context-window-management▌
sickn33/antigravity-awesome-skills · updated Apr 8, 2026
Strategies for managing LLM context windows through summarization, trimming, routing, and prioritization.
- ›Covers six core capabilities: context engineering, summarization, trimming, routing, token counting, and prioritization to prevent token limits and context rot
- ›Implements tiered context strategies that adapt based on context size, and serial position optimization to place critical information at start and end of context
- ›Avoids common anti-patterns including naive truncation, igno
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
When to Use
This skill is applicable to execute the workflow or actions described in the overview.