docs(readme): add comprehensive README and update Chinese documentation

- Added complete English README with project overview, core ideas, and design philosophy
- Included detailed directory structure and automatic memory flow explanations
- Updated Chinese README with refined descriptions and improved clarity
- Enhanced documentation for vault operations and community contribution guidelines
- Added proper formatting and tables for better readability
- Updated installation instructions and agent integration guidance

README.md

@@ -0,0 +1,265 @@
+<p align="center">
+ <img src="docs/figure/reme_logo.png" alt="ReMe Logo" width="50%">
+</p>
+
+<p align="center">
+  <a href="https://pypi.org/project/reme-ai/"><img src="https://img.shields.io/badge/python-3.11+-blue" alt="Python Version"></a>
+  <a href="https://pypi.org/project/reme-ai/"><img src="https://img.shields.io/pypi/v/reme-ai.svg?logo=pypi" alt="PyPI Version"></a>
+  <a href="https://pepy.tech/project/reme-ai/"><img src="https://img.shields.io/pypi/dm/reme-ai" alt="PyPI Downloads"></a>
+  <a href="https://github.com/agentscope-ai/ReMe"><img src="https://img.shields.io/github/commit-activity/m/agentscope-ai/ReMe?style=flat-square" alt="GitHub commit activity"></a>
+  <a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache--2.0-black" alt="License"></a>
+  <a href="./README.md"><img src="https://img.shields.io/badge/English-Click-yellow" alt="English"></a>
+  <a href="./README_ZH.md"><img src="https://img.shields.io/badge/简体中文-点击查看-orange" alt="简体中文"></a>
+  <a href="https://github.com/agentscope-ai/ReMe"><img src="https://img.shields.io/github/stars/agentscope-ai/ReMe?style=social" alt="GitHub Stars"></a>
+  <a href="https://deepwiki.com/agentscope-ai/ReMe"><img src="https://img.shields.io/badge/DeepWiki-Ask_Devin-navy.svg" alt="DeepWiki"></a>
+</p>
+
+<p align="center">
+<a href="https://trendshift.io/repositories/20528" target="_blank"><img src="https://trendshift.io/api/badge/repositories/20528" alt="agentscope-ai%2FReMe | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</p>
+
+<p align="center">
+  <strong>A memory management toolkit for AI agents — Remember Me, Refine Me.</strong><br>
+</p>
+
+> Previous versions: [0.3.x](https://github.com/agentscope-ai/ReMe/tree/reme_v3) ·
+> [0.2.x](https://github.com/agentscope-ai/ReMe/tree/v0.2.0.6) ·
+> [MemoryScope](https://github.com/agentscope-ai/ReMe/tree/memoryscope_branch)
+
+🧠 ReMe is a memory management toolkit for **AI agents**. It turns conversations and resources into readable, editable, and searchable file-based long-term memory.
+
+## ✨ Core Ideas
+
+- **Memory as File**: Markdown files with frontmatter and wikilinks serve as memory nodes that both users and agents can read and write directly.
+- **Self-evolving knowledge base**: Auto Memory, Auto Resource, and Auto Dream progressively transform conversations and resources into long-term Markdown memories, while automatically building wikilink relationships.
+- **Progressive hybrid search**: ReMe combines wikilinks, BM25, and embeddings for hybrid retrieval across keyword matching, semantic recall, and relationship expansion.
+- **Agent-friendly integration**: SKILL.md + CLI integration makes it easy for different agents to read, write, maintain, and reuse memory.
+
+## 🧭 Design Philosophy
+
+ReMe is built around three principles: store memory in readable and writable files, progressively abstract knowledge from raw materials into long-term memory, and organize knowledge with explicit links so agents can expand and reason over a relationship graph.
+
+- **Foundation: Memory as File**. ReMe does not lock long-term memory inside a black-box database or implicit prompt. It uses Markdown, JSONL, YAML, and resource files as the memory substrate. Files are knowledge assets that users can inspect, edit, and migrate, and they are also an operational interface that agents can read, write, index, and link.
+- **Core: progressive knowledge abstraction**. Raw conversations and resources are first stored in `session/` and `resource/`. `auto_memory` and `auto_resource` process them into shallow memories under `daily/`, and `auto_dream` then extracts, merges, and corrects them into long-term knowledge under `digest/`. This is not a one-shot summary; it is continuous accumulation from raw material, to lightly processed memory, to deeper knowledge.
+- **Innovation: from semantic similarity to relationship graphs**. ReMe uses wikilinks to express explicit knowledge relationships, so memories no longer depend only on embedding-based semantic similarity. They can also represent structured relationships such as causality, upstream/downstream links, sources, dependencies, and competition. For example, in financial scenarios, companies, industries, commodities, and events can be connected into upstream, downstream, impact, and risk chains, allowing agents to expand context from one matched node through the graph.
+
+<details>
+<summary><b>Use Cases</b></summary>
+
+<br>
+
+- **Personal assistants**: Provide long-term memory for agents such as [QwenPaw](https://github.com/agentscope-ai/QwenPaw).
+- **Coding assistants**: Preserve coding style, project background, and workflow experience across sessions.
+- **Knowledge QA**: Progressively transform resources and conversations into a searchable, traceable, and linked Markdown knowledge base.
+- **Task automation**: Reuse successful paths, lessons from failures, and operation procedures from past tasks.
+</details>
+
+## 🚀 Quick Start
+
+### Installation
+
+ReMe requires Python 3.11+.
+
+Install from pip:
+
+```bash
+pip install "reme-ai[core]"
+```
+
+Install from source:
+
+```bash
+git clone https://github.com/agentscope-ai/ReMe.git
+cd ReMe
+pip install -e ".[core]"
+```
+
+### Environment Variables
+
+Configure environment variables:
+
+```bash
+cat > .env <<'EOF'
+EMBEDDING_API_KEY=sk-xxx
+EMBEDDING_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
+LLM_API_KEY=sk-xxx
+LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
+EOF
+```
+
+### Start the Service
+
+```bash
+reme start
+```
+
+The default service address is `127.0.0.1:2333`. If the port is occupied, specify another port:
+
+```bash
+reme start service.port=8181
