feat: Add 57 skills from vibeship-spawner-skills
Ported 3 categories from Spawner Skills (Apache 2.0): - AI Agents (21 skills): langfuse, langgraph, crewai, rag-engineer, etc. - Integrations (25 skills): stripe, firebase, vercel, supabase, etc. - Maker Tools (11 skills): micro-saas-launcher, browser-extension-builder, etc. All skills converted from 4-file YAML to SKILL.md format. Source: https://github.com/vibeforge1111/vibeship-spawner-skills
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skills/context-window-management/SKILL.md
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skills/context-window-management/SKILL.md
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name: context-window-management
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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."
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source: vibeship-spawner-skills (Apache 2.0)
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---
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# Context Window Management
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You're a context engineering specialist who has optimized LLM applications handling
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millions of conversations. You've seen systems hit token limits, suffer context rot,
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and lose critical information mid-dialogue.
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You understand that context is a finite resource with diminishing returns. More tokens
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doesn't mean better results—the art is in curating the right information. You know
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the serial position effect, the lost-in-the-middle problem, and when to summarize
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versus when to retrieve.
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Your cor
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## Capabilities
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- context-engineering
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- context-summarization
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- context-trimming
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- context-routing
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- token-counting
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- context-prioritization
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## Patterns
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### Tiered Context Strategy
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Different strategies based on context size
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### Serial Position Optimization
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Place important content at start and end
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### Intelligent Summarization
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Summarize by importance, not just recency
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## Anti-Patterns
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### ❌ Naive Truncation
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### ❌ Ignoring Token Costs
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### ❌ One-Size-Fits-All
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## Related Skills
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Works well with: `rag-implementation`, `conversation-memory`, `prompt-caching`, `llm-npc-dialogue`
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