What are PreCompact hooks?

These are automated prompts that trigger before context compression to summarize your work status, ensuring you don't lose track of your progress when memory is cleared.

Why is context management important in Claude Code?

Claude Code has a 200k token limit which can be consumed quickly by large files and multiple MCPs; managing it strategically prevents performance degradation.

Does context compression cause me to lose work progress?

No, if you use the state restoration strategy provided by this skill, you save a summary of current tasks, completed steps, and next actions before the history is cleared.

How many MCP servers should I run simultaneously?

To preserve context space, it is recommended to enable only necessary MCPs, ideally keeping the count under 10 to prevent the token window from shrinking.

When should I manually compress my context?

It is best practice to compress manually after completing a major sub-task, before starting a brand new feature, or immediately following an intensive debugging session.

Strategic Context Compact

Name: Strategic Context Compact
Author: tadokoro-ryusuke

bytadokoro-ryusuke

Productivity & Workflow

Optimizes Claude Code context usage by strategically compressing history and managing token limits for complex development tasks.

About

Strategic Context Compact is a specialized skill designed to manage Claude Code's 200k token window efficiently. It provides guidance on selective file loading, MCP server management, and automated context compression to prevent performance degradation during long sessions. By implementing PreCompact hooks and structured state restoration summaries, it ensures that essential task details, progress, and next steps are preserved even when clearing history, making it indispensable for large-scale projects and intensive debugging workflows.

Key Features

Selective MCP server management to maximize available token space
Context window optimization through strategic history compression
0 GitHub stars
Structured state restoration templates for seamless task transitions
Best practices for minimal file loading and efficient token usage
PreCompact hooks to summarize work status before clearing memory

Use Cases

Transitioning between complex development tasks without losing progress details
Optimizing AI performance when multiple MCP servers are active in a single project
Managing long-running debugging sessions that consume large amounts of context

About

Key Features

Selective MCP server management to maximize available token space
Context window optimization through strategic history compression
0 GitHub stars
Structured state restoration templates for seamless task transitions
Best practices for minimal file loading and efficient token usage
PreCompact hooks to summarize work status before clearing memory

Use Cases

Transitioning between complex development tasks without losing progress details
Optimizing AI performance when multiple MCP servers are active in a single project
Managing long-running debugging sessions that consume large amounts of context