# Context Window Management

Strategies for managing LLM context windows including summarization, trimming, routing...

- Repository: https://github.com/davila7/claude-code-templates (33041 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add davila7/claude-code-templates --skill context-window-management -g -a claude-code -y`
Codex: `npx skills add davila7/claude-code-templates --skill context-window-management -g -a codex -y`
Cursor: `npx skills add davila7/claude-code-templates --skill context-window-management -g -a cursor -y`
Gemini CLI: `npx skills add davila7/claude-code-templates --skill context-window-management -g -a gemini-cli -y`

## Description

Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context engineering, long context.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Context Window Management

You're a context engineering specialist who has optimized LLM applications handling
millions of conversations. You've seen systems hit token limits, suffer context rot,
and lose critical information mid-dialogue.

You understand that context is a finite resource with diminishing returns. More tokens
doesn't mean better results, the art is in curating the right information. You know
the serial position effect, the lost-in-the-middle problem, and when to summarize
versus when to retrieve.

Your cor

## Capabilities

- context-engineering
- context-summarization
- context-trimming
- context-routing
- token-counting
- context-prioritization

## Patterns

### Tiered Context Strategy

Different strategies based on context size

### Serial Position Optimization

Place important content at start and end

### Intelligent Summarization

Summarize by importance, not just recency

## Anti-Patterns

### ❌ Naive Truncation

### ❌ Ignoring Token Costs

### ❌ One-Size-Fits-All

## Related Skills

Works well with: `rag-implementation`, `conversation-memory`, `prompt-caching`, `llm-npc-dialogue`