docs: update file references after agent.go split (process.go, eventloop.go, distill.go)

docs/en/ARCHITECTURE.md

@@ -41,7 +41,7 @@ eventLoop() → processTextInput()
         └── after_output stage      Read-only, cleanup
 ```
 
-Code: `internal/agent/core/agent.go` — `process()` is the main tool loop
+Code: `internal/agent/core/process.go` — `process()` is the main tool loop
 
 ### 7 Stage Hooks
 
@@ -141,7 +141,7 @@ All vectorization unified under `StaticEmbedder` (`internal/memory/static_embedd
 | Context Prune | `context.go:155` | Trim low-relevance context events | VectorizeClean → CosineSimilarity(queryVec, evt.Vector) |
 | DocStore Query | `document.go:206` | Recall from document memory | TF-IDF Vectorize → vec.Search |
 | Indexer Entity Search | `indexer.go:96+111` | Recall from Graph | vector entity search + jieba keywords → SQLite LIKE + BFS |
-| Entity Similarity Detection | `agent.go` | Detect similar entities in Graph | Bigram Jaccard (>0.75 → consolidation) |
+| Entity Similarity Detection | `distill.go` | Detect similar entities in Graph | Bigram Jaccard (>0.75 → consolidation) |
 
 ### Context Layer
 
@@ -365,7 +365,7 @@ Three delivery paths:
 | interceptCh | Insert `[interrupt message]` in process() | Before each LLM call |
 | InjectInput | Trigger new processing when eventLoop is idle | No ongoing request |
 
-Code: `internal/agent/core/agent.go` — `interceptLoop` / `drainInterrupt`
+Code: `internal/agent/core/eventloop.go` — `interceptLoop` / `drainInterrupts`
 
 <img src="../../branding/mascot-xiaozhai.webp" width="20" style="border-radius:50%;vertical-align:middle"> :
 

docs/en/OVERVIEW.md

@@ -33,11 +33,12 @@ Three progressive layers: context → cold archive → long-term graph memory, e
 
 Code is in the project root, implemented in Go.
 
-**Kernel** (`internal/agent/core/agent.go`):
-- Maintains a message loop (`eventLoop`), queuing input from the IO layer
-- Each input goes through the full processing pipeline: memory recall → persona injection → LLM call → tool execution → output delivery
+**Kernel** (`internal/agent/core/`):
+- `eventloop.go` — Message loop (`eventLoop`), queuing input from the IO layer
+- `process.go` / `stages.go` — Processing pipeline: memory recall → persona injection → LLM call → tool execution → output delivery, 7 stage hooks
+- `toolcall.go` — Tool scheduling and execution
+- `context.go` — Context management (pretrained word embedding scoring StaticEmbedder → CosineSimilarity, TF-IDF fallback), automatic pruning of low-relevance events
 - LLM calls abstracted through Provider interface, supports 8 LLM sources with automatic fallback
-- Context management (`context.go`) based on pretrained word embedding scoring (StaticEmbedder → CosineSimilarity, TF-IDF fallback), automatic pruning of low-relevance events
 
 **Memory System** (`internal/memory/`):
 - **GraphDB** (`graph.go`) — SQLite, entities + relations tables, BFS traversal

docs/zh/ARCHITECTURE.md

@@ -41,7 +41,7 @@ eventLoop() → processTextInput()
         └── after_output stage       插件只读，收尾
 ```
 
-代码：`internal/agent/core/agent.go` — `process()` 是工具循环主体
+代码：`internal/agent/core/process.go` — `process()` 是工具循环主体
 
 ### 7 个阶段钩子
 
@@ -141,7 +141,7 @@ eventLoop() → processTextInput()
 | Context Prune | `context.go:155` | 裁剪低相关性上下文事件 | VectorizeClean → CosineSimilarity(queryVec, evt.Vector) |
 | DocStore Query | `document.go:206` | 文档记忆召回 | TF-IDF Vectorize → vec.Search |
 | Indexer 实体搜索 | `indexer.go:96+111` | Graph实体召回 | 向量实体搜索 + jieba关键词 → SQLite LIKE + BFS |
-| 实体相似度检测 | `agent.go` | Graph中相似实体 | Bigram Jaccard (>0.75 → consolidation) |
+| 实体相似度检测 | `distill.go` | Graph中相似实体 | Bigram Jaccard (>0.75 → consolidation) |
 
 ### Context 层
 
@@ -365,7 +365,7 @@ interceptLoop (goroutine)
 | interceptCh | process() 中插入 `[打断消息]` | 每个 LLM call 前 |
 | InjectInput | eventLoop 空闲时触发新处理 | 无进行中请求 |
 
-代码：`internal/agent/core/agent.go` — `interceptLoop` / `drainInterrupt`
+代码：`internal/agent/core/eventloop.go` — `interceptLoop` / `drainInterrupts`
 
 <img src="../../branding/mascot-xiaozhai.webp" width="20" style="border-radius:50%;vertical-align:middle"> :
 

docs/zh/OVERVIEW.md

@@ -33,11 +33,12 @@ HomeAgent 是一个持续运行的个人智能 Agent 框架。
 
 代码位于项目仓库根目录，Go 语言实现。
 
-**内核** (`internal/agent/core/agent.go`)：
-- 维护一个消息循环（`eventLoop`），从 IO 层排队接收输入
-- 每次输入走完整的处理管道：记忆召回 → 人格注入 → LLM 调用 → 工具执行 → 输出发送
+**内核** (`internal/agent/core/`)：
+- `eventloop.go` — 消息循环（`eventLoop`），从 IO 层排队接收输入
+- `process.go` / `stages.go` — 处理管道：记忆召回 → 人格注入 → LLM 调用 → 工具执行 → 输出发送，7 阶段钩子
+- `toolcall.go` — 工具调度与执行
+- `context.go` — 上下文管理（预训练词嵌入评分 StaticEmbedder → CosineSimilarity，TF-IDF 回退），自动剪枝低相关性事件
 - LLM 调用通过 Provider 接口抽象，支持 8 个 LLM 源自动降级
-- 上下文管理（`context.go`）基于预训练词嵌入评分（StaticEmbedder → CosineSimilarity，TF-IDF回退），自动剪枝低相关性事件
 
 **记忆系统** (`internal/memory/`)：
 - **GraphDB** (`graph.go`) — SQLite，entities + relations 表，BFS 遍历