Antigravity-awesome-skills context-window-management

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...

install

source · Clone the upstream repo

git clone https://github.com/benjaminasterA/antigravity-awesome-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/benjaminasterA/antigravity-awesome-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/context-window-management" ~/.claude/skills/benjaminastera-antigravity-awesome-skills-context-window-management && rm -rf "$T"

manifest: skills/context-window-management/SKILL.md

source content

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.