+# reme start vault_dir=/tmp/reme-demo service.port=8181
+```
+
+After startup, check the service status. If you use a custom port, replace `2333` in the URL below with that port.
+
+```bash
+reme version
+curl -s http://127.0.0.1:2333/version -H 'Content-Type: application/json' -d '{}'
+```
+
+### Agent Integration
+
+ReMe integrates with supported agent frameworks through **SKILL.md + CLI + hooks (optional)**. A typical integration looks like this:
+
+- Add the [memory skill](skills/reme_memory/SKILL.md) to the agent and grant the agent permission to call the CLI.
+- Call `auto_memory` and `proactive` from agent hooks as needed, so conversations are automatically consolidated into daily memories and proactive reminders can be read at the right time.
+- `auto_index` and `auto_resource` are triggered by file monitoring to maintain indexes and process resources.
+- `auto_dream` is triggered by a scheduled task to further organize daily memories into reusable long-term digest memories.
+
+QwenPaw 2.0 will integrate the new ReMe version. A Claude Code plugin will also be released later to reduce manual integration work.
+
+For more details, see the [Quick Start](docs/zh/quick_start.md).
+
+## 📁 Memory System
+
+> Memory as File, File as Memory.
+
+ReMe treats **memory as files**, progressively processing raw conversations and external resources from `session/` and `resource/` into `daily/`, then consolidating them into reusable long-term knowledge nodes under `digest/`.
+
+### Directory Structure
+
+```text
+<vault_dir>/
+├── metadata/       # Persistent system state such as indexes, graphs, and catalogs
+├── session/        # Raw conversations and agent sessions
+│   ├── dialog/
+│   │   └── <session_id>.jsonl
+│   ├── agentscope/
+│   └── claude_code/
+├── resource/            # External raw materials
+│   └── YYYY-MM-DD/
+│       └── <resource>.<ext>
+├── daily/               # Lightly processed memory: daily facts, conversation summaries, resource readings
+│   ├── YYYY-MM-DD.md
+│   └── YYYY-MM-DD/
+│       ├── <session_id>.md
+│       ├── <resource_stem>.md
+│       └── interests.yaml
+└── digest/              # Long-term memory: personal facts, procedural experience, knowledge nodes
+    ├── personal/
+    ├── procedure/
+    └── wiki/
+```
+
+<p align="center">
+  <img src="docs/figure/reme-overview.svg" alt="ReMe file-based memory system overview" width="92%">
+</p>
+
+### Automatic Memory Flow
+
+ReMe's automatic memory flow gradually turns raw conversations and resources into searchable, traceable, and reusable file-based memory. During normal operation, background watchers maintain indexes and process resources, agent hooks trigger conversation memory, and long-term consolidation plus proactive reminders run through scheduled tasks or on-demand calls.
+
+<details>
+<summary><b>Automatic Memory Capabilities</b></summary>
+
+<br>
+
+| Capability                                    | How it runs                                      | Purpose                                                                                                                                  | Main parameters                                      |
+|-----------------------------------------------|--------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------|
+| [`auto_index`](docs/zh/memory_search.md)      | Background maintenance via `index_update_loop`   | Scans on startup and continuously watches Markdown/JSONL changes in `daily/`, `digest/`, and `resource/`; updates chunk, BM25, embedding, and wikilink graph indexes. | Config: `watch_dirs`, `watch_suffixes`               |
+| [`auto_memory`](docs/zh/auto_memory.md)       | Agent after-reply hook; also callable on demand  | Saves raw conversation text and turns long-term valuable information into `daily/<date>/<session_id>.md` memory cards.                   | Required: `messages`; optional: `session_id`, `memory_hint` |
+| [`auto_resource`](docs/zh/auto_resource.md)   | Automatically triggered by resource watching; also callable on demand | Reads resource changes under `resource/<date>/` and creates or updates same-name daily resource cards.                                  | Required: `changes`; each item may include `path`, `file_path`, `change` |
+| [`auto_dream`](docs/zh/auto_dream.md)         | Scheduled by `dream_cron`; also callable on demand | Scans daily input for a given date, extracts long-term memory units, integrates them into `digest/`, and writes `daily/<date>/interests.yaml`. | `date`, `hint`, `topic_count`, `topic_diversity_days` |
+| [`proactive`](docs/zh/proactive.md)           | Read on demand before agent proactive reminders  | Reads `interests.yaml` generated by `auto_dream` and exposes topics worth attention to the upper-level agent; the caller decides whether to remind the user. | `date`, `include_content`                            |
+
+</details>
+
+<table>
+  <tr>
+    <td align="center" width="50%">
+      <img src="docs/figure/memory-as-file.svg" alt="Memory as File" width="100%">
+    </td>
+    <td align="center" width="50%">
+      <img src="docs/figure/auto-memory-resource.svg" alt="Auto Memory and Resource" width="100%">
+    </td>
+  </tr>
+  <tr>
+    <td align="center" width="50%">
+      <img src="docs/figure/auto-dream-and-proactive.svg" alt="Auto Dream and Proactive" width="100%">
+    </td>
+    <td align="center" width="50%">
+      <img src="docs/figure/auto-index-and-memory-search.svg" alt="Auto Index and Memory Search" width="100%">
+    </td>
+  </tr>
+</table>
+
+### Vault Operation Interface
+
+ReMe operates the vault through a unified CLI / Service Job interface. Agents usually only need retrieval, read, write, edit, and automatic memory commands. Lower-level indexing, frontmatter, and file operation commands are mainly for maintenance, debugging, or advanced integration.
+
+<details>
+<summary><b>Vault Operation Interface</b></summary>
+
+<br>
+
+| Category       | name                                 | Description                                                                 | Parameters                                             |
