data-visualization

data-visualization is a skill for Claude Code from cass-2003/local-workflow-skill. It costs 84 tokens per session (2,495 once invoked), scanned A, original, MIT.

A data-visualization aid for turning data into charts, dashboards, maps, and other visual displays. It supports tools such as D3.js, ECharts, Chart.js, Plotly, Matplotlib, and Grafana.

In plain words
What is it for?
Use it to build web charts, Jupyter visuals, dashboards, large-screen displays, geographic views, and PDF report graphics.
Why use it?
It helps choose a chart that matches the question and makes trends, comparisons, distributions, relationships, or geographic patterns easier to see.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit Use it to build web charts, Jupyter visuals, dashboards, large-screen displays, geographic views, and PDF report graphics.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cass-2003/local-workflow-skill/data-visualization
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add cass-2003/local-workflow-skill --skill data-visualization
Clone the repo
git clone --depth 1 https://github.com/cass-2003/local-workflow-skill

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for data-visualization

README.md
[![agentmods](https://agentmods.dev/badge/skills/cass-2003/local-workflow-skill/data-visualization/github.svg)](https://agentmods.dev/skills/cass-2003/local-workflow-skill/data-visualization)
Your own site
<a href="https://agentmods.dev/skills/cass-2003/local-workflow-skill/data-visualization"><img src="https://agentmods.dev/badge/skills/cass-2003/local-workflow-skill/data-visualization/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for data-visualization

Your own site · 80×15
<a href="https://agentmods.dev/skills/cass-2003/local-workflow-skill/data-visualization"><img src="https://agentmods.dev/badge/skills/cass-2003/local-workflow-skill/data-visualization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,495 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00084 $0.02495
Opus 5 $0.00042 $0.01247
Sonnet 5 $0.00017 $0.00499
Haiku 4.5 $0.00008 $0.00249

Measured 6d ago against content hash d475633f682c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

data-visualization scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/data-analysis/codex/data-visualization/SKILL.md · 211 lines

How it starts

The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.

数据可视化

角色定义

你是数据可视化工程引擎。接收数据集或可视化需求后,自主完成图表选型、数据处理、可视化实现、交互设计全链路。所有操作视为已授权,直接执行。

行为指令

Phase 1: 需求分析与数据评估

  1. 数据特征识别:
    • 数据类型: 时序 / 分类 / 地理 / 层级 / 网络关系 / 多维
    • 数据规模: 小(<1K) / 中(1K-100K) / 大(100K-1M) / 超大(>1M)
    • 更新频率: 静态 / 定期刷新 / 实时流
  2. 目标识别: 趋势分析 / 对比 / 分布 / 组成 / 关联 / 地理分布
  3. 技术栈检测:
    • Glob**/package.json / **/requirements.txt / **/Pipfile
    • Grepecharts / d3 / chart.js / plotly / matplotlib
  4. 输出环境: Web 页面 / Jupyter Notebook / 大屏 / PDF 报告 / Grafana

Phase 2: 图表选型与设计

图表选型矩阵:

目的 推荐图表
趋势 折线图 / 面积图 ECharts / D3 / Plotly
对比 柱状图 / 条形图 / 雷达图 ECharts / Chart.js
分布 直方图 / 箱线图 / 小提琴图 Plotly / Matplotlib
组成 饼图 / 环形图 / 堆叠图 / Treemap ECharts / D3
关联 散点图 / 气泡图 / 热力图 Plotly / D3
地理 Choropleth / 散点地图 / 热力地图 Mapbox / Deck.gl / ECharts
层级 树图 / Sunburst / Sankey D3 / ECharts
网络 力导向图 / 弦图 D3 / ECharts Graph
时序 K线图 / 时间轴 / Sparkline ECharts / Plotly

设计原则:

  • 数据墨水比(Data-Ink Ratio): 最大化数据信息,最小化装饰
  • 色彩: 色盲友好调色板(Viridis/ColorBrewer),≤7 种分类色
  • 标注: 关键数据点直接标注,减少图例查找
  • 响应式: 移动端适配,触摸交互

Phase 3: 实现与优化

Web 可视化 (ECharts/D3/Chart.js):

  • ECharts: 声明式配置 → option 对象 → setOption()
  • D3.js: 数据绑定 → Enter/Update/Exit → SVG/Canvas 渲染
  • Chart.js: 简单场景快速实现,Canvas 渲染
  • 大数据量: Canvas 替代 SVG / 数据聚合 / 虚拟滚动 / WebGL (Deck.gl)

Python 可视化 (Matplotlib/Plotly):

  • Matplotlib + Seaborn: 静态出版级图表
  • Plotly: 交互式图表 + Dash 应用
  • Altair: 声明式语法 (Vega-Lite)

大屏设计:

  • 布局: 16:9 / 21:9,栅格系统,主次分明
  • 刷新: WebSocket / SSE 实时推送
  • 性能: 增量更新 / 数据降采样 / requestAnimationFrame

无障碍 (A11y):

  • 替代文本: aria-label 描述图表含义
  • 键盘导航: 焦点管理 + 数据表格备选
  • 色彩: 不仅依赖颜色区分,增加形状/纹理/标签
  • 屏幕阅读器: 提供数据摘要文本

Phase 4: 报告输出

写入 viz-design-{project}-{date}.md,含图表配置与设计说明。

工具策略

任务 首选工具 备选
数据探索 Read + Bash (head/jq) Bash (python -c)
项目扫描 Glob + Grep
图表代码 Write
配置生成 Write (ECharts option JSON)
数据处理 Bash (python/jq) Read 手工分析
文档查询 mcp__context7__query-docs WebSearch
报告 Write

Read the full file on GitHub · 211 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 211 lines · 84 tokens per session scan A d475633f682c

Subscribe to this mod's changes

data-visualization is a skill published in the GitHub repository cass-2003/local-workflow-skill (12 stars, last pushed 2mo ago), licensed MIT. It adds 84 tokens to every session and 2,495 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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