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jugrajsingh
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optimize

Reduce CLAUDE.md token usage through deduplication, condensation, and reference extraction.

1|Updated Jan 31, 2026
Search Tags:#optimization#claude#token reduction#claudemd#context cost#codebase hygiene
One-click install
npx skills add https://github.com/jugrajsingh/skillgarden --skill optimize-jugrajsingh
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: optimize
Source: https://github.com/jugrajsingh/skillgarden/tree/main/plugins/claudemd/skills/optimize
Command: npx skills add https://github.com/jugrajsingh/skillgarden --skill optimize-jugrajsingh

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill tackles the problem of excessive token usage in CLAUDE.md files by systematically reducing their size and optimizing their content for better efficiency and cost savings.

Core Features & Use Cases

  • Context Cost Reduction: Minimizes token count across the entire CLAUDE.md hierarchy (root, modules, rules).
  • Deduplication: Identifies and removes redundant information shared between module and root CLAUDE.md files.
  • Condensation: Transforms verbose prose into terse, directive-style content.
  • Reference Optimization: Replaces inline code examples with pointers to canonical files.
  • Rule Extraction: Moves common patterns from multiple modules into centralized .claude/rules/ files.
  • Use Case: Streamline your project's context files to reduce Claude's processing costs and improve response times by making the essential information more accessible.

Quick Start

Run the optimize skill to reduce context cost across all CLAUDE.md files in the repository.

Frequently Asked Questions about optimize

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

FAQPage Schema
How do I reduce CLAUDE.md context cost and token usage in my codebase?▼

To reduce CLAUDE.md context cost, you can systematically shrink the file hierarchy by applying deduplication, condensation, and reference extraction across root, module, and rule files to minimize token usage.

What is the best way to optimize CLAUDE.md files for efficient AI interaction?▼

Optimizing CLAUDE.md files for efficient AI interaction involves replacing verbose prose with directive-style content, extracting common patterns into centralized `.claude/rules/` files, and replacing inline code examples with canonical file pointers.

How does deduplication work for CLAUDE.md module and root files?▼

Deduplication for CLAUDE.md module and root files works by identifying and removing redundant information shared across the hierarchy, moving shared patterns to `.claude/rules/` files to improve the signal-to-noise ratio.

Can I extract inline code examples from CLAUDE.md to reduce context size?▼

Yes, you can reduce context size by applying reference optimization, which replaces inline code examples in CLAUDE.md files with pointers to canonical files, directly minimizing token consumption.

Does optimizing CLAUDE.md context cost require any external dependencies?▼

No, optimizing CLAUDE.md context cost requires no external dependencies, allowing you to directly run the optimization process across all root, module, and rule files within your existing repository.

Why does my CLAUDE.md hierarchy use so many tokens during Claude processing?▼

Your CLAUDE.md hierarchy uses excessive tokens due to redundant information across modules, verbose prose, and inline code examples, which can be resolved through condensation and reference extraction to meet size targets.

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