chartjs-generator

SKILL开发
开发 未标注权限 许可证不明确

This skill generates interactive Chart.js visualizations for use in iframes using any chart type supported by the library (line, bar, pie, doughnut, radar, polar area, bubble, scatter). Use this skill when users need to create data visualizations for educational content, reports, or dashboards. The skill creates complete MicroSim packages with HTML, CSS, and documentation.

一句话选型结论

按资料字段整理

chartjs-generator是开发类的 Agent Skill,安装方式:GitHub 仓库,权限级别未标注,许可证不明确,没有现成安装命令,需按说明手动放置 SKILL.md。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类开发 安装方式GitHub 仓库 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 1 仓库 database-management
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

GitHub 仓库
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    按安装说明或仓库 README,把 SKILL.md 放到客户端的 skills 目录(一般一个技能一个文件夹)。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

开发
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方vishalsachdev仓库 database-management · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式GitHub 仓库安装包 vishalsachdev/database-management
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 未标注
正文体量17.5 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
写代码与改 bug

按需求补代码、定位并修掉报错。

读仓库与生成改动

让模型读懂项目结构,再给出可落地的改动。

跑测试与排查故障

按现象排查问题,补测试用例并复跑。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 基础信息齐全,可以先按说明装一个试试。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有现成安装命令,要按安装说明或仓库 README 手动放置。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在开发场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
chartjs-generator当前 未标注权限 GitHub 仓库 未标注 未标注 无
技能审查员 浏览器控制 ClawHub 市场 877.9 万 OpenClaw 有
Vercel React 最佳实践 浏览器控制 GitHub 仓库 849.1 万 Codex、Claude、Cursor 有
GitHub 代码协作 联网访问 ClawHub 市场 763.3 万 OpenClaw 有
网页设计指南 联网访问 GitHub 仓库 668.6 万 Codex、Claude、Cursor 有
本体论 只读 ClawHub 市场 663.7 万 OpenClaw 有

SKILL.md 全文

17.5 KB
模型实际读到的说明书原文,来自技能仓库

Chart.js Generator

Overview

This skill generates professional, interactive charts using Chart.js, supporting all major chart types. Chart.js is a powerful, flexible JavaScript library for creating responsive data visualizations. The skill creates a complete MicroSim package suitable for embedding in educational content or documentation sites built with MkDocs. The default placement in a intelligent book uses an iframe with minimal padding and margins.
Do not add any analysis or supporting documentation above or below the chart region.

Supported Chart Types

Chart.js supports the following chart types:

  1. Line - Time series, trends, continuous data
  2. Bar - Comparisons, categorical data, horizontal or vertical
  3. Pie - Proportions, percentages, part-to-whole relationships
  4. Doughnut - Similar to pie with central space for labels
  5. Radar - Multi-dimensional data, spider/web charts
  6. Polar Area - Similar to pie but with varying radius
  7. Bubble - Three-dimensional data (x, y, size)
  8. Scatter - Correlations, distributions, relationships

When to Use This Skill

Use this skill when users request:

  • Data visualizations: Any chart or graph for presenting data
  • Comparisons: Bar charts, grouped bars, stacked bars
  • Trends: Line charts, area charts, multi-line charts
  • Proportions: Pie charts, doughnut charts
  • Distributions: Scatter plots, bubble charts
  • Multi-dimensional data: Radar charts, bubble charts
  • Interactive charts: Hover tooltips, clickable elements, animations

Common trigger phrases:
- "Create a [chart type] showing..."
- "Visualize [data] as a [chart type]..."
- "Build an interactive chart for..."
- "Generate a graph showing..."

Workflow

Step 1: Determine Chart Type

If the user doesn't specify a chart type, ask them to select from the supported types:

Use the AskUserQuestion tool with these options:

  1. Line Chart - Best for trends over time, continuous data
  2. Bar Chart - Best for comparing categories, discrete data
  3. Pie/Doughnut Chart - Best for showing proportions and percentages
  4. Bubble/Scatter Chart - Best for multi-dimensional or correlation data
  5. Radar Chart - Best for comparing multiple variables across categories
  6. Polar Area Chart - Best for showing proportions with emphasis on differences

Step 2: Gather Data and Requirements

Before generating the chart, gather information about:

  1. Data structure: What data needs to be visualized?
    - Data points/values
    - Labels/categories
    - Multiple datasets (if applicable)
    - Time periods or categories
    - Units of measurement

  2. Chart configuration:
    - Chart title
    - Axis labels (for bar, line, scatter, bubble charts)
    - Legend requirements
    - Color scheme preferences
    - Special features (stacked, grouped, filled areas, etc.)

