package

Clean Python repository caches, build artifacts, and exposed secrets.

Updated Apr 1, 2026
One-click install
npx skills add https://github.com/zhuangfanupup/modular-rag-mcp-server --skill package-zhuangfanupup
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: package
Source: https://github.com/zhuangfanupup/modular-rag-mcp-server/tree/main/.github/skills/package
Command: npx skills add https://github.com/zhuangfanupup/modular-rag-mcp-server --skill package-zhuangfanupup

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill removes clutter, build leftovers, and accidental secrets so a project can be safely shared, archived, or prepared for distribution.

Core Features & Use Cases

  • Workspace Cleanup: Removes Python caches, virtual environments, build artifacts, IDE files, coverage output, logs, and temporary data directories.
  • Secret Sanitization: Replaces sensitive values in configuration files with placeholders instead of deleting the entire file.
  • Packaging Workflow: Supports dry-run review, user confirmation, execution, and verification so cleanup can be performed with confidence.
  • Use Case: Before handing a repository to a teammate or publishing a release, use this Skill to produce a minimal, clean codebase without stale artifacts.

Quick Start

Ask the package skill to scan the repository, show the cleanup plan, and then remove the approved files while preserving data if needed.

Frequently Asked Questions about package

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

FAQPage Schema
How do I clean up a Python repository before sharing or distribution?

To sanitize secrets in configuration files before handoff, replace sensitive values with placeholders instead of deleting the entire file. This skill detects exposed config values and sanitizes them in place to ensure safe repository distribution.

Can I preview which files will be removed during Python cache cleanup?

Yes, you can preview files during Python cache cleanup using a dry-run review. This skill detects removable paths like build artifacts and temporary data, shows the cleanup plan for user confirmation, and executes deletions only after approval.

Does the cleanup process preserve data and logs when preparing a codebase for archiving?

The cleanup process can optionally preserve data and logs when preparing a codebase for archiving. It safely removes Python caches and IDE files while allowing you to retain necessary data directories during the packaging and handoff workflow.

What is the best way to remove distribution blockers from a Python project?

The best way to remove distribution blockers from a Python project is to automate the detection and deletion of build leftovers and accidental secrets. This skill uses a cleanup script to sanitize configurations and strip clutter for a shareable codebase.

Why should I sanitize configuration files instead of deleting them before a release?

You should sanitize configuration files instead of deleting them before a release to maintain project structure while protecting sensitive data. Replacing secret values with placeholders keeps configs functional for teammates without exposing actual credentials.