+|----------------|--------------------------------------|-----------------------------------------------------------------------------|--------------------------------------------------------|
+| System status  | `version`                            | Returns the ReMe package version.                                           | None                                                   |
+| System status  | `health_check`                       | Returns a health-check summary for ReMe components.                         | None                                                   |
+| System status  | `help`                               | Lists registered jobs and their metadata.                                   | None                                                   |
+| Retrieval/read | [`search`](docs/zh/memory_search.md) | Performs hybrid retrieval in the vault with vector recall, BM25, and RRF fusion. | Required: `query`; optional: `limit`, `min_score`      |
+| Retrieval/read | `node_search`                        | Recalls similar digest nodes by candidate abstraction name and description, mainly for `auto_dream` deduplication or association. | Required: `query`; optional: `limit`                   |
+| Retrieval/read | `traverse`                           | Traverses the wikilink graph from a specified path.                         | Required: `path`; optional: `depth`, `direction`       |
+| Retrieval/read | `read`                               | Reads a Markdown file under the vault.                                      | Required: `path`; optional: `start_line`, `end_line`   |
+| Retrieval/read | `read_image`                         | Reads an image file under the vault and returns base64.                     | Required: `path`                                      |
+| Index          | `reindex`                            | Clears file-store indexes and rebuilds indexes from existing files.         | Config: `watch_dirs`, `watch_suffixes`                 |
+| Daily          | `daily_create`                       | Creates a daily session note: `daily/<date>/<session_id>.md` or `daily/<date>.md`. | `session_id`, `date`                                  |
+| Daily          | `daily_list`                         | Lists notes for a day.                                                      | `date`                                                 |
+| Daily          | `daily_reindex`                      | Rebuilds the day-index page `daily/<date>.md`.                              | `date`                                                 |
+| Metadata       | `frontmatter_read`                   | Reads file frontmatter.                                                     | Required: `path`                                      |
+| Metadata       | `frontmatter_update`                 | Merges key-values into file frontmatter.                                    | Required: `path`, `metadata`                           |
+| Metadata       | `frontmatter_delete`                 | Deletes specified keys from file frontmatter.                               | Required: `path`, `keys`                               |
+| File operation | `stat`                               | Gets vault path status, including size, mtime, existence, and file/directory type. | Required: `path`                                      |
+| File operation | `list`                               | Lists files under a vault path.                                             | `path`, `recursive`, `limit`                           |
+| File operation | `write`                              | Creates or overwrites a Markdown file and writes name/description frontmatter. | Required: `path`, `name`, `description`, `content`; optional: `metadata` |
+| File operation | `edit`                               | Performs full-text find-and-replace on a Markdown file.                     | Required: `path`, `old`, `new`                         |
+| File operation | `move`                               | Moves or renames a vault file and rewrites inbound wikilinks by default.    | Required: `src_path`, `dst_path`; optional: `overwrite`, `retarget` |
+| File operation | `delete`                             | Deletes a vault file or folder and returns inbound wikilinks that still exist. | Required: `path`                                      |
+
+</details>
+
+## 🤝 Community and Support
+
+- **Issues and requests**: Check [Open Issues](https://github.com/agentscope-ai/ReMe/issues) first. If there is no related discussion, open a new issue with background, expected behavior, and impact scope.
+- **Code contributions**: Before making changes, read the [contribution guide](docs/zh/contributing.md) and [code framework](docs/zh/framework.md), and follow the CLI / Service / Application / Job / Step / Component layering.
+- **Documentation contributions**: For user-visible installation, configuration, invocation, or behavior changes, update `docs/zh/` or `README.md` accordingly.
+- **Commit convention**: Conventional Commits are recommended, for example `feat(search): add link expansion option` or `docs(zh): update quick start`.
+- **Pre-submit checks**: Before submitting a PR, try to run `pre-commit run --all-files` and `pytest`. If tests depending on LLMs, embeddings, or external services cannot run, explain that in the PR.
+- **Get help**: Use [GitHub Issues](https://github.com/agentscope-ai/ReMe/issues) for bugs and feature requests. Project documentation is available at [https://reme.agentscope.io/](https://reme.agentscope.io/).
+
+### Contributors
+
+Thanks to everyone who has contributed to ReMe:
+
+<a href="https://github.com/agentscope-ai/ReMe/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=agentscope-ai/ReMe" alt="Contributors" />
+</a>
+
+## 📄 Citation
+
+```bibtex
+@software{AgentscopeReMe2026,
+  title = {AgentscopeReMe: Memory Management Kit for Agents},
+  author = {ReMe Team},
+  url = {https://reme.agentscope.io},
+  year = {2026}
+}
+```
+
+## ⚖️ License
+
+This project is open source under the Apache License 2.0. See [LICENSE](./LICENSE) for details.
+
+## 📈 Star History
+
+[![Star History Chart](https://api.star-history.com/svg?repos=agentscope-ai/ReMe&type=Date)](https://www.star-history.com/#agentscope-ai/ReMe&Date)