  3. Context: What is the purpose of the visualization?
    - Educational content
    - Data analysis
    - Report or presentation
    - Dashboard component

  4. Integration: Where will the chart be used?
    - Standalone page
    - Embedded in documentation
    - MkDocs site integration

Step 3: Create Directory Structure

Create a new directory for the MicroSim following this pattern:

docs/sims/<chart-name>/
├── main.html         # Main visualization file
├── style.css         # Styling
└── index.md          # Documentation (if part of MkDocs)

Naming convention: Use kebab-case (lowercase with hyphens) for directory names that are descriptive and URL-friendly (e.g., sales-trend-chart, market-share-pie, student-performance-radar).

Step 4: Create main.html with Chart.js

Generate the main HTML file with the following structure:

  1. HTML boilerplate with proper meta tags
  2. Chart.js CDN import: https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js
  3. Canvas element for the chart
  4. Optional analysis/legend section do not any analysis or documentation unless requested
  5. JavaScript implementation:
    - Data array/object
    - Color scheme configuration
    - Chart.js configuration for the selected chart type
    - Custom plugins (if needed)
    - Interactive features (tooltips, legends, animations)
    - Tooltips should always be used

Key Chart.js configuration by type:

Line Chart

{
    type: 'line',
    data: {
        labels: ['Jan', 'Feb', 'Mar', ...],
        datasets: [{
            label: 'Dataset 1',
            data: [12, 19, 3, 5, 2, 3],
            borderColor: 'rgb(75, 192, 192)',
            backgroundColor: 'rgba(75, 192, 192, 0.2)',
            tension: 0.1  // Curve smoothness
        }]
    },
    options: {
        responsive: true,
        scales: {
            y: { beginAtZero: true }
        }
    }
}

Bar Chart

{
    type: 'bar',
    data: {
        labels: ['Category A', 'Category B', ...],
        datasets: [{
            label: 'Dataset 1',
            data: [65, 59, 80, 81, 56, 55],
            backgroundColor: 'rgba(54, 162, 235, 0.8)',
            borderColor: 'rgb(54, 162, 235)',
            borderWidth: 1
        }]
    },
    options: {
        responsive: true,
        scales: {
            y: { beginAtZero: true }
        }
    }
}

Pie/Doughnut Chart

{
    type: 'pie',  // or 'doughnut'
    data: {
        labels: ['Red', 'Blue', 'Yellow', ...],
        datasets: [{
            data: [300, 50, 100],
            backgroundColor: [
                'rgba(255, 99, 132, 0.8)',
                'rgba(54, 162, 235, 0.8)',
                'rgba(255, 206, 86, 0.8)'
            ]
        }]
    },
    options: {
        responsive: true,
        plugins: {
            legend: { position: 'top' }
        }
    }
}

Radar Chart

{
    type: 'radar',
    data: {
        labels: ['Strength', 'Speed', 'Intelligence', ...],
        datasets: [{
            label: 'Player 1',
            data: [65, 59, 90, 81, 56],
            backgroundColor: 'rgba(255, 99, 132, 0.2)',
            borderColor: 'rgb(255, 99, 132)',
            pointBackgroundColor: 'rgb(255, 99, 132)'
        }]
    },
    options: {
        responsive: true,
        scales: {
            r: {
                beginAtZero: true,
                max: 100
            }
        }
    }
}

Bubble Chart

{
    type: 'bubble',
    data: {
        datasets: [{
            label: 'Dataset 1',
            data: [
                { x: 20, y: 30, r: 15 },  // r = bubble radius
                { x: 40, y: 10, r: 10 }
            ],
            backgroundColor: 'rgba(255, 99, 132, 0.8)'
        }]
    },
    options: {
        responsive: true,
        scales: {
            x: { min: 0, max: 100 },
            y: { min: 0, max: 100 }
        }
    }
}

Scatter Chart

{
    type: 'scatter',
    data: {
        datasets: [{
            label: 'Dataset 1',
            data: [
                { x: -10, y: 0 },
                { x: 0, y: 10 },
                { x: 10, y: 5 }
            ],
            backgroundColor: 'rgba(255, 99, 132, 0.8)'
        }]
    },
    options: {
        responsive: true,
        scales: {
            x: { type: 'linear', position: 'bottom' }
        }
    }
}

Important considerations:

