Mviz
matsonj/mviz
A chart & report builder for AI. An agent skill from matsonj/mviz.
Guide to Apache ECharts for interactive research data dashboards
$ npx skills add wentorai/research-plugins --skill echarts-visualization-guide -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install wentorai/research-plugins echarts-visualization-guide --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analysis/dataviz/echarts-visualization-guide .claude/skills/echarts-visualization-guide && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "echarts-visualization-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/analysis/dataviz/echarts-visualization-guide into .claude/skills/echarts-visualization-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "echarts-visualization-guide", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/wentorai/research-plugins/tree/main/skills/analysis/dataviz/echarts-visualization-guideType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add wentorai/research-plugins --skill echarts-visualization-guide -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install wentorai/research-plugins echarts-visualization-guide --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/analysis/dataviz/echarts-visualization-guide .agents/skills/echarts-visualization-guide && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "echarts-visualization-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/analysis/dataviz/echarts-visualization-guide into .agents/skills/echarts-visualization-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "echarts-visualization-guide", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add wentorai/research-plugins --skill echarts-visualization-guide -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install wentorai/research-plugins echarts-visualization-guide --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/analysis/dataviz/echarts-visualization-guide .cursor/skills/echarts-visualization-guide && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "echarts-visualization-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/analysis/dataviz/echarts-visualization-guide into .cursor/skills/echarts-visualization-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "echarts-visualization-guide", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/wentorai/research-plugins.git --path skills/analysis/dataviz/echarts-visualization-guide--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add wentorai/research-plugins --skill echarts-visualization-guide -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install wentorai/research-plugins echarts-visualization-guide --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/analysis/dataviz/echarts-visualization-guide .gemini/skills/echarts-visualization-guide && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "echarts-visualization-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/analysis/dataviz/echarts-visualization-guide into .gemini/skills/echarts-visualization-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "echarts-visualization-guide", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install wentorai/research-plugins echarts-visualization-guideInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add wentorai/research-plugins --skill echarts-visualization-guide -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/analysis/dataviz/echarts-visualization-guide .github/skills/echarts-visualization-guide && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "echarts-visualization-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/analysis/dataviz/echarts-visualization-guide into .github/skills/echarts-visualization-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "echarts-visualization-guide", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add wentorai/research-plugins --skill echarts-visualization-guide -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install wentorai/research-plugins echarts-visualization-guide --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/analysis/dataviz/echarts-visualization-guide .opencode/skills/echarts-visualization-guide && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "echarts-visualization-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/analysis/dataviz/echarts-visualization-guide into .opencode/skills/echarts-visualization-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "echarts-visualization-guide", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
echarts-visualization-guideGuide to Apache ECharts for interactive research data dashboards
Echarts Visualization Guide is an agent skill from wentorai/research-plugins. Guide to Apache ECharts for interactive research data dashboards
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Data & Analytics, covering Data visualization. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.
Read from SKILL.md and the folder at commit bf44b3c. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are javascript and html).
From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
cdn.jsdelivr.netAlso links to:
echarts.apache.orggithub.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Echarts Visualization Guide loads about 1.9k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 255 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 255 words, ~1,905 tokens.
