show: true } (endpointLabels stays auto-on).

Legend Toggle (Runtime)

Clicking a legend entry hides/shows the corresponding series at runtime. This goes through engine recompile (not CSS hide), so:

The y-axis rebalances to the remaining visible series.
The color scale stays locked -- remaining lines keep their original palette colors (engine injects a stable scale.domain from the unfiltered data).
Per-series UI hides with the line: endpoint chip, leader, dot annotation, and any text annotation anchored to that series.
The last visible series can't be hidden (the toggle is a no-op).
Range annotations and reference lines pass through unchanged (they anchor to constant axis values, not series).

Pass onLegendToggle to observe these clicks; you don't need to wire up hiddenSeries yourself for default behavior. Use hiddenSeries on the spec to start with specific series hidden on first render.

Label Density (Charts Only)

labels accepts density, format, prefix (full shape: LabelSpec in index.d.ts). The choice that actually drives the chart is density:

`density`	Behavior	Use when
`"auto"` (default)	Show labels with collision detection	Most charts
`"all"`	Show every label, no collision detection	Few data points, precise values matter
`"endpoints"`	First and last per series only (legacy end-of-line labels on line/area)	Single-series line emphasizing start/end
`"none"`	No labels (tooltips + legend only)	Dense data, clean look

For multi-series line/area, prefer endpointLabels (the chip+swatch column) over density: "endpoints" (the legacy fallback). The chip column wraps long names and resolves collisions; the legacy labels reserve a large right margin for long series names.

Format Strings

Both axis.format and labels.format accept d3-format strings plus a literal suffix extension. See format strings reference for the full table.

Format	Output example	Use case
`".1f%"`	`12.5%`	Percentage (data already in %, not 0-1)
`"$,.0f"`	`$1,234`	Currency with commas
`"~s"`	`10k`, `1.5M`	SI suffix for large numbers
`",.0f"`	`132,979`	Comma-separated, no decimals
`".1%"`	`12.5%` (from 0.125)	d3 native percent (multiplies by 100)

Critical: When data is already in percentage form (12.5 meaning 12.5%), use ".1f%" not ".1%". The d3 % type multiplies by 100, so 12.5 becomes 1,250.0%.

Per-Series Styling (Charts Only)

Use seriesStyles: Record<string, SeriesStyle> to override visuals for individual series, keyed by the color-field value. Use this for "highlight one series, dim the rest" patterns or for a dashed reference series alongside primary data. Field shape: SeriesStyle in index.d.ts. Editorial guidance + examples: series-styles.md.

Data Resolution

Keep data arrays under 150 rows per series. More data doesn't make a better chart - it makes a slower, harder-to-read one. Reduce resolution before building the spec, not after.

Time span	Resolution	Typical rows	Example
< 1 year	Daily or weekly	50-200	Stock price last 6 months
1-5 years	Monthly	12-60	Unemployment rate 2020-2025
5-25 years	Quarterly or annual	20-100	GDP since 2000
25-100+ years	Annual or decade	25-100	CO2 emissions since 1900

How to reduce: When querying APIs, aggregate before passing data to the spec:

Use group_by=year with aggregate=avg(value) to go from monthly to annual
Sample every Nth row for evenly-spaced data
Filter to the time range that matters (don't chart 75 years when the story is about the last 10)

Multi-series charts are multiplicative. A 3-series line chart with 300 points per series = 900 data rows. Reduce each series to ~50-80 points for a clean result. For the same 25-year span, annual data (25 points x 3 series = 75 rows) reads better than monthly (300 x 3 = 900 rows).

Why this matters beyond readability: Large data arrays inflate the spec JSON, slow rendering, and generate massive accessibility tables in the DOM. A 900-row chart produces a ~19,000px tall screen-reader table that can break page layout if styles don't load correctly.

First Draft Checklist

Run these checks before outputting a spec. These catch the issues that most often require iteration after rendering.

Check	What to verify
Data resolution is appropriate	Check total rows in the data array. Over 150 per series? Aggregate to a coarser time grain or sample. A 25-year time series should use annual or quarterly data, not monthly. See Data Resolution table.
Color encodes the story	If one variable drives the narrative, color should reinforce it. Use the decision table in color-strategy.md to pick the right strategy and `theme.colors` array. Don't leave a scatter plot monochrome when a gradient would make the pattern obvious.
Bar stacking is intentional	If using `color` encoding on a bar chart, verify stacking mode. Default is stacked (`stack: "zero"`), which adds values together visually. For side-by-side comparison bars (e.g., 2018 vs 2022), set `stack: null` on the quantitative encoding. Stacked bars sum values visually, so a comparison chart will show bars extending to the sum of both values.
Area stacking is intentional	Area charts default to stacked (`stack: "zero"`) when colored, same as bars. For side-by-side/overlap comparison, set `stack: null` on the y-channel (or `"normalize"` for percentage stacking, `"center"` for streamgraph).
Y-domain fits the data	Domain ceiling should be ~5-10% above the highest data value. `[0, 55]` for data peaking at 48.8 wastes space. Use `[0, 52]`. For bar/column charts with narrow data ranges (e.g., values between 200 and 280), don't default the floor to 0 - it makes variations invisible. Set the domain floor near the minimum value. Exception: charts where zero is a meaningful baseline (percent change from 0, counts).
Annotations clear of data AND each other	The engine auto-resolves annotation-to-annotation collisions, but start with good separation for cleaner results. Prefer 0-2 text annotations; use reflines for additional callouts. On scatter/bubble, use 40-100px offsets into empty quadrants with connectors. When using 2+ text annotations, verify with `playwright-cli`.
Subtitle is intentional about wrapping	Unintentional wrapping with orphaned fragments looks broken. Abbreviate, restructure, or use `\n` for explicit line breaks. Use shorthand keys in the subtitle (e.g., `"LI = low-income"`) rather than spelling everything out.
Endpoint labels won't eat the chart	The default chip+swatch column (`endpointLabels`) wraps long names at `width` (default 96px) and resolves collisions, so it handles long series names well. Only the legacy fallback (`labels: { density: "endpoints" }` with no `endpointLabels` and no top legend) reserves a huge right margin for long names — if you've forced that path, either abbreviate series names or switch to `legend: { position: "top" }, endpointLabels: false`.
Axis ticks show units	Percentages should show `10%` not `10`. Use `format: ".0f%"` when data is already in percent form (e.g., 10 meaning 10%). Use `format: ".0%"` only when data is in decimal form (0.10 meaning 10%). Large numbers should use SI suffixes: `format: "~s"` turns 10000 into `10k` and 1000000 into `1M`. For currency: `format: "$~s"` gives `$10k`, `$1M`. See the Format Strings table above.
Consistent color palette across related charts	If multiple charts in the same article cover the same dimension (e.g., poverty), use the same color mapping (blue = low, red = high) so the reader builds a mental model.

