
Context Optimization
When you're hitting context limits or watching token costs spiral, this gives you four concrete levers: compress old conversation turns into summaries, mask verbose tool outputs with compact references, optimize for KV-cache hits by reordering stable content first, or partition work across sub-agents with isolated contexts. The claim is you can double or triple effective capacity without quality loss. Most valuable when tool outputs dominate your token budget or you're building long-running agents. The compaction and masking strategies are immediately practical. The real insight here is that context quality beats quantity, so you're strategically choosing what to keep rather than trying to cram everything in.
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- Jul 14, 2026
Install
$ npx -y skills add sickn33/antigravity-awesome-skills --skill context-optimization --agent claude-codeInstalls into .claude/skills of the current project.
Files
Context Optimization Techniques
Context optimization extends the effective capacity of limited context windows through strategic compression, masking, caching, and partitioning. The goal is not to magically increase context windows but to make better use of available capacity. Effectiveness depends on task/workload and must be measured; compression can lose critical information.
When to Use
Activate this skill when:
- Context limits constrain task complexity
- Optimizing for cost reduction (fewer tokens = lower costs)
- Reducing latency for long conversations
- Implementing long-running agent systems
- Needing to handle larger documents or conversations
- Building production systems at scale
Core Concepts
Context optimization extends effective capacity through four primary strategies: compaction (summarizing context near limits), observation masking (replacing verbose outputs with references), KV-cache optimization (reusing cached computations), and context partitioning (splitting work across isolated contexts).
Sponsors
Details
- Repository
- github.com/sickn33/antigravity-awesome-skills
- First seen
- Jun 3, 2026
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