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chartchart 命令行

Agent Skill

chart 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:chart(chart 命令行)
来源仓库:https://github.com/pvergaraf/chart-skill
仓库路径:skills/chart
安装命令:
npx skills add https://github.com/pvergaraf/chart-skill --skill chart
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/pvergaraf/chart-skill --skill chart

简介

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态和协作事项进行整理时使用。
  • 可结合来源仓库和原始 README 核验具体用法和功能边界。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网或文件操作。
  • 涉及敏感操作时应注意运行环境隔离和数据保护。

SKILL.md

Chart Generation Skill

Generate clean, minimal charts with shadcn-inspired grayscale styling using QuickChart.io (no dependencies needed).

Quick Usage

Users can describe charts naturally:

/chart show me monthly revenue: Jan $12k, Feb $15k, Mar $18k, Apr $14k

/chart compare Q4 performance - Revenue was 450, Costs 320, Profit 130

/chart visualize team breakdown: Engineering 45%, Product 25%, Design 20%, Operations 10%

/chart create an area chart of daily active users over the past week

/chart horizontal bar ranking: Chile 89, Mexico 76, Peru 65, Colombia 58

/chart plot this data as a line chart [paste CSV or JSON]

Data Input Formats

Inline (Simple)

Label1 Value1, Label2 Value2, Label3 Value3

From file

/chart line chart from /path/to/data.csv

Chart Types

TypeKeywordsDescription
Bar (vertical)bar, bar chartVertical bars
Bar (horizontal)horizontal bar, hbarHorizontal bars
Lineline, line chartTime series, trends
Areaarea, area chartFilled line chart
Piepie, pie chartProportions
Doughnutdoughnut, donutRing-style proportions

Options

  • title: title "My Chart Title"
  • output: save to /path/to/chart.png (default: ~/Downloads/chart_YYYYMMDD_HHMMSS.png)
  • size: size 800x600 (width x height in pixels, default: 600x400)

Color Palette (Grayscale - shadcn/Zinc)

ColorHexUsage
zinc-900#18181BPrimary series
zinc-700#3F3F46Secondary series
zinc-500#71717AThird series
zinc-400#A1A1AAFourth series
zinc-300#D4D4D8Fifth series
zinc-200#E4E4E7Sixth series
zinc-100#F4F4F5Grid lines

Style Elements

  • Clean, minimal design
  • Grayscale color palette
  • Subtle grid lines (zinc-100)
  • Rounded corners on bars (radius: 4)
  • Smooth curves on lines (tension: 0.3)
  • No borders, light aesthetic
  • Semi-transparent fills for area charts

CRITICAL: Y-Axis Labels

Every Y-axis MUST have visible numeric tick values. Never omit them. This applies to:

  • Single Y-axis: Always include ticks with color and padding on the y scale. Never set display: false on ticks.
  • Dual Y-axis: Both y (left) AND y1 (right) must have visible tick values. The right axis must also have ticks configured with color and padding, not just a title.
  • Axis titles (optional): If the data has units (e.g., "minutes", "hours", "$"), add a title to the axis with display: true and text: "Unit".

If a chart has two datasets with different units, use dual Y-axis with yAxisID on each dataset — and ensure BOTH axes render tick values.

Instructions

When the user requests a chart:

  1. Parse the request to identify:

- Chart type (bar, line, area, pie, doughnut, horizontal bar) - Data (inline or file path) - Title (if provided) - Output path (default: ~/Downloads/chart_$(date +%Y%m%d_%H%M%S).png) - Size (default: 600x400)

