Individual skill
context-optimization
This skill should be used for improving context efficiency: context budgeting, observation masking, prefix or KV-cache strategy, partitioning, token-cost reduction, retrieval scoping, and extending effective context capacity without lowering answer quality.
skills/context-optimization/SKILL.md
Source commit a6603bf9fa9acd6bf9c7cc2fa6273ad3faa1c3b6
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- Observed behavior
- Network or broad shell
- Last checked
- Nov 11, 2026
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- Repository stars (not skill ratings)
- 992
- Repository last updated
- Nov 10, 2026
- License
- MIT
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- ai-skills Repository topic
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SKILL.mdcore · 16,052 bytesSKILL.mdcore · 16,052 bytesSKILL.mdcore · 16,052 bytesSKILL.mdcore · 16,052 bytesreferences/optimization_techniques.mddoc · 9,347 bytesscripts/compaction.pyruns · 19,723 bytes
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# Context Optimization Techniques
Context optimization extends the effective capacity of limited context windows through strategic compression, masking, caching, and partitioning. Effective optimization increases useful capacity without requiring larger models or longer windows — but only when applied with measurement discipline. The techniques below are ordered by impact and risk.
## When to Activate
Activate this skill when:
- Context budgets or token costs constrain task complexity
- Observation masking can replace verbose tool outputs with retrievable references
- Prefix or KV-cache hit rate needs improvement
- Retrieval scoping can reduce irrelevant loaded context
- Context partitioning can extend effective capacity across agents
- Budget triggers are needed for masking, compaction, or partitioning
