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Auto Data Analyzer

Name: Auto Data Analyzer
Author: jason-aka-chen

作者 jason-aka-chen · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ⚠ suspicious

137

总下载

当前安装

版本数

在 OpenClaw 中安装

/install auto-data-analyzer-chen

功能描述

Automated data analysis tool - Input CSV/Excel data and automatically generate comprehensive analysis reports. Includes data cleaning, statistical descriptio...

使用说明 (SKILL.md)

auto-data-analyzer

Automated data analysis tool that generates comprehensive reports from input data.

Features

1. Data Cleaning

Missing value detection and handling
Outlier detection
Data type conversion
Duplicate value handling

2. Statistical Description

Basic statistics (mean, median, standard deviation, etc.)
Quantile analysis
Distribution visualization

3. Visualization

Histograms
Box plots
Scatter plots
Heatmaps

4. Advanced Analysis

Correlation analysis
Regression analysis
Clustering analysis
Time series analysis

Usage

Installation

pip install pandas numpy matplotlib seaborn scikit-learn

Basic Usage

from analyzer import DataAnalyzer

analyzer = DataAnalyzer('data.csv')
analyzer.clean()
analyzer.describe()
analyzer.visualize()
analyzer.report()  # Generate HTML report

Command Line

python main.py data.csv --output report.html

Output

HTML analysis report
PNG charts
CSV statistical results

Use Cases

Business data analysis
Market research reports
User behavior analysis
Sales data analysis

安全使用建议

This skill's documentation describes a useful data-analysis tool but it does not include any code or a link to the implementation. Before installing or running anything: 1) Ask the publisher for the source repository or the pip package name for 'analyzer' and for main.py — do not assume these exist. 2) If you find a package/repo, review the code (or have someone review it) before running it, especially any scripts that read or upload your files. 3) Install the recommended Python libraries only in a controlled environment (virtualenv or container) so they don't affect your system Python. 4) If you plan to feed sensitive data, ensure the tool does not transmit data externally and run it in an isolated environment. If you cannot obtain the implementation or verify its origin, avoid installing or running the skill.

能力评估

⚠ Purpose & Capability

The SKILL.md describes a DataAnalyzer and shows example usage (from analyzer import DataAnalyzer, python main.py), but the skill bundle contains no code, no repository/link, and no published package name for 'analyzer' or 'main.py'. That is a mismatch between the claimed capability (an automated tool) and the actual contents (instruction-only).

ℹ Instruction Scope

The runtime instructions are narrowly focused (data cleaning, visualization, etc.) and only recommend installing common Python libraries and running a local script. They do not ask for unrelated files or credentials. However the instructions are vague about where the analyzer code comes from and assume local files that are not supplied.

ℹ Install Mechanism

There is no install spec in the registry (instruction-only). The SKILL.md suggests running 'pip install pandas numpy matplotlib seaborn scikit-learn' — installing these common packages is expected for data analysis and low risk, but the skill does not provide or point to the actual implementation that would use them.

✓ Credentials

The skill requests no environment variables, credentials, or config paths. The only environment actions are installing common Python data libraries and running local Python scripts, which is proportionate to the stated purpose — assuming the analyzer code exists.

✓ Persistence & Privilege

The skill does not request persistent privileges (always: false) and does not modify other skills or system settings. Autonomous invocation is allowed by default but not unusual.

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 auto-data-analyzer-chen
安装完成后，直接呼叫该 Skill 的名称或使用 /auto-data-analyzer-chen 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

元数据

Slug auto-data-analyzer-chen

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题