  1. Build the Chart.js configuration using this shadcn-style template. Every Y-axis must have visible ticks — never omit them:
{
  "type": "bar",
  "data": {
    "labels": ["A", "B", "C"],
    "datasets": [{
      "data": [10, 20, 30],
      "backgroundColor": "#18181B",
      "borderRadius": 4
    }]
  },
  "options": {
    "layout": {
      "padding": { "top": 20, "right": 30, "bottom": 20, "left": 20 }
    },
    "plugins": {
      "title": {
        "display": true,
        "text": "Chart Title",
        "align": "start",
        "font": { "size": 16, "weight": "600", "family": "Inter, system-ui, sans-serif" },
        "color": "#18181B",
        "padding": { "bottom": 20 }
      },
      "legend": { "display": false },
      "datalabels": { "display": false }
    },
    "scales": {
      "y": {
        "beginAtZero": true,
        "border": { "display": false },
        "grid": { "color": "#F4F4F5" },
        "ticks": { "color": "#71717A", "padding": 10, "font": { "size": 11 } }
      },
      "x": {
        "border": { "display": false },
        "grid": { "display": false },
        "ticks": { "color": "#71717A", "padding": 10, "font": { "size": 11 } }
      }
    }
  }
}
  1. Generate the chart using POST to QuickChart.io:
curl -X POST https://quickchart.io/chart \
  -H 'Content-Type: application/json' \
  -d '{
    "version": "4",
    "backgroundColor": "white",
    "width": 600,
    "height": 400,
    "chart": CHART_CONFIG_JSON
  }' \
  --output ~/Downloads/chart_$(date +%Y%m%d_%H%M%S).png
  1. Show the result by reading the generated image file with the Read tool

Chart Type Configurations

Bar Chart

{
  "type": "bar",
  "data": {
    "labels": ["A", "B", "C"],
    "datasets": [{
      "data": [10, 20, 30],
      "backgroundColor": "#18181B",
      "borderRadius": 4
    }]
  }
}

Horizontal Bar Chart

{
  "type": "bar",
  "data": {
    "labels": ["A", "B", "C"],
    "datasets": [{
      "data": [10, 20, 30],
      "backgroundColor": "#18181B",
      "borderRadius": 4
    }]
  },
  "options": {
    "indexAxis": "y"
  }
}

Line Chart

{
  "type": "line",
  "data": {
    "labels": ["Jan", "Feb", "Mar"],
    "datasets": [{
      "data": [10, 20, 30],
      "borderColor": "#18181B",
      "borderWidth": 2,
      "tension": 0.3,
      "pointRadius": 0,
      "fill": false
    }]
  }
}

Area Chart (Filled Line)

{
  "type": "line",
  "data": {
    "labels": ["Jan", "Feb", "Mar"],
    "datasets": [{
      "data": [10, 20, 30],
      "borderColor": "#18181B",
      "backgroundColor": "rgba(24, 24, 27, 0.1)",
      "borderWidth": 2,
      "tension": 0.3,
      "pointRadius": 0,
      "fill": true
    }]
  }
}

Multi-Series Area Chart

{
  "type": "line",
  "data": {
    "labels": ["Jan", "Feb", "Mar", "Apr"],
    "datasets": [
      {
        "label": "Desktop",
        "data": [100, 150, 120, 180],
        "borderColor": "#18181B",
        "backgroundColor": "rgba(24, 24, 27, 0.15)",
        "borderWidth": 2,
        "tension": 0.3,
        "fill": true
      },
      {
        "label": "Mobile",
        "data": [80, 120, 140, 160],
        "borderColor": "#71717A",
        "backgroundColor": "rgba(113, 113, 122, 0.15)",
        "borderWidth": 2,
        "tension": 0.3,
        "fill": true
      }
    ]
  },
  "options": {
    "plugins": {
      "legend": { "display": true, "position": "bottom", "labels": { "color": "#71717A", "usePointStyle": true } }
    }
  }
}

