docs: add token efficiency highlight to Core Features (EN+CN)
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@@ -23,6 +23,7 @@ Every time GenericAgent solves a new task, it automatically crystallizes the exe
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- **Minimal Architecture**: ~3K lines of core code. Agent Loop is ~100 lines. No complex dependencies, zero deployment overhead.
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- **Minimal Architecture**: ~3K lines of core code. Agent Loop is ~100 lines. No complex dependencies, zero deployment overhead.
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- **Strong Execution**: Injects into a real browser (preserving login sessions). 9 atomic tools take direct control of the system.
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- **Strong Execution**: Injects into a real browser (preserving login sessions). 9 atomic tools take direct control of the system.
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- **High Compatibility**: Supports Claude / Gemini / Kimi / MiniMax and other major models. Cross-platform.
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- **High Compatibility**: Supports Claude / Gemini / Kimi / MiniMax and other major models. Cross-platform.
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- **Token Efficient**: <30K context window — a fraction of the 200K–1M other agents consume. Layered memory ensures the right knowledge is always in scope. Less noise, fewer hallucinations, higher success rate — at a fraction of the cost.
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## 🧬 Self-Evolution Mechanism
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## 🧬 Self-Evolution Mechanism
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@@ -213,6 +214,7 @@ MIT License — see [LICENSE](LICENSE)
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- **极简架构**: ~3K 行核心代码,Agent Loop 约百行,无复杂依赖,部署零负担
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- **极简架构**: ~3K 行核心代码,Agent Loop 约百行,无复杂依赖,部署零负担
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- **强执行力**: 注入真实浏览器(保留登录态),9 个原子工具直接接管系统
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- **强执行力**: 注入真实浏览器(保留登录态),9 个原子工具直接接管系统
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- **高兼容性**: 支持 Claude / Gemini / Kimi / MiniMax 等主流模型,跨平台运行
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- **高兼容性**: 支持 Claude / Gemini / Kimi / MiniMax 等主流模型,跨平台运行
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- **极致省 Token**: 上下文窗口不到 30K,是其他 Agent(200K–1M)的零头。分层记忆让关键信息始终在场——噪声更少,幻觉更低,成功率反而更高,而成本低一个数量级。
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## 🧬 自我进化机制
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## 🧬 自我进化机制
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