package

Remove caches, build artifacts, logs, and exposed secrets from repositories.

Updated Apr 15, 2026

Search Tags:#packaging #cleanup #repository #secrets #distribution #caches

Ready to run

npx skills add https://github.com/CvNoobLrx/rag-mcp-modular-agent --skill package-cvnooblrx

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: package
Source: https://github.com/CvNoobLrx/rag-mcp-modular-agent/tree/main/.github/skills/package
Command: npx skills add https://github.com/CvNoobLrx/rag-mcp-modular-agent --skill package-cvnooblrx

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill removes local build noise, caches, virtual environments, logs, and exposed secrets so a project can be safely shared or packaged for distribution.

Core Features & Use Cases

Workspace Cleanup: Deletes common Python artifacts such as pycache, coverage outputs, build folders, and IDE files.
Data Preservation Options: Lets you keep data and logs when you want a lighter cleanup without losing ingested documents or runtime traces.
Secret Sanitization: Replaces real credentials in configuration files with placeholders to reduce the risk of leaking API keys.
Use Case: Before handing a repository to a teammate or uploading it for review, run this Skill to produce a minimal, sanitized copy ready to share.

Quick Start

Use the package skill to dry-run the cleanup, review what will be removed, and then execute the cleanup once you confirm.

Frequently Asked Questions about package

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I clean a repository for distribution and remove build artifacts?▼

Workspace cleanup removes Python artifacts such as __pycache__, coverage outputs, build folders, and IDE files to produce a minimal, shareable codebase. It deletes local build noise while preserving user-selected data and logs when a lighter cleanup is requested.

How do I sanitize configuration files and remove exposed secrets before sharing code?▼

Secret sanitization replaces real credentials in configuration files with placeholders to reduce the risk of leaking API keys. This ensures your codebase is safe before handing it to a teammate or uploading it for review.

Can I keep data and logs while removing virtual environments and caches?▼

Yes, data preservation options let you keep data and logs when you want a lighter cleanup without losing ingested documents or runtime traces, while still removing caches and virtual environments.

What is the best way to dry-run repository cleanup before executing the deletion?▼

The best way to dry-run repository cleanup is to preview what will be removed first, review the deletion list, and then execute the cleanup once you confirm the changes are safe for your distribution package.

Does repository cleanup work for Python virtual environments and coverage outputs?▼

Yes, repository cleanup works for Python projects by deleting common artifacts such as virtual environments, __pycache__, coverage outputs, and build folders to achieve a deterministic filesystem cleanup before release packaging.