Dual Y-Axis Bar Chart

{
  "type": "bar",
  "data": {
    "labels": ["Jan", "Feb", "Mar"],
    "datasets": [
      {
        "label": "Count",
        "data": [38, 41, 43],
        "backgroundColor": "#18181B",
        "borderRadius": 4,
        "yAxisID": "y"
      },
      {
        "label": "Hours",
        "data": [31, 36, 39],
        "backgroundColor": "#A1A1AA",
        "borderRadius": 4,
        "yAxisID": "y1"
      }
    ]
  },
  "options": {
    "scales": {
      "y": {
        "beginAtZero": true,
        "position": "left",
        "border": { "display": false },
        "grid": { "color": "#F4F4F5" },
        "ticks": { "color": "#71717A", "padding": 10, "font": { "size": 11 } },
        "title": { "display": true, "text": "Count", "color": "#71717A", "font": { "size": 11 } }
      },
      "y1": {
        "beginAtZero": true,
        "position": "right",
        "border": { "display": false },
        "grid": { "display": false },
        "ticks": { "color": "#71717A", "padding": 10, "font": { "size": 11 } },
        "title": { "display": true, "text": "Hours", "color": "#71717A", "font": { "size": 11 } }
      },
      "x": {
        "border": { "display": false },
        "grid": { "display": false },
        "ticks": { "color": "#71717A", "padding": 10, "font": { "size": 11 } }
      }
    },
    "plugins": {
      "legend": { "display": true, "position": "bottom", "labels": { "color": "#71717A", "usePointStyle": true } }
    }
  }
}

Pie / Doughnut Chart

{
  "type": "doughnut",
  "data": {
    "labels": ["A", "B", "C"],
    "datasets": [{
      "data": [45, 30, 25],
      "backgroundColor": ["#18181B", "#71717A", "#D4D4D8"],
      "borderWidth": 0
    }]
  },
  "options": {
    "cutout": "60%"
  }
}

Examples

Bar Chart

/chart compare our Q4 numbers - Revenue hit 450, Costs were 320, and Profit came in at 130

Generated curl:

curl -X POST https://quickchart.io/chart \
  -H 'Content-Type: application/json' \
  -d '{
    "version": "4",
    "backgroundColor": "white",
    "width": 600,
    "height": 400,
    "chart": {
      "type": "bar",
      "data": {
        "labels": ["Revenue", "Costs", "Profit"],
        "datasets": [{"data": [450, 320, 130], "backgroundColor": "#18181B", "borderRadius": 4}]
      },
      "options": {
        "layout": {"padding": {"top": 20, "right": 30, "bottom": 20, "left": 20}},
        "plugins": {
          "title": {"display": true, "text": "Q4 Financial Summary", "align": "start", "font": {"size": 16, "weight": "600"}, "color": "#18181B", "padding": {"bottom": 20}},
          "legend": {"display": false}
        },
        "scales": {
          "y": {"beginAtZero": true, "border": {"display": false}, "grid": {"color": "#F4F4F5"}, "ticks": {"color": "#71717A", "padding": 10}},
          "x": {"border": {"display": false}, "grid": {"display": false}, "ticks": {"color": "#71717A", "padding": 10}}
        }
      }
    }
  }' \
  --output ~/Downloads/chart_$(date +%Y%m%d_%H%M%S).png

Area Chart

/chart show monthly visitors as an area chart - Jan had 186, Feb 305, Mar 237, Apr 73, May 209, Jun 214

Multi-Series Comparison

/chart compare desktop vs mobile traffic:
Desktop: Jan 100, Feb 150, Mar 120
Mobile: Jan 80, Feb 120, Mar 140

From Data

/chart visualize this CSV as a line chart:
date,users
2024-01-01,150
2024-01-02,180
2024-01-03,220

Output

Charts are saved to ~/Downloads/chart_YYYYMMDD_HHMMSS.png by default (with timestamp). Use the Read tool to display the generated image to the user.

No Dependencies

This skill uses QuickChart.io's free API - no local packages required. Just curl.

适合场景

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02

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03

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能力 2

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能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.6%
按下载量换算666

Claude

33.14%
按下载量换算603

Cursor

17.4%
按下载量换算317

Gemini CLI

9.5%
按下载量换算173

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安装前确认

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