  • Responsive design: Set responsive: true and appropriate aspect ratio
  • Color accessibility: Use distinguishable colors with good contrast
  • Tooltips: Customize tooltips to show relevant information
  • Legends: Position legends appropriately (top, bottom, left, right)
  • Animations: Enable/disable based on use case
  • Data labels: Use Chart.js plugins for data labels if needed

Step 5: Create style.css

Generate CSS with professional styling:

  1. Reset and base styles: Clean defaults for cross-browser consistency
  2. Chart container: Appropriate sizing, padding, box-shadow
  3. Legend/analysis container: Styling for supplementary information
  4. Interactive elements: Hover effects, transitions
  5. Responsive design: Media queries for mobile/tablet
  6. Print styles: Do not add additional CSS for printing

Key design principles:
- Use clean, modern aesthetics
- Assume placement of the chart in a book with narrow margins using a iframe
- Provide clear visual hierarchy
- Add subtle shadows and borders
- Include smooth transitions
- Ensure accessibility with sufficient contrast
- Make text readable at all sizes

Step 6: Create index.md Documentation

If the chart is part of a MkDocs site, create comprehensive documentation:

  1. YML Metadata: Add title, and description
  2. Title and overview: Brief description of the visualization
  3. Embedded iframe: Display the chart inline
  4. Link to fullscreen: Markdown link to main.html with button "View MicroSim Fullscreen"
  5. Interpretation guide: Explain how to read the chart
  6. Features section: List interactive elements
  7. Customization guide: Detailed instructions for modifying:
    - Data structure
    - Colors and styling
    - Chart options
    - Responsive behavior
    - Animations
  8. Technical details: Dependencies, browser compatibility, file structure
  9. Use cases: Other applications for this chart type
  10. References: Links to Chart.js docs and related resources

Documentation structure template:

---
title: [Chart Title]
description: [brief description of chart]
---

# [Chart Title]

[Brief description]

## Interactive Chart

<iframe src="main.html" width="100%" height="500" scrolling="no"></iframe>

[View Fullscreen](main.html){ .md-button .md-button--primary }

## Overview

[Detailed explanation of what the chart shows]

## Features

### Interactive Elements
- Hover tooltips showing detailed data
- Clickable legend items to show/hide datasets
- Smooth animations on load and update