Spec Anti-Patterns

Mistake	Fix
Using `nominal` for numeric field	Use `quantitative` for numbers, `temporal` for dates
Using `ordinal` for temporal data	Use `temporal`; ordinal is for ordered categories
Too many data points (>150 per series)	Aggregate or sample before building the spec. See Data Resolution table above. Monthly data over 25 years = 300 rows per series, use annual instead
Forgetting encoding.color for multi-series	Line/bar with groups needs `color` channel
Bar chart for time series	Use line for temporal data; bar with vertical orientation for periodic categories
Using chart mark for network data	Use `type: "graph"` with nodes + edges
Using chart mark for US state data	Use `type: "tilemap"` with state code keys
Hand-rolling D3 for choropleths or symbol maps	Use `type: "map"` with TopoJSON from us-atlas/world-atlas. See map.md
Not specifying axis format for currency/pct	Add `axis: { format: "$,.0f" }` or `".1f%"`
Using `".1%"` when data is already in percent form	`".1%"` multiplies by 100 (d3 convention). If data is `12.5` meaning 12.5%, use `".1f%"` (literal suffix)
Axis format and label format inconsistent	Set both `axis.format` and `labels.format` to the same pattern so ticks and data labels match
Using `darkMode: "auto"` in class-based dark mode apps	`"auto"` checks `prefers-color-scheme` only. For class-based toggles (Astro, Next.js), observe DOM and map to `"force"`/`"off"`. See rendering
Temporal scale with `nice: true` (default) creating dead space	`nice` rounds the domain outward (e.g., `2010-01` becomes `2008`). Set `scale: { domain: ["2010-01", "2026-01"], nice: false }` for precise control
Using `type` instead of `mark` for charts	Charts use `mark: "line"` (not `type: "line"`). Only tables, graphs, sankey, tilemap, and geo maps use `type`.

For design anti-patterns (titles, color, annotations), see design review.

Known Gotchas

Rendering and component behaviors that aren't obvious from the spec alone.

Gotcha	Behavior	Fix
Refline labels only support top/bottom	`labelAnchor` on refline annotations only accepts `"top"` or `"bottom"`. Left/right values are accepted in the type but have no visible effect on reflines (they do work on range annotations).	Set `label: ""` on the refline and add a separate `type: "text"` annotation positioned where you want a side label.
Endpoint chip labels wrap by width, not `\n`	The chip+swatch column wraps long series names at `endpointLabels.width` (default 96px). `\n` in the series name does not create a hard break.	Either shorten the series name in the data, or raise `width` if you have horizontal room.
Area defaults to stacked, not overlap	Multi-series area charts stack from a zero baseline by default when colored, same as bars. Setting `color` without `stack: null` on the y-channel produces a stacked composition, not overlapping semi-transparent fills.	For overlap/side-by-side, opt out with `encoding: { y: { ..., stack: null } }`.
`connector: 'drop-line'` only flips against the chart edge	The drop-line connector renders a vertical line through the data point's x and lays the label beside it. The auto-flip only checks against the chart area edge -- it does not avoid neighboring marks or other annotations.	Place the annotation away from cluttered regions; if collisions persist, switch to `connector: 'curve'` with a manual `offset`.
DataTable CSS overrides unreliable	Custom CSS targeting `.oc-table-wrapper td` may not apply due to CSS specificity.	Use the DataTable `style` prop for inline overrides: `<DataTable style={{ paddingLeft: 10 }} spec={...} />`.
Scatter plots auto-set `zero: false`	Unlike other chart types, scatter/point marks automatically set `scale.zero: false` on both axes if not explicitly configured. This means scatter domains fit tightly to data.	To include zero, explicitly set `scale: { zero: true }` on the relevant axis. Be aware that scatter and bar/line charts handle zero differently by default.
Constant colors require `mark.fill`, not encoding	`encoding.color: { value: "#hex" }` will error. The color encoding channel requires a `field` that maps to data.	Use `mark: { type: "bar", fill: "#1b7fa3" }` for constant colors across all marks.
Default gradient direction is top-to-bottom	A gradient with no explicit `x1/y1/x2/y2` defaults to vertical (top-to-bottom). On horizontal bars, the engine auto-orients this to left-to-right. On other marks, set coordinates explicitly.	For left-to-right: `x1:0, y1:0, x2:1, y2:0`. For top-to-bottom (default): omit coordinates or use `x1:0, y1:0, x2:0, y2:1`.
Layer scale mismatch	Second layer renders at wrong positions when layers have different value ranges.	For independent y-scales (e.g., revenue + enrollment), use `resolve: { scale: { y: "independent" } }` on the layer spec -- this renders both series correctly with left and right y-axes. For simple overlays where both series share the same scale, set an explicit `scale.domain` on both layers. Prefer `annotations` with `refline` over a full layer when you just need to add a threshold line.

