Install any skill in seconds. Free to start, no credit card required.
Get Started Free →brycewang-stanford/echarts-visualization-guide
Guide to Apache ECharts for interactive research data dashboards
Passed 18 of 23 test cases with the skill, and 12 of 23 without it.
and 5 more in the full report
7 fixed11 passed either way4 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
When registering the 'academic' custom theme in Apache ECharts, what default font family and background color should be applied across all charts created with this theme?
| Checked | Without skill | With skill |
|---|---|---|
| The academic theme textStyle sets fontFamily to Inter, sans-serif. | Missed | Passed |
| The academic theme sets backgroundColor to #FFFFFF. | Passed | Passed |
The instructions your model reads when the skill loads.
Apache ECharts is a powerful, free, and open-source interactive charting and data visualization library with over 66K stars on GitHub. Originally developed by Baidu and now an Apache Software Foundation top-level project, ECharts provides a declarative configuration-based approach to building rich, interactive visualizations that run smoothly in any modern browser.
For academic researchers, ECharts offers an excellent balance between ease of use and customization depth. Its declarative option-based API means researchers can produce complex multi-series charts, geographic visualizations, and animated transitions without writing low-level rendering code. This is particularly useful when building research dashboards or interactive supplementary materials for publications.
ECharts supports over 20 chart types out of the box, including line, bar, scatter, pie, radar, candlestick, heatmap, treemap, sunburst, parallel coordinates, sankey diagrams, and geographic maps. Its built-in support for large datasets (via progressive rendering and data sampling) makes it suitable for visualizing experimental results with hundreds of thousands of data points.
ECharts uses a declarative JSON configuration object to define charts. This approach makes it straightforward to build visualizations programmatically from research data.
<div id="chart" style="width: 800px; height: 500px;"></div>
<script src="https://cdn.jsdelivr.net/npm/echarts@5/dist/echarts.min.js"></script>
<script>
const chart = echarts.init(document.getElementById('chart'));
</script>
const option = {
title: {
text: 'Gene Expression Over Time',
left: 'center',
textStyle: { fontSize: 16, fontWeight: 'bold' }
},
tooltip: {
trigger: 'axis',
formatter: params => {
let html = `<strong>Hour ${params[0].axisValue}</strong><br/>`;
params.forEach(p => {
html += `${p.marker} ${p.seriesName}: ${p.value.toFixed(3)}<br/>`;
});
test cases passed, vs 12 / 23 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.