neat-freak

Synchronize project documentation and AI memory with Python scripts.

Updated Jun 3, 2026

Search Tags:#project management #AI memory #code documentation #rule enforcement #knowledge cleanup

Ready to run

npx skills add https://github.com/gclm/skills-hub --skill neat-freak-gclm

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: neat-freak
Source: https://github.com/gclm/skills-hub/tree/main/neat-freak
Command: npx skills add https://github.com/gclm/skills-hub --skill neat-freak-gclm

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Git, ls, grep, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Ensures your project documents and AI memory are clean, accurate, and consistent across sessions, promoting knowledge retention and maintainability.

Core Features & Use Cases

End-of-Session Cleanup: Synchronizes project documentation (CLAUDE.md, README.md, docs/) and AI memory against the code, cleaning up outdated or conflicting information.
Rule Enforcement: Audits adherence to naming conventions, required files, and other project rules to maintain consistency and quality.
Use Case: After finishing development, use "sync up" to trigger the Skill to review and reconcile all knowledge bases.

Quick Start

Trigger the "neat-freak" Skill by saying "sync up" or "tidy up docs" in the context of project development or review.

Frequently Asked Questions about neat-freak

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

FAQPage Schema

How do I synchronize AI memory with project documentation after a coding session?▼

To synchronize AI memory with project documentation after a coding session, trigger a knowledge cleanup process to automatically review and reconcile information across files like CLAUDE.md and README.md. It scans your codebase to identify and correct outdated or conflicting knowledge.

What is AI memory cleanup in project management and when do I need it?▼

AI memory cleanup is the process of validating rule compliance and synchronizing retained knowledge against actual code changes. You need it after development sessions to ensure long-term project documents and AI memory remain accurate, consistent, and free of outdated information.

Do I need Git installed to automate code documentation and rule enforcement?▼

Yes, you need Git installed along with ls and grep commands to automate code documentation and rule enforcement. These external dependencies are required for the Python scripts to analyze files, audit project rules, and manipulate memory accurately.

How do I audit my codebase for naming convention and required file compliance?▼

To audit your codebase for naming convention and required file compliance, run an automated rule enforcement check against your project rules. This validates adherence to your established standards and suggests corrections for any identified inconsistencies.

What's the best way to clean up outdated information in project docs and AI memory?▼

The best way to clean up outdated information in project docs and AI memory is to run an end-of-session synchronization that performs extensive knowledge cleanup. This reconciles documents like docs/ and CLAUDE.md directly against the current code state.