Custom D3.js Infographics

When a visualization goes beyond what declarative specs can handle (creative metaphors, unusual layouts, treemaps, generative art), fall back to raw D3.js + SVG. Note: sankey, tilemap, and geo maps (choropleth + symbol) are first-class types with their own spec formats (see references/sankey.md, references/tilemap.md, and references/map.md), and scrollytelling is now first-class too -- use the chart story API (base spec + patch steps) instead of hand-rolling D3 scroll effects (see references/story.md). Use the D3 reference only for heavily customized layouts. These references cover D3 implementation patterns:

Topic	Reference
D3 selections, scales, axes, margin convention	references/d3/d3-core-patterns.md
Tufte principles, storytelling, publication design	references/d3/infographic-design.md
Path morphing, generative art, creative coding	references/d3/advanced-techniques.md
D3 transitions, scroll effects, easing, timing	references/d3/animation-transitions.md
Treemap, sunburst, sankey diagrams	references/d3/chart-hierarchy.md
D3 color APIs, programmatic palette generation, contrast checking	references/d3/color-palettes.md
SVG text wrapping, collision detection, leader lines, ARIA	references/d3/typography-labels.md
viewBox, ResizeObserver, responsive SVG patterns	references/d3/responsive-svg.md

name

openchart

description

Data Visualization with OpenChart

Note: SVG design capabilities (logos, icons, graphics) have moved to the opendesign plugin. Install with /plugin install opendesign@opendata-skills.

Source of truth: load the types first

Try these locations in order; stop at the first one that resolves:

Installed package (most common): node_modules/@opendata-ai/openchart-core/dist/index.d.ts. The full chart, table, graph, sankey, tilemap, and map spec surface is rolled into this single bundled .d.ts.
Source repo (if you're working in the openchart monorepo): packages/core/src/types/spec.ts and packages/core/src/types/layout.ts. JSDoc comments here are richer than the bundled .d.ts.
Published CDN (no local install, network available): https://unpkg.com/@opendata-ai/openchart-core/dist/index.d.ts (redirects to the latest published version).
GitHub raw (if unpkg is unreachable, or you want the richer source JSDoc): https://raw.githubusercontent.com/tryopendata/openchart/main/packages/core/src/types/spec.ts. For version-exact types, pin to a release tag instead of main: https://raw.githubusercontent.com/tryopendata/openchart/core-v<version>/packages/core/src/types/spec.ts, matching <version> to the installed @opendata-ai/* package version. Note main may document unpublished surface.
Fallback: if none of the above are reachable (no filesystem, no network fetch), use the type sketches in this skill and flag the uncertainty in your response so the user knows you authored without canonical types.

Rendering via MCP

If you have access to the OpenData MCP openchart tool, use it to render specs interactively -- it handles rendering, theming, and responsive layout. Two ways to call it:

Quick chart: pass chartType (bar, line, area, point, arc, lollipop, circle, rect, tick) plus the field names (x, y, color). Good for the common x/y shapes.
Full control: pass a spec object (the OpenChart JSON described in this skill) -- required for marks the quick chartType list doesn't cover (range, waffle, calendar, parliament, beeswarm, text, rule) and for any encoding/chrome/annotation options.

When the openchart tool is not available, output the spec as JSON for the user to render with <Chart> / createChart() (see rendering reference).

Structured outputs (tool-use / constrained generation). OpenChart ships a published JSON Schema and a generated llms.txt, both derived from the spec types so they never drift:

JSON Schema for constraining an LLM tool call to a valid spec. Import from the core ./schema subpath (not the type barrel): @opendata-ai/openchart-core/schema is the full VizSpec union (usable directly as an Anthropic tool input_schema); @opendata-ai/openchart-core/schema/chart.schema.json is the chart-only subset covering all 16 marks; .../table.schema.json is the table subset. Files also live at packages/core/schema/*.schema.json and on unpkg/GitHub raw for fetch-only agents.
llms.txt at the repo root (https://raw.githubusercontent.com/tryopendata/openchart/main/llms.txt) is the compact narrative surface: install, core concept, the mark-encoding table, and validation notes. Prefer it as a quick primer when you can't load the full .d.ts.

What this skill carries that the types don't

The types tell you the shape of a valid spec. This skill carries the things types can't express:

Behavioral defaults that live in the normalizer/compiler, not in the type signature. (E.g. bar and area both default to stacked when colored; grouped/overlap behavior requires explicit stack: null.)
Cross-field interactions and truth tables. (E.g. how legend.show, endpointLabels, and the legacy end-of-line labels interact.)
Runtime semantics. (E.g. legend toggle recompiles, rebalances the y-axis, locks the color scale, hides per-series UI, refuses to hide the last visible series.)
Editorial judgment. (E.g. when to pick a bar vs a line, color strategy, annotation density, data-resolution budgets.)
Worked examples for common stories.
Failure modes and gotchas that you'd only learn after rendering and looking at the result.

If you find yourself restating a field shape this skill already documents, prefer the types — they're authoritative and won't drift.

<link rel="stylesheet" href="https://esm.sh/@opendata-ai/openchart-vanilla/styles.css">

See rendering reference for details.

