What kind of code statistics can I generate?

You can generate statistics for total lines of code, the number of functions or classes defined, and the frequency of specific patterns like imports or comments.

Does this skill modify my files?

No, the File Operations skill is strictly non-destructive. it uses tools like stat, wc, and grep to analyze and read files without making any changes.

How does it handle large repositories?

It utilizes optimized native shell commands like 'find' and 'du' to quickly process large directories and identify the largest files without excessive memory usage.

Can I count lines for specific file types only?

Yes, you can use pattern matching with Glob and find commands to target specific extensions like .py, .js, or .md for line counting.

File Operations & Analytics

Name: File Operations & Analytics
Author: pur3v4d3r

bypur3v4d3r

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Analytics & Monitoring

Analyzes file systems to provide detailed metadata, line counts, and content statistics without modifying source code.

About

The File Operations skill empowers Claude to perform deep audits of your codebase by retrieving technical metadata such as file sizes, modification timestamps, and line counts. By utilizing native shell tools and pattern searching, it provides a non-destructive way to analyze project structure, identify large files, and gather code quality metrics like TODO counts or class distributions. This skill is an essential utility for developers needing a high-level overview or specific quantitative data about their repository to inform architectural decisions, optimization efforts, or documentation updates.

Key Features

Efficient large-scale file discovery and directory-wide statistics
Accurate line counting for individual files or entire directory trees
Detailed file metadata retrieval including size, permissions, and timestamps
Pattern-based content analysis using Grep for code quality metrics
1 GitHub stars
Non-destructive file reading and structural analysis

Use Cases

Identifying technical debt by searching for TODOs and FIXMEs across the project
Performing a comprehensive audit of repository size and code-to-test ratios
Comparing file versions and sizes to optimize codebase performance and storage

About

Key Features

Efficient large-scale file discovery and directory-wide statistics
Accurate line counting for individual files or entire directory trees
Detailed file metadata retrieval including size, permissions, and timestamps
Pattern-based content analysis using Grep for code quality metrics
1 GitHub stars
Non-destructive file reading and structural analysis

Use Cases

Identifying technical debt by searching for TODOs and FIXMEs across the project
Performing a comprehensive audit of repository size and code-to-test ratios
Comparing file versions and sizes to optimize codebase performance and storage