.claude/skills/echarts-visualization-guide/SKILL.md (or your agent's skills folder).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/>`;
});
return html;
}
},
legend: { data: ['Gene A', 'Gene B', 'Gene C'], bottom: 10 },
xAxis: {
type: 'category',
name: 'Time (hours)',
data: [0, 2, 4, 8, 12, 24, 48, 72]
},
yAxis: {
type: 'value',
name: 'Relative Expression',
nameLocation: 'middle',
nameGap: 50
},
series: [
{
name: 'Gene A',
type: 'line',
data: [1.0, 1.2, 2.4, 5.1, 8.3, 12.1, 10.5, 9.2],
smooth: true,
lineStyle: { width: 2 }
},
{
name: 'Gene B',
type: 'line',
data: [1.0, 0.9, 0.7, 0.5, 0.3, 0.2, 0.15, 0.1],
smooth: true,
lineStyle: { width: 2 }
},
{
name: 'Gene C',
type: 'line',
data: [1.0, 1.1, 1.3, 1.8, 3.2, 6.7, 8.9, 11.4],
smooth: true,
lineStyle: { width: 2 }
}
]
};
chart.setOption(option);const scatterOption = {
title: { text: 'Treatment Response vs Dosage', left: 'center' },
xAxis: { type: 'value', name: 'Dosage (mg/kg)' },
yAxis: { type: 'value', name: 'Response Score' },
tooltip: {
formatter: p => `Dosage: ${p.value[0]}<br/>Response: ${p.value[1]}`
},
visualMap: {
min: 0, max: 100,
dimension: 2,
inRange: { color: ['#3B82F6', '#EF4444'] },
text: ['High', 'Low'],
calculable: true
},
series: [{
type: 'scatter',
symbolSize: d => Math.sqrt(d[2]) * 2,
data: experimentalData.map(d => [d.dosage, d.response, d.confidence])
}]
};const heatmapOption = {
title: { text: 'Sample Correlation Matrix', left: 'center' },
tooltip: {
position: 'top',
formatter: p => {
return `${sampleNames[p.value[0]]} vs ${sampleNames[p.value[1]]}<br/>` +
`Correlation: ${p.value[2].toFixed(4)}`;
}
},
grid: { left: 120, top: 60, right: 80, bottom: 100 },
xAxis: {
type: 'category',
data: sampleNames,
axisLabel: { rotate: 45 }
},
yAxis: {
type: 'category',
data: sampleNames
},
visualMap: {
min: -1, max: 1,
calculable: true,
orient: 'vertical',
right: 10,
top: 'center',
inRange: {
color: ['#2166AC', '#F7F7F7', '#B2182B']
}
},
series: [{
type: 'heatmap',
data: correlationData,
label: { show: true, formatter: p => p.value[2].toFixed(2), fontSize: 9 },
emphasis: {
itemStyle: { shadowBlur: 10, shadowColor: 'rgba(0,0,0,0.5)' }
}
}]
};const radarOption = {
title: { text: 'Model Performance Comparison', left: 'center' },
legend: { data: ['Model A', 'Model B', 'Baseline'], bottom: 10 },
radar: {
indicator: [
{ name: 'Accuracy', max: 1.0 },
{ name: 'Precision', max: 1.0 },
{ name: 'Recall', max: 1.0 },
{ name: 'F1 Score', max: 1.0 },
{ name: 'AUC-ROC', max: 1.0 },
{ name: 'Speed (norm)', max: 1.0 }
]
},
series: [{
type: 'radar',
data: [
{ value: [0.94, 0.91, 0.89, 0.90, 0.96, 0.72], name: 'Model A' },
{ value: [0.92, 0.95, 0.85, 0.90, 0.94, 0.88], name: 'Model B' },
{ value: [0.85, 0.82, 0.80, 0.81, 0.87, 0.95], name: 'Baseline' }
]
}]
};ECharts supports custom themes and responsive resizing, which is important when embedding visualizations in research web applications.
// Register a custom academic theme
echarts.registerTheme('academic', {
color: ['#3B82F6', '#EF4444', '#10B981', '#F59E0B', '#8B5CF6', '#EC4899'],
backgroundColor: '#FFFFFF',
textStyle: { fontFamily: 'Inter, sans-serif' },
title: { textStyle: { color: '#1F2937', fontSize: 16 } },
line: { smooth: false, symbolSize: 6 }
});
// Initialize chart with the academic theme
const chart = echarts.init(document.getElementById('chart'), 'academic');
// Handle responsive resizing
window.addEventListener('resize', () => chart.resize());// Load CSV data and convert to ECharts format
async function loadExperimentData(csvUrl) {
const response = await fetch(csvUrl);
const text = await response.text();
const rows = text.split('\n').slice(1);
const data = rows.map(row => {
const [sample, condition, value, error] = row.split(',');
return { sample, condition, value: parseFloat(value), error: parseFloat(error) };
});
return data;
}
// Export chart as PNG for publications
function downloadChart(chartInstance, filename) {
const url = chartInstance.getDataURL({
type: 'png',
pixelRatio: 3,
backgroundColor: '#fff'
});
const link = document.createElement('a');
link.href = url;
link.download = filename || 'chart.png';
link.click();
}© wentorai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/analysis/dataviz/echarts-visualization-guide of wentorai/research-plugins.