Chart Selection Decision Tree

Single KPI / KPI row         -> spec.metrics: Metric[] (label+value+delta, rendered between subtitle and chart)
Temporal x-axis column?      -> 1 series: line | 2-5 series: line + color | 6+: filter to top 5
Categorical + numeric?       -> Ranked list: bar (horizontal) | Periodic (Q1, Jan): bar (vertical) | 2-6 composition: arc
Two numeric columns?         -> point (optional size/color for 3rd/4th dims)
Categorical + series + num?  -> stacked bar (use color for series)
Distribution/spread?         -> circle (strip plot) | many observations per group: beeswarm
Change between two values?   -> range (dumbbell / arrow / floating bar per category)
Part-to-whole as counts?     -> waffle ("x of 100" unit grid)
Election / legislature seats?-> parliament (hemicycle) | half-donut result: arc + startAngle/endAngle
Daily value over a year?     -> calendar (GitHub-style heatmap)
Nodes + edges / network?     -> graph (force/radial/hierarchical layout)
Flow between stages?         -> sankey (source/target/value)
US state-level data?         -> tilemap (state codes + values, equal-weight grid)
Real geography / shapes?     -> map (TopoJSON choropleth; counties, countries, or points over a basemap)
Tabular data overview?       -> table (with sparklines, heatmaps, bars)
Scroll-driven narrative?     -> chart story (base spec + patch steps, see references/story.md)
Default                      -> bar

Visualization Types

Each type has a detailed reference with full spec, encoding rules, and examples. Load the reference when you need the details.

Mark / Type	Best for	Data model	Reference
`mark: "line"`	Trends over time	x: temporal/ordinal, y: quantitative	references/line.md
`mark: "area"`	Trends with volume emphasis	x: temporal/ordinal, y: quantitative	references/area.md
`mark: "bar"`	Rankings (horizontal) or periodic/categorical (vertical)	Orientation inferred from encoding (see below)	references/bar.md
`mark: "arc"`	Part-to-whole (2-5 categories)	theta: quantitative, color: nominal/ordinal	references/pie-donut.md
`mark: "point"`	Correlation between two variables	x: quantitative, y: quantitative	references/scatter.md
`mark: "circle"`	Distribution, strip plots	x: quantitative, y: nominal/ordinal	references/dot.md
`mark: "text"`	Text labels positioned by x/y	x: any, y: any, text: nominal	-
`mark: "rule"`	Reference lines (horizontal or vertical)	x or y: quantitative/temporal	-
`mark: "tick"`	Tick marks for distributions	x: quantitative, y: nominal/ordinal	-
`mark: "rect"`	Rectangles for heatmaps	x: ordinal/nominal, y: ordinal/nominal, color: quantitative	-
`mark: "lollipop"`	Ranked categorical values (dot on a stem)	x: quantitative, y: nominal/ordinal	references/dot.md
`mark: "beeswarm"`	Distribution, one dot per observation	one axis quantitative, other optional nominal (lanes)	references/dot.md
`mark: "range"`	Change between two values (dumbbell / arrow / floating bar)	category + start + end (x/x2 or y/y2)	-
`mark: "waffle"`	Part-to-whole as counts ("x of 100")	color: nominal, theta: quantitative share	references/pie-donut.md
`mark: "calendar"`	Daily value over weeks/years (GitHub heatmap)	x: temporal (daily), color: quantitative	-
`mark: "parliament"`	Election / legislature seats (hemicycle)	color: nominal (party), theta: quantitative seats	-
`type: "table"`	Data tables with visual features	columns + data rows	references/table.md
`type: "graph"`	Networks, relationships, hierarchies	nodes + edges	references/graph.md
`type: "sankey"`	Flows between stages/processes	source + target + value	references/sankey.md
`type: "tilemap"`	US state-level data (equal-weight grid)	state codes + values	references/tilemap.md
`type: "map"`	Real geography: choropleth + symbol maps	TopoJSON + join key + color value; optional lat/lon points	references/map.md

New-mark behavior the types don't tell you:

range needs the second value channel: x + x2 (horizontal, the common editorial form with y as the category) or y + y2 (vertical). style picks the form: "dumbbell" (default, muted start dot + accent end dot + connector), "arrow" (arrowhead at the x2/y2 end, strongest "change over time" read), or "bar" (plain floating range bar). colorByDirection: true colors increases with the theme's positive color and decreases with negative; a field-based encoding.color wins over it. Use this mark for dumbbell/change plots rather than faking one with two overlaid point series.
waffle takes color (the category) and a quantitative share via theta (the same part-to-whole channel arc uses; y is still accepted as a deprecated alias). units (default 100) sets total cells, columns (default 10) the grid width. Shares normalize to units via largest-remainder rounding so cells always sum exactly; a small nonzero share can round to 0 cells (there's no minimum-one-cell floor), but it still appears in the legend.
calendar takes x (temporal, one row per day) and color (quantitative per-day value). Multi-year data stacks one band per year sharing a single color scale. Date math is UTC, so "2024-01-15" parses as UTC midnight. Days with no data render as empty achromatic cells, distinct from the scale minimum. weekStart ("monday" default / "sunday") sets the top row; cellRadius rounds the cells.
parliament takes color (party) and seat count via theta (y is still accepted as a deprecated alias). Only shape: "hemicycle" ships (concentric semicircular arcs). Parties fill left-to-right in data order, so sort your rows by political spectrum yourself. majorityLine (default true) draws the threshold line and "N to win" label; seatRadius defaults to "auto".
beeswarm takes one quantitative positional channel (the value axis) plus an optional nominal channel for grouped lanes; size scales dot area. The cross axis is pure pixel-space with no scale, so tall stacks can overflow a short container -- cap the size range or give it vertical room.
lollipop is a semantic alias for the dot/stem renderer (x quantitative, y category): a dot on a stem from the baseline. Negative values extend the stem left of the baseline.