### Visual Design
- Color-coded categories
- Clear axis labels and grid lines
- Responsive layout

## Customization Guide

### Changing the Data

To modify the chart data, edit the `data` object in `main.html`:

```javascript
const data = {
    labels: ['Your', 'Labels', 'Here'],
    datasets: [{
        label: 'Your Dataset',
        data: [10, 20, 30, 40]
    }]
};

Adjusting Colors

Customize the color scheme by modifying the backgroundColor and borderColor properties:

backgroundColor: [
    'rgba(255, 99, 132, 0.8)',
    'rgba(54, 162, 235, 0.8)',
    // Add more colors...
]

Chart Options

Modify chart behavior in the options object:

options: {
    responsive: true,
    maintainAspectRatio: true,
    aspectRatio: 2,  // Width:height ratio
    plugins: {
        title: { display: true, text: 'Your Title' },
        legend: { position: 'top' }
    }
}

Technical Details

  • Library: Chart.js 4.4.0
  • Browser Compatibility: All modern browsers (Chrome, Firefox, Safari, Edge)
  • Dependencies: Chart.js (loaded from CDN)
  • Responsive: Yes, adapts to container width

Use Cases

This chart type is useful for:
- [List relevant use cases]

References

- [Chart.js Documentation](https://www.chartjs.org/docs/latest/)
- [Chart Type Guide](https://www.chartjs.org/docs/latest/charts/[type].html)

Step 7: Integrate into Navigation (MkDocs)

Always add the chart to the navigation in mkdocs.yml:

- MicroSims:
    - Introduction: sims/index.md
    - [Chart Name]: sims/[chart-name]/index.md
    - [Other sims...]: ...

Place the entry in a alphabetical order.

Step 8: Test and Validate

Before considering the chart complete:

  1. Visual testing:
    - Open main.html in a browser directly
    - Test with mkdocs serve if applicable
    - Check all breakpoints (desktop, tablet, mobile)
    - Verify data displays correctly
    - Confirm labels and legends are readable

  2. Interactive testing:
    - Hover over chart elements to verify tooltips
    - Click legend items to show/hide datasets
    - Test animations (reload page)
    - Test on different browsers

  3. Documentation review:
    - Verify all code examples are accurate
    - Test customization instructions
    - Check all internal and external links

  4. Data validation:
    - Confirm all data points are plotted correctly
    - Verify calculations if applicable
    - Check that chart accurately represents the data

Best Practices

Data Preparation

  1. Consistent formatting: Use consistent data types and formats
  2. Meaningful labels: Use clear, descriptive labels
  3. Appropriate scale: Choose scales that show data effectively
  4. Complete data: Ensure all required fields are present

Visual Design

  1. Color coding: Use intuitive, accessible color schemes
  2. Contrast: Ensure sufficient contrast for readability
  3. Labels: Make all text readable at different sizes
  4. Spacing: Prevent overlap with appropriate padding
  5. Consistency: Use consistent styling across charts

Documentation

  1. Code examples: Provide exact, testable code snippets
  2. Before/after: Show the effect of customizations
  3. Parameter ranges: Suggest appropriate value ranges
  4. Common issues: Address typical problems and solutions

MkDocs Integration

  1. Iframe sizing: Use appropriate height for chart type (typically 500-900px)
  2. Path references: Use relative paths (../sims/...)
  3. Navigation placement: Group with related MicroSims
  4. Responsive embedding: Ensure iframe is responsive

Chart Type Selection Guide

Help users choose the right chart type:

Chart Type Best For Not Suitable For
Line Trends over time, continuous data Categorical comparisons
Bar Comparing categories, discrete data Trends, continuous data
Pie/Doughnut Part-to-whole, proportions (≤6 slices) Precise comparisons, many categories
Radar Comparing multiple variables, profiles Single variable, continuous data
Polar Area Proportions with emphasis on differences Precise comparisons
Bubble Three dimensions (x, y, size) Simple 1D or 2D data
Scatter Correlations, distributions Categorical data

Common Variations

Stacked Bar Chart

options: {
    scales: {
        x: { stacked: true },
        y: { stacked: true }
    }
}

Horizontal Bar Chart

{
    type: 'bar',
    options: {
        indexAxis: 'y'  // Makes bars horizontal
    }
}

Multi-Line Chart

Add multiple datasets to a line chart:

data: {
    datasets: [
        { label: 'Series 1', data: [...], borderColor: 'red' },
        { label: 'Series 2', data: [...], borderColor: 'blue' }
    ]
}

Filled Area Chart

{
    type: 'line',
    data: {
        datasets: [{
            fill: true,  // Fill area under line
            backgroundColor: 'rgba(75, 192, 192, 0.2)'
        }]
    }
}

Troubleshooting

Chart Not Displaying

Solution: Check that Chart.js CDN is loading correctly and canvas element has an ID.

Data Not Updating

Solution: Ensure chart.update() is called after modifying data:

chart.data.datasets[0].data = newData;
chart.update();

Labels Overlapping

Solution: Rotate labels or reduce font size:

scales: {
    x: {
        ticks: {
            maxRotation: 45,
            minRotation: 45
        }
    }
}

Colors Not Showing

Solution: Verify color format (rgba, rgb, hex) and ensure arrays match data length.

Responsive Issues

Solution: Set container dimensions and use maintainAspectRatio:

options: {
    responsive: true,
    maintainAspectRatio: true,
    aspectRatio: 2
}

Advanced Features

Data Labels Plugin

To show values on chart elements, use the Chart.js Data Labels plugin:

<script src="https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2"></script>

Animations

Customize animation timing and easing:

options: {
    animation: {
        duration: 2000,
        easing: 'easeInOutQuart'
    }
}

Custom Tooltips

Create fully custom tooltip content:

plugins: {
    tooltip: {
        callbacks: {
            label: function(context) {
                return 'Custom: ' + context.parsed.y;
            }
        }
    }
}

Click Events

Handle click events on chart elements:

options: {
    onClick: (event, elements) => {
        if (elements.length > 0) {
            const dataIndex = elements[0].index;
            console.log('Clicked:', chart.data.labels[dataIndex]);
        }
    }
}

References

This skill uses the following assets and references:

Assets

  • Chart.js CDN: https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js
  • Optional Data Labels Plugin: https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2
  • No local assets required (Chart.js loaded from CDN)

References

  • Chart.js Documentation
  • Chart.js Samples
  • Chart.js GitHub
  • Chart Types Guide

Example Implementations

See example charts in /docs/sims/ directory for reference implementations of different chart types.

```

常见问题

5 问
答案由本站依据条目字段整理
chartjs-generator怎么安装?

没有现成安装命令:按安装说明或仓库 README,把 SKILL.md 放进客户端的 skills 目录(一般一个技能一个文件夹)。

chartjs-generator支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

chartjs-generator权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

chartjs-generator收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

chartjs-generator用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。