Open the folder on GitHubat commit bf44b3c
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.
Echarts Visualization Guide next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Echarts Visualization Guide this skillwentorai/research-plugins | 298 | 1 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Mvizmatsonj/mviz | 226 | — | ~11k | Automated safety check: Pass | None | |
| Dataviz Design GuidanceQwenLM/qwen-code | 28k | — | ~514 | Automated safety check: Pass | Apache-2.0 | |
| Creating Dashboardsancoleman/ai-design-components | 526 | — | ~3.5k | Automated safety check: Pass | MIT | |
| D3 Visualizationbenchflow-ai/skillsbench | 1.8k | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Cs448b Visualizationsundial-org/skills | 152 | — | ~684 | Automated safety check: Pass | None |
matsonj/mviz
A chart & report builder for AI. An agent skill from matsonj/mviz.
QwenLM/qwen-code
Guides chart, dashboard and map design: pick the simplest form for the question, state the finding in the title, and check palettes with a local validator.
ancoleman/ai-design-components
Creates comprehensive dashboard and analytics interfaces that combine data visualization, KPI cards, real-time updates, and interactive layouts.
benchflow-ai/skillsbench
Build deterministic, verifiable data visualizations with D3.js (v6).
sundial-org/skills
Data visualization design based on Stanford CS448B. An agent skill from sundial-org/skills.
GPTomics/bioSkills
Select colormaps and qualitative palettes for scientific figures using perceptual-uniformity, color-vision-deficiency safety, and luminance-monotonicity criteria.
wentorai/research-plugins
Craft structured research abstracts that maximize clarity and journal acceptance
wentorai/research-plugins
Manage academic citations across BibTeX, APA, MLA, and Chicago formats
wentorai/research-plugins
Summarize academic papers with structured extraction of key elements
wentorai/research-plugins
Evidence-based study techniques for academic learning and retention
wentorai/research-plugins
Adjust writing tone and register for academic audiences and venues
wentorai/research-plugins
Academic translation, post-editing, and Chinglish correction guide
Categories
Guide to Apache ECharts for interactive research data dashboards. Echarts Visualization Guide is an agent skill from wentorai/research-plugins.
Echarts Visualization Guide fits situations like: tasks that involve Data visualization.
Run `npx skills add wentorai/research-plugins --skill echarts-visualization-guide -a claude-code`. Or copy the skill folder (skills/analysis/dataviz/echarts-visualization-guide in wentorai/research-plugins) into .claude/skills/echarts-visualization-guide in your project. Claude Code loads it when a task matches its description.
Run `npx skills add wentorai/research-plugins --skill echarts-visualization-guide -a codex`. Or copy the skill folder (skills/analysis/dataviz/echarts-visualization-guide in wentorai/research-plugins) into .agents/skills/echarts-visualization-guide in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wentorai/research-plugins --skill echarts-visualization-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/echarts-visualization-guide, .gemini/skills/echarts-visualization-guide, .github/skills/echarts-visualization-guide and .opencode/skills/echarts-visualization-guide in your project.
SKILL.md names no scripts, command-line tools or credentials: Echarts Visualization Guide is instructions for the agent only.
SKILL.md names 3 domains. In commands or code: cdn.jsdelivr.net; the agent is likely to contact it when it follows the instructions. As links in the text: echarts.apache.org and github.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Echarts Visualization Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.9k tokens (SKILL.md is roughly 7.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Echarts Visualization Guide: Mviz (matsonj/mviz, 226 stars), Dataviz Design Guidance (QwenLM/qwen-code, 28k stars), Creating Dashboards (ancoleman/ai-design-components, 526 stars) and D3 Visualization (benchflow-ai/skillsbench, 1.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.
Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.