Collapsed mark types: These mark aliases no longer exist as separate values. Use the canonical marks instead:

Old mark	Use instead
`"column"`	`"bar"` (engine infers vertical from encoding)
`"pie"`	`"arc"`
`"donut"`	`{ type: "arc", innerRadius: 40 }`
`"scatter"`	`"point"`
`"dot"`	`"circle"`

Reference Routing

Always load when generating a new chart spec: encoding-channels.md, format-strings.md, color-strategy.md

When the task involves...	Load
Dual-axis charts, independent y-scales	See Layer Composition section above -- no extra reference needed
Adding annotations, callouts, reference lines	annotations.md
onEdit callback, selection, inline editing	editing.md
Responsive layout, mobile, breakpoint overrides	responsive.md
Theme customization (colors, fonts, spacing)	theme.md
Data transforms (window, filter, aggregate, etc.)	data-transforms.md
Rendering setup (React, Vue, Svelte, vanilla)	rendering.md
Choosing chart type for a story	chart-selection.md
Writing titles, subtitles, annotation text	editorial-writing.md
Font sizing, type hierarchy	typography.md
Per-series visual overrides (dashed lines, opacity)	series-styles.md
Gradient fills (linear, radial, per-mark)	gradients.md
Entrance animations, easing, stagger, reduced motion	animation.md
Sankey diagram (flows between stages)	sankey.md
US state tile grid map	tilemap.md
Geo map: choropleth, symbol/point layer, projections, TopoJSON joins	map.md
Scroll-driven chart story (scrollytelling)	story.md
Final design quality check	design-review.md
Checking rendered output for defects	visual-qa.md

Common reference bundles:

New chart: encoding-channels + format-strings + color-strategy + editorial-writing + (mark-specific ref)
Design polish: design-review + visual-qa + editorial-writing
D3 infographic: d3-core-patterns + infographic-design + (topic-specific D3 ref)

Spec discriminant

Charts use mark (16 marks: "bar", "line", "area", "point", "circle", "arc", "text", "rule", "tick", "rect", "lollipop", "beeswarm", "range", "waffle", "calendar", "parliament").
Tables, graphs, sankey, tilemap, geo maps use type ("table" | "graph" | "sankey" | "tilemap" | "map").

Behavior worth knowing that the types don't tell you:

animation is off by default. Set true for sensible per-mark entrance defaults; pass an AnimationConfig for per-phase control. See animation.md.
crosshair is off by default and only renders on line/area charts.
endpointLabels is auto-on for ≥2-series line/area and auto-suppresses the traditional legend in that case. See the "Endpoint Labels" section below for the full suppression truth table.
hiddenSeries on the spec hides series on first render. The vanilla adapter also maintains a separate runtime hidden set populated by legend clicks; that triggers full engine recompile (y-axis rebalance, locked color scale, per-series UI hide). See "Legend Toggle (Runtime)" below.
display: 'sparkline' strips chrome, axes, legend, watermark, animation, and crosshair for inline KPI-card use. Explicit per-field overrides still win (set chrome.title and you'll still get a title in sparkline mode).
seriesSearch (boolean | { placeholder }) renders a typeahead "find your country" input over a categorical color encoding; selecting values highlights them (multi-select chips). Mutually exclusive with edit mode (search wins).
youDrawIt ({ from, prompt?, revealLabel?, comparisonLine? }) is the NYT "draw your guess before the reveal" format. Line marks only, single-series only; mutually exclusive with edit mode and seriesSearch. The vanilla instance exposes resetDrawing() / revealDrawing() and an onReveal(guess) callback.
mark.fillPattern: 'auto' layers a per-series SVG pattern (hatch, dots, crosshatch) over each fill so filled marks (bar/area/arc) stay distinguishable without color vision; 'none' (default) is solid fills.
Accessibility is automatic: openchart generates alt text, ARIA labels, and a hidden screen-reader data table. Override the alt text with top-level description (Vega-Lite sugar) or a11y.description (a11y.description wins); set a11y.hidden: true to aria-hidden a purely decorative chart. The engine also emits console warnings when adjacent series or text fall below WCAG contrast, naming the nearest passing color.

Mark (Charts Only)

Behavior the types don't tell you:

Bar orientation is inferred from encoding types. x: nominal/ordinal/temporal + y: quantitative = vertical column. x: quantitative + y: nominal/ordinal = horizontal bar. Override with mark: { type: "bar", orient: "horizontal" | "vertical" } only when the inference is wrong.
mark: "arc" is a pie by default. Pass innerRadius > 0 to get a donut.
mark.fill accepts a GradientDef for linear or radial gradients. Gradients can also appear as conditional color values in encoding.color. See gradients.md.
Default entrance animation depends on mark type when animation: true. Bars clip-reveal from the baseline; lines draw progressively; areas draw + fade; arcs scale from center; points pop in with scale + fade; text/rules/ticks fade in. See animation.md for per-mark defaults and per-phase overrides.

