Auto Data Analyzer

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

Security Scan

The skill's description promises an automated data analyzer, but the package/implementation is missing — the instructions tell you to install generic Python libraries and reference modules/files that are not provided or sourced, so it's unclear how the skill would actually run.

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).

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.

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.

What to consider before installing

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.

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