compress

Compress natural language memory files into caveman format to reduce tokens.

Updated Aug 29, 2025
One-click install
npx skills add https://github.com/DDTully/dotfiles --skill compress-ddtully
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: compress
Source: https://github.com/DDTully/dotfiles/tree/main/skills/.agent_skills/compress
Command: npx skills add https://github.com/DDTully/dotfiles --skill compress-ddtully

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires anthropic, tiktoken, and includes scripts (resource) components.

What problem does it solve?

Compress memory files (CLAUDE.md, todos, preferences) into caveman format to reduce per-session token usage while preserving content and structure.

Core Features & Use Cases

  • Compress natural language memory files to minimize token load during Claude interactions.
  • Preserve code blocks, URLs, and file paths; automatically back up the original as <filename>.original.md.
  • Validate results and retry with targeted fixes if validation detects issues.

Quick Start

Run the caveman compress process on a target memory file to overwrite the original with a compressed version and generate a human-readable backup.

Frequently Asked Questions about compress

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

FAQPage Schema
How do I reduce token usage in Claude memory files like CLAUDE.md?

To reduce Claude memory tokens, compress natural language files into a condensed caveman format. This minimizes per-session token usage while preserving essential code blocks, URLs, and file paths.

What happens to my original markdown files when the compression process runs?

Your original markdown files are preserved by creating a human-readable backup named <filename>.original.md. The active memory file is then overwritten with the newly compressed version.

Do I need Python dependencies to run the markdown memory compression workflow?

Yes, the markdown memory compression workflow requires the anthropic and tiktoken Python dependencies. These drive the CLI workflow that detects language content and validates the compressed output.

How does the validation process handle compression errors in Claude memory files?

The validation process checks compressed Claude memory files and performs limited retries with targeted fixes if issues are detected. This ensures the final caveman format output maintains structural integrity.

Can I apply this token compression technique to project-level todos and preferences?

Yes, you can apply this token compression technique to project-level todos and preferences. The CLI-driven workflow detects language content across various memory files to systematically reduce token load.