Collapsed mark aliases (don't use these):

Old mark	Use instead
`"column"`	`"bar"` (engine infers vertical from encoding)
`"pie"`	`"arc"`
`"donut"`	`{ type: "arc", innerRadius: 40 }`
`"scatter"`	`"point"`
`"dot"`	`"circle"`

Examples:

{ "mark": { "type": "line", "point": true, "interpolate": "monotone" } }
{ "mark": { "type": "arc", "innerRadius": 40 } }
{ "mark": { "type": "bar", "fill": { "gradient": "linear", "stops": [{"offset": 0, "color": "#1b7fa3"}, {"offset": 1, "color": "#1b7fa3", "opacity": 0.4}] } } }

Encoding Channels (Charts Only)

Behavior the types don't tell you:

field + type is the minimum for any channel. type must be one of "quantitative" | "temporal" | "nominal" | "ordinal" — picking the wrong one is the most common spec authoring bug (see Spec Anti-Patterns below).
axis.format is d3-format with a literal-suffix extension (e.g. ".1f%"). The literal suffix is OpenChart's add-on; native d3 doesn't support it. See format-strings.md and the Format Strings section below for the percent-form pitfall.
scale.nice: true is the default for quantitative and temporal scales — it rounds the domain outward to clean tick values. On temporal scales this can shift the domain by years; set nice: false when you need precise control.
stack defaults to stacked ("zero") when colored for both bar and area; line = n/a. Set stack: null for grouped/overlap behavior. See the per-mark default table in encoding-channels.md.
See encoding-channels.md for conditional encoding examples and the full per-channel guide.

Data Transforms (Charts Only)

Layer Composition (Charts Only)

Overlay multiple marks in a single chart using layer. Each layer is a standalone spec with its own mark, data, and encoding.

{
  "layer": [
    { "mark": "bar", "data": [...], "encoding": { ... } },
    { "mark": "line", "data": [...], "encoding": { ... } }
  ]
}

Layers share the same coordinate space. Use this for combo charts (bar + line), adding reference lines, or overlaying annotations.

Dual-Axis Charts (Independent Y-Scales)

{
  "resolve": { "scale": { "y": "independent" } },
  "layer": [
    {
      "mark": { "type": "bar", "opacity": 0.85 },
      "data": [
        { "year": "2022", "revenue": 8000000 },
        { "year": "2023", "revenue": -5000000 }
      ],
      "encoding": {
        "x": { "field": "year", "type": "ordinal" },
        "y": {
          "field": "revenue",
          "type": "quantitative",
          "axis": { "title": "Net Revenue ($)", "format": "~s", "labelColor": "#3E7CB1" }
        }
      },
      "labels": { "density": "none" }
    },
    {
      "mark": { "type": "line", "stroke": "#E07B39", "strokeWidth": 2.5, "point": true, "interpolate": "monotone" },
      "data": [
        { "year": "2022", "enrollment": 52800 },
        { "year": "2023", "enrollment": 51600 }
      ],
      "encoding": {
        "x": { "field": "year", "type": "ordinal" },
        "y": {
          "field": "enrollment",
          "type": "quantitative",
          "axis": { "title": "Enrollment", "format": "~s", "labelColor": "#E07B39" }
        }
      },
      "labels": { "density": "none" }
    }
  ]
}

Dual-axis rules:

Max 2 layers -- there are only left and right y-axes.
Both layers must have compatible x-field types (both ordinal, both temporal, etc.).
Use axis.labelColor on each layer's y-encoding to color the axis labels to match the series -- this is the standard dual-axis pattern (Datawrapper, Highcharts style).
Use labels: { density: "none" } on both layers to avoid label collisions between the two series.
The engine zero-aligns both y-scales so zero sits at the same pixel height on both axes. Annotations target the primary (left) y-scale.
Works with any combination: bar + line, bar + area, area + line.

Legend Configuration (Charts Only)

legend accepts position, show, columns, symbolLimit, maxRows, offset, exclude. Full shape: LegendConfig in index.d.ts.

Endpoint Labels (Multi-Series Line/Area)

endpointLabels accepts boolean | EndpointLabelsConfig (show, valueField, format, width, showMarker, showLeader, markerStyle). Full shape: EndpointLabelsConfig in index.d.ts.

`legend.show`	`endpointLabels`	Traditional legend	Endpoint column	End-of-line labels
unset	unset	hidden (auto-suppressed)	shown (default)	hidden
`true`	unset	shown	shown	hidden
unset	`false`	shown (auto-suppress revoked)	hidden	hidden
`false`	`false`	hidden	hidden	shown (last-resort)
`true`	`false`	shown	hidden	hidden
`false`	`true`	hidden	shown	hidden
`true`	`true`	shown	shown	hidden

Single-series charts: column hidden by default (nothing to identify).

Common patterns:

Default multi-series: leave both unset -- you get the endpoint column, no traditional legend.
"I want a top legend instead": legend: { position: 'top' }, endpointLabels: false.
"Both legend and endpoint column": legend: { show: true } (endpointLabels stays auto-on).

Legend Toggle (Runtime)

Clicking a legend entry hides/shows the corresponding series at runtime. This goes through engine recompile (not CSS hide), so:

The y-axis rebalances to the remaining visible series.
The color scale stays locked -- remaining lines keep their original palette colors (engine injects a stable scale.domain from the unfiltered data).
Per-series UI hides with the line: endpoint chip, leader, dot annotation, and any text annotation anchored to that series.
The last visible series can't be hidden (the toggle is a no-op).
Range annotations and reference lines pass through unchanged (they anchor to constant axis values, not series).

Label Density (Charts Only)

labels accepts density, format, prefix (full shape: LabelSpec in index.d.ts). The choice that actually drives the chart is density:

`density`	Behavior	Use when
`"auto"` (default)	Show labels with collision detection	Most charts
`"all"`	Show every label, no collision detection	Few data points, precise values matter
`"endpoints"`	First and last per series only (legacy end-of-line labels on line/area)	Single-series line emphasizing start/end
`"none"`	No labels (tooltips + legend only)	Dense data, clean look

Format Strings

Both axis.format and labels.format accept d3-format strings plus a literal suffix extension. See format strings reference for the full table.

