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context-window-management

Estrategias para gestionar las ventanas de contexto de LLM que incluyen resumen, recorte, enrutamiento y evitar la degradación del contexto. Usar cuando: ventana de contexto, límite de tokens, gestión de contexto, ingeniería de contexto, contexto largo.

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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

Instalación

npx claude-code-templates@latest --skill ai-research/context-window-management

Quick start

  1. Install Claude Code if you have not already.
  2. Copy the Install command from this page and run it in your project directory.
  3. In Claude Code, load or mention the skill when your task matches what the skill is for.

Documentation

Use the links below for agent skills, troubleshooting, and official examples.

Recursos