Default skill for structured-data visualization, chart generation, and dashboard-style reporting. Use when the user asks to create charts, graphs, plots, das...
数据分析
Echarts Chart Skill
Generate charts from natural language or tabular data, recommend chart types, and export ECharts-based HTML or SVG. Use when users ask for one-sentence chart...
它能做什么
Generate charts from natural language or tabular data, recommend chart types, and export ECharts-based HTML or SVG. Use when users ask for one-sentence chart...
技能文档
ECharts Chart Skill
Use this skill when the user wants chart output from a short description or from table-like data.
Workflow
- Translate the user's request into a
ChartRequestJSON object. - If the chart type is unclear, run the recommendation command first.
- Run the generation command to produce a stable ECharts option.
- Run the render command when the user wants an embeddable
htmlorsvg.
Files
- Core types:
src/types/chart.ts - Chart recommendation:
src/core/recommend.ts - Option generation:
src/core/spec-to-option.ts - Rendering:
src/core/render.ts - Sample input:
examples/study-progress.request.json - Universal metadata:
manifest.yaml,agents/openai.yaml
Setup
npm install
Output rules
--outwrites to an exact file path.--out-dirwrites the default file into a directory you choose.desktopandhomeare valid aliases for--out-dirwhen the user explicitly asks for those locations.~is expanded to the current user's home directory.- If no output path is provided, files default to the current working directory.
Commands
node dist/cli/recommend-chart.js --input examples\study-progress.request.json
node dist/cli/generate-chart.js --input examples\study-progress.request.json
node dist/cli/render-chart.js --input option.json --format html
node dist/cli/render-chart.js --input option.json --format svg --out D:\reports\study-chart.svg
Default output filenames:
- Recommendation:
spec.json - Option:
option.json - HTML preview:
preview.html - SVG preview:
preview.svg
ChartRequest shape
{
"title": "Monthly study completion",
"dataset": [
{ "day": "2026-03-01", "completionRate": 62, "targetRate": 75 },
{ "day": "2026-03-02", "completionRate": 68, "targetRate": 75 }
],
"goal": "trend",
"xField": "day",
"yField": "completionRate",
"series": [
{ "name": "Completion", "field": "completionRate" },
{ "name": "Target", "field": "targetRate" }
]
}
Guidance
- Prefer deterministic field mapping over free-form inference when the user has already named fields.
- For pie charts, keep one category field and one metric field.
- For scatter charts, require numeric
xFieldandyField. - If the user only gave natural language, construct the smallest valid
ChartRequestbefore calling scripts. - If the user needs a report artifact, render
htmlfirst andsvgsecond.
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