Format	Output example	Use case
`".1f%"`	`12.5%`	Percentage (data already in %, not 0-1)
`"$,.0f"`	`$1,234`	Currency with commas
`"~s"`	`10k`, `1.5M`	SI suffix for large numbers
`",.0f"`	`132,979`	Comma-separated, no decimals
`".1%"`	`12.5%` (from 0.125)	d3 native percent (multiplies by 100)

Critical: When data is already in percentage form (12.5 meaning 12.5%), use ".1f%" not ".1%". The d3 % type multiplies by 100, so 12.5 becomes 1,250.0%.

Per-Series Styling (Charts Only)

Data Resolution

Keep data arrays under 150 rows per series. More data doesn't make a better chart - it makes a slower, harder-to-read one. Reduce resolution before building the spec, not after.

Time span	Resolution	Typical rows	Example
< 1 year	Daily or weekly	50-200	Stock price last 6 months
1-5 years	Monthly	12-60	Unemployment rate 2020-2025
5-25 years	Quarterly or annual	20-100	GDP since 2000
25-100+ years	Annual or decade	25-100	CO2 emissions since 1900

How to reduce: When querying APIs, aggregate before passing data to the spec:

Use group_by=year with aggregate=avg(value) to go from monthly to annual
Sample every Nth row for evenly-spaced data
Filter to the time range that matters (don't chart 75 years when the story is about the last 10)

First Draft Checklist

Run these checks before outputting a spec. These catch the issues that most often require iteration after rendering.

Check	What to verify
Data resolution is appropriate	Check total rows in the data array. Over 150 per series? Aggregate to a coarser time grain or sample. A 25-year time series should use annual or quarterly data, not monthly. See Data Resolution table.
Color encodes the story	If one variable drives the narrative, color should reinforce it. Use the decision table in color-strategy.md to pick the right strategy and `theme.colors` array. Don't leave a scatter plot monochrome when a gradient would make the pattern obvious.
Bar stacking is intentional	If using `color` encoding on a bar chart, verify stacking mode. Default is stacked (`stack: "zero"`), which adds values together visually. For side-by-side comparison bars (e.g., 2018 vs 2022), set `stack: null` on the quantitative encoding. Stacked bars sum values visually, so a comparison chart will show bars extending to the sum of both values.
Area stacking is intentional	Area charts default to stacked (`stack: "zero"`) when colored, same as bars. For side-by-side/overlap comparison, set `stack: null` on the y-channel (or `"normalize"` for percentage stacking, `"center"` for streamgraph).
Y-domain fits the data	Domain ceiling should be ~5-10% above the highest data value. `[0, 55]` for data peaking at 48.8 wastes space. Use `[0, 52]`. For bar/column charts with narrow data ranges (e.g., values between 200 and 280), don't default the floor to 0 - it makes variations invisible. Set the domain floor near the minimum value. Exception: charts where zero is a meaningful baseline (percent change from 0, counts).
Annotations clear of data AND each other	The engine auto-resolves annotation-to-annotation collisions, but start with good separation for cleaner results. Prefer 0-2 text annotations; use reflines for additional callouts. On scatter/bubble, use 40-100px offsets into empty quadrants with connectors. When using 2+ text annotations, verify with `playwright-cli`.
Subtitle is intentional about wrapping	Unintentional wrapping with orphaned fragments looks broken. Abbreviate, restructure, or use `\n` for explicit line breaks. Use shorthand keys in the subtitle (e.g., `"LI = low-income"`) rather than spelling everything out.
Endpoint labels won't eat the chart	The default chip+swatch column (`endpointLabels`) wraps long names at `width` (default 96px) and resolves collisions, so it handles long series names well. Only the legacy fallback (`labels: { density: "endpoints" }` with no `endpointLabels` and no top legend) reserves a huge right margin for long names — if you've forced that path, either abbreviate series names or switch to `legend: { position: "top" }, endpointLabels: false`.
Axis ticks show units	Percentages should show `10%` not `10`. Use `format: ".0f%"` when data is already in percent form (e.g., 10 meaning 10%). Use `format: ".0%"` only when data is in decimal form (0.10 meaning 10%). Large numbers should use SI suffixes: `format: "~s"` turns 10000 into `10k` and 1000000 into `1M`. For currency: `format: "$~s"` gives `$10k`, `$1M`. See the Format Strings table above.
Consistent color palette across related charts	If multiple charts in the same article cover the same dimension (e.g., poverty), use the same color mapping (blue = low, red = high) so the reader builds a mental model.

Spec Anti-Patterns

Mistake	Fix
Using `nominal` for numeric field	Use `quantitative` for numbers, `temporal` for dates
Using `ordinal` for temporal data	Use `temporal`; ordinal is for ordered categories
Too many data points (>150 per series)	Aggregate or sample before building the spec. See Data Resolution table above. Monthly data over 25 years = 300 rows per series, use annual instead
Forgetting encoding.color for multi-series	Line/bar with groups needs `color` channel
Bar chart for time series	Use line for temporal data; bar with vertical orientation for periodic categories
Using chart mark for network data	Use `type: "graph"` with nodes + edges
Using chart mark for US state data	Use `type: "tilemap"` with state code keys
Hand-rolling D3 for choropleths or symbol maps	Use `type: "map"` with TopoJSON from us-atlas/world-atlas. See map.md
Not specifying axis format for currency/pct	Add `axis: { format: "$,.0f" }` or `".1f%"`
Using `".1%"` when data is already in percent form	`".1%"` multiplies by 100 (d3 convention). If data is `12.5` meaning 12.5%, use `".1f%"` (literal suffix)
Axis format and label format inconsistent	Set both `axis.format` and `labels.format` to the same pattern so ticks and data labels match
Using `darkMode: "auto"` in class-based dark mode apps	`"auto"` checks `prefers-color-scheme` only. For class-based toggles (Astro, Next.js), observe DOM and map to `"force"`/`"off"`. See rendering
Temporal scale with `nice: true` (default) creating dead space	`nice` rounds the domain outward (e.g., `2010-01` becomes `2008`). Set `scale: { domain: ["2010-01", "2026-01"], nice: false }` for precise control
Using `type` instead of `mark` for charts	Charts use `mark: "line"` (not `type: "line"`). Only tables, graphs, sankey, tilemap, and geo maps use `type`.

