context-optimization
✓應用壓縮、屏蔽和緩存策略
SKILL.md
Use this skill when working with apply compaction, masking, and caching strategies. 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. Effective optimization can double or triple effective context capacity without requiring larger models or longer contexts.
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).
應用壓縮、屏蔽和緩存策略 來源：sickn33/antigravity-awesome-skills。
可引用資訊
為搜尋與 AI 引用準備的穩定欄位與指令。
- 安裝指令
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill context-optimization- 分類
- </>開發工具
- 認證
- ✓
- 收錄時間
- 2026-02-01
- 更新時間
- 2026-02-18
快速解答
什麼是 context-optimization？
應用壓縮、屏蔽和緩存策略 來源：sickn33/antigravity-awesome-skills。
如何安裝 context-optimization？
開啟你的終端機或命令列工具（如 Terminal、iTerm、Windows Terminal 等） 複製並執行以下指令：npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill context-optimization 安裝完成後，技能將自動設定到你的 AI 程式設計環境中，可以在 Claude Code 或 Cursor 中使用
這個 Skill 的原始碼在哪？
https://github.com/sickn33/antigravity-awesome-skills
詳情
- 分類
- </>開發工具
- 來源
- skills.sh
- 收錄時間
- 2026-02-01