← 返回 Skills 市场

Data Visualization Pro (Automaton)

Name: Data Visualization Pro (Automaton)
Author: chenghaifeng08-creator

作者 chenghaifeng08-creator · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ⚠ suspicious

533

总下载

当前安装

版本数

在 OpenClaw 中安装

/install data-visualization-pro-automaton

功能描述

AI-powered data visualization tool with 6 chart types (bar, line, pie, scatter, heatmap, radar), CSV/JSON import, AI-driven chart recommendations, interactiv...

使用说明 (SKILL.md)

Data Visualization Pro

AI-powered data visualization with smart chart recommendations.

Features

6 Chart Types: Bar, Line, Pie, Scatter, Heatmap, Radar
AI Chart Recommendations: Analyzes your data and suggests the best chart type
CSV/JSON Import: Drop in your data file and visualize instantly
Interactive Dashboards: Combine multiple charts into a single view
Export: PNG, SVG, PDF — publication-ready output
Responsive: Works on desktop and mobile

Quick Start

1. Visualize a CSV file

Visualize this data: [paste CSV or provide file path]

The agent will:

Parse the data (CSV, JSON, or raw text)
Analyze column types (numeric, categorical, temporal)
Recommend the best chart type
Generate an interactive visualization

2. Create a specific chart

Create a bar chart comparing Q1-Q4 revenue for 2024 and 2025

3. Build a dashboard

Build a dashboard from sales-data.csv with:
- Revenue trend (line chart)
- Regional breakdown (pie chart)
- Product comparison (bar chart)

Chart Selection Guide

Data Pattern	Recommended Chart	When to Use
Trends over time	Line	Time-series, stock prices, growth
Category comparison	Bar	Revenue by region, product sales
Part-of-whole	Pie	Market share, budget allocation
Correlation	Scatter	Height vs weight, price vs demand
Multi-variable	Radar	Product comparison, skill assessment
Density/matrix	Heatmap	Correlation matrix, geographic data

AI Recommendation Engine

The AI analyzes your data to recommend the optimal visualization:

Column type detection: Numeric, categorical, temporal, boolean
Relationship analysis: Correlation strength, distribution shape
Data volume assessment: Row count determines complexity level
Pattern recognition: Trends, clusters, outliers, proportions

Sample Datasets Included

sample-data.csv — Mixed business metrics
sample-categories.csv — Category comparison data
sample-correlation.csv — Multi-variable correlation data
sample-proportions.csv — Part-of-whole data

Technical Stack

Frontend: React + TypeScript + Vite
Charts: Recharts (built on D3.js)
Styling: Tailwind CSS
Export: html2canvas + jsPDF
Build: 382KB production build

Web App

Try the live demo: https://courageous-bonbon-d1af15.netlify.app

Usage Tips

For large datasets (>10K rows), use aggregation before visualizing
AI recommendations work best with 3-20 columns
Export at 2x resolution for print-quality output
Use the dashboard view to tell a complete data story

安全使用建议

This skill appears to be a benign data-visualization helper, but it has small inconsistencies that merit caution: (1) the SKILL.md claims sample datasets and a web app build but the package contains no code or those files — treat the live demo URL as an external, unverified site; (2) the skill asks for pasted CSV/JSON or a file path — do not give file paths to sensitive local files, and avoid uploading private data when testing; (3) if you plan to rely on this skill, ask the publisher for source code or a trustworthy repository, test with non-sensitive sample data first, and confirm where data is processed (local agent vs external demo). If you need higher assurance, only install skills with verifiable source code or from trusted publishers.

功能分析

Type: OpenClaw Skill Name: data-visualization-pro-automaton Version: 1.0.0 The skill bundle contains metadata and documentation for a data visualization tool. The instructions in SKILL.md are consistent with the stated purpose of parsing CSV/JSON data to generate charts and dashboards. No executable code, data exfiltration logic, or malicious prompt injection patterns were identified in the provided files.

能力评估

ℹ Purpose & Capability

Name/description describe a client-side visualization tool and the SKILL.md stays on-topic, but it claims included sample datasets and a 382KB production build / specific frontend stack while no code or sample files are present in the package. The live demo URL is provided but there is no install or source code to verify the app. These are marketing-style claims that aren't reflected in the bundle.

ℹ Instruction Scope

Instructions tell the agent to accept pasted CSV/JSON or a 'file path' and to parse/analyze data — this is appropriate for visualization, but 'provide file path' is ambiguous and could lead the agent to read local files. The SKILL.md does not explicitly instruct the agent to upload data to remote services, but the presence of an external demo URL means users might be directed to or influenced to use an external endpoint. No instructions request unrelated system files or env vars.

✓ Install Mechanism

No install spec and no code files — nothing is written to disk by the skill itself. This is the lower-risk configuration for an instruction-only skill.

✓ Credentials

The skill requests no environment variables, secrets, or config paths. There are no declared credentials, which is proportionate for a visualization helper that runs client-side or as instructions.

✓ Persistence & Privilege

always is false and the skill requires user invocation. It does not request permanent platform presence or to modify other skills or system-wide settings.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install data-visualization-pro-automaton
安装完成后，直接呼叫该 Skill 的名称或使用 /data-visualization-pro-automaton 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

Initial release: 6 chart types, AI recommendations, CSV/JSON import, interactive dashboards

元数据

Slug data-visualization-pro-automaton

版本 1.0.0

许可证 MIT-0

累计安装 1

当前安装数 1

历史版本数 1

常见问题