For design anti-patterns (titles, color, annotations), see design review.

Known Gotchas

Rendering and component behaviors that aren't obvious from the spec alone.

Gotcha	Behavior	Fix
Refline labels only support top/bottom	`labelAnchor` on refline annotations only accepts `"top"` or `"bottom"`. Left/right values are accepted in the type but have no visible effect on reflines (they do work on range annotations).	Set `label: ""` on the refline and add a separate `type: "text"` annotation positioned where you want a side label.
Endpoint chip labels wrap by width, not `\n`	The chip+swatch column wraps long series names at `endpointLabels.width` (default 96px). `\n` in the series name does not create a hard break.	Either shorten the series name in the data, or raise `width` if you have horizontal room.
Area defaults to stacked, not overlap	Multi-series area charts stack from a zero baseline by default when colored, same as bars. Setting `color` without `stack: null` on the y-channel produces a stacked composition, not overlapping semi-transparent fills.	For overlap/side-by-side, opt out with `encoding: { y: { ..., stack: null } }`.
`connector: 'drop-line'` only flips against the chart edge	The drop-line connector renders a vertical line through the data point's x and lays the label beside it. The auto-flip only checks against the chart area edge -- it does not avoid neighboring marks or other annotations.	Place the annotation away from cluttered regions; if collisions persist, switch to `connector: 'curve'` with a manual `offset`.
DataTable CSS overrides unreliable	Custom CSS targeting `.oc-table-wrapper td` may not apply due to CSS specificity.	Use the DataTable `style` prop for inline overrides: `<DataTable style={{ paddingLeft: 10 }} spec={...} />`.
Scatter plots auto-set `zero: false`	Unlike other chart types, scatter/point marks automatically set `scale.zero: false` on both axes if not explicitly configured. This means scatter domains fit tightly to data.	To include zero, explicitly set `scale: { zero: true }` on the relevant axis. Be aware that scatter and bar/line charts handle zero differently by default.
Constant colors require `mark.fill`, not encoding	`encoding.color: { value: "#hex" }` will error. The color encoding channel requires a `field` that maps to data.	Use `mark: { type: "bar", fill: "#1b7fa3" }` for constant colors across all marks.
Default gradient direction is top-to-bottom	A gradient with no explicit `x1/y1/x2/y2` defaults to vertical (top-to-bottom). On horizontal bars, the engine auto-orients this to left-to-right. On other marks, set coordinates explicitly.	For left-to-right: `x1:0, y1:0, x2:1, y2:0`. For top-to-bottom (default): omit coordinates or use `x1:0, y1:0, x2:0, y2:1`.
Layer scale mismatch	Second layer renders at wrong positions when layers have different value ranges.	For independent y-scales (e.g., revenue + enrollment), use `resolve: { scale: { y: "independent" } }` on the layer spec -- this renders both series correctly with left and right y-axes. For simple overlays where both series share the same scale, set an explicit `scale.domain` on both layers. Prefer `annotations` with `refline` over a full layer when you just need to add a threshold line.

Custom D3.js Infographics

Topic	Reference
D3 selections, scales, axes, margin convention	references/d3/d3-core-patterns.md
Tufte principles, storytelling, publication design	references/d3/infographic-design.md
Path morphing, generative art, creative coding	references/d3/advanced-techniques.md
D3 transitions, scroll effects, easing, timing	references/d3/animation-transitions.md
Treemap, sunburst, sankey diagrams	references/d3/chart-hierarchy.md
D3 color APIs, programmatic palette generation, contrast checking	references/d3/color-palettes.md
SVG text wrapping, collision detection, leader lines, ARIA	references/d3/typography-labels.md
viewBox, ResizeObserver, responsive SVG patterns	references/d3/responsive-svg.md

openchart

同仓库更多 Skills

同仓库更多 Skills

Data Visualization with OpenChart

Source of truth: load the types first

Rendering via MCP

What this skill carries that the types don't

Chart Selection Decision Tree

Visualization Types

Reference Routing

Spec discriminant

Mark (Charts Only)

Encoding Channels (Charts Only)

Data Transforms (Charts Only)

Layer Composition (Charts Only)

Dual-Axis Charts (Independent Y-Scales)

Legend Configuration (Charts Only)

Endpoint Labels (Multi-Series Line/Area)

Legend Toggle (Runtime)

Label Density (Charts Only)

Format Strings

Per-Series Styling (Charts Only)

Data Resolution

First Draft Checklist

Spec Anti-Patterns

Known Gotchas

Custom D3.js Infographics

Data Visualization with OpenChart

Source of truth: load the types first

Rendering via MCP

What this skill carries that the types don't

Chart Selection Decision Tree

Visualization Types

Reference Routing

Spec discriminant

Mark (Charts Only)

Encoding Channels (Charts Only)

Data Transforms (Charts Only)

Layer Composition (Charts Only)

Dual-Axis Charts (Independent Y-Scales)

Legend Configuration (Charts Only)

Endpoint Labels (Multi-Series Line/Area)

Legend Toggle (Runtime)

Label Density (Charts Only)

Format Strings

Per-Series Styling (Charts Only)

Data Resolution

First Draft Checklist

Spec Anti-Patterns

Known Gotchas

Custom D3.js Infographics