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AlexanderRadevich
AlexanderRadevichCOMMUNITY
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split-memory

Split monolithic CLAUDE.md files into modular instruction units with precedence rules.

Updated Aug 27, 2026
Search Tags:#project management#modularity#code organization#claudemd#ai configuration#instruction management
One-click install
npx skills add https://github.com/AlexanderRadevich/SportowyHub_clientApp --skill split-memory-alexanderradevich
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: split-memory
Source: https://github.com/AlexanderRadevich/SportowyHub_clientApp/tree/main/.claude/skills/split-memory
Command: npx skills add https://github.com/AlexanderRadevich/SportowyHub_clientApp --skill split-memory-alexanderradevich

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the challenge of managing large or complex instruction sets for AI models by providing a strategy to break down a monolithic instruction file into smaller, more organized, and maintainable units.

Core Features & Use Cases

  • Modularization: Organizes instructions by concern, module, or team to improve clarity and reduce cognitive load.
  • Precedence Rules: Establishes clear guidelines for resolving conflicts when instructions are distributed across multiple files.
  • Scalability: Enables effective management of AI instructions as projects grow in size and complexity.
  • Use Case: A project's CLAUDE.md file has grown to over 500 lines, making it difficult to find specific rules. This Skill can help refactor it into a root index file and several topic-specific files (e.g., architecture.md, testing.md).

Quick Start

Use the split-memory skill to organize the CLAUDE.md file by splitting it into multiple files based on concerns.

Frequently Asked Questions about split-memory

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

FAQPage Schema
How do I split a large CLAUDE.md file into smaller organized files?▼

You can modularize a large CLAUDE.md file by splitting it into a root index file and multiple topic-specific files, organizing instructions by concern, module, or team to reduce cognitive load.

What is the best way to organize AI configuration when a project involves multiple teams?▼

Organizing AI configuration for multiple teams is best handled by splitting instructions by team, establishing clear precedence rules to resolve conflicts across distributed files for better maintainability.

When do I need to refactor my AI instruction files?▼

You need to refactor your AI instruction files when a monolithic configuration exceeds a certain line count, involves multiple teams, or requires better organization by concern or module.

How do precedence rules manage conflicting instructions across split files?▼

Precedence rules manage conflicting instructions by establishing clear guidelines for resolving conflicts when AI instructions are distributed across multiple modular files.

Can I organize CLAUDE.md files by splitting them by concern or module?▼

Yes, you can organize CLAUDE.md files using split-by-concern, split-by-module, or split-by-team patterns to refactor monolithic files into a root index and topic-specific files like architecture.md and testing.md.

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