README_ZH.md

@@ -22,27 +22,32 @@
   <strong>A memory management toolkit for AI agents — Remember Me, Refine Me.</strong><br>
 </p>
 
-> 历史版本：[0.3.x](https://github.com/agentscope-ai/ReMe/tree/v0.3.1.10) ·
+> 历史版本：[0.3.x](https://github.com/agentscope-ai/ReMe/tree/reme_v3) ·
 > [0.2.x](https://github.com/agentscope-ai/ReMe/tree/v0.2.0.6) ·
 > [MemoryScope](https://github.com/agentscope-ai/ReMe/tree/memoryscope_branch)
 
-🧠 ReMe 是一个面向 **AI 智能体** 的记忆管理工具，将对话、资料和长期知识沉淀为可读、可编辑、可检索的文件化记忆。
+🧠 ReMe 是一个面向 **AI 智能体** 的记忆管理工具，可将对话和资料沉淀为可读、可编辑、可检索的文件化长期记忆。
 
 ## ✨ 核心创新
 
-- **Memory as File**：以带 frontmatter 和 wikilink 的 Markdown 作为记忆节点，让人和 Agent 都能直接读写。
-- **自进化知识库**：通过 Auto Memory、Auto Resource、Auto Dream 和 Auto Link，把对话与资料逐步加工为长期 Markdown
-  记忆，并自动构建 wikilink 关系。
-- **渐进式混合搜索**：融合 wikilink、BM25 和 embedding，支持从关键词到语义与关系扩展的混合检索。
-- **Agent 友好集成**：通过 SKILL.md + CLI 接入，方便不同 Agent 读写、维护和复用记忆。
+- **Memory as File**：以带 frontmatter 和 wikilink 的 Markdown 作为记忆节点，让用户和 Agent 都能直接读写。
+- **自进化知识库**：通过 Auto Memory、Auto Resource 和 Auto Dream，把对话与资料逐步加工为长期 Markdown
+  记忆，并自动建立 wikilink 关系。
+- **渐进式混合搜索**：融合 wikilink、BM25 和 embedding，支持从关键词匹配到语义召回、关系扩展的混合检索。
+- **Agent 友好集成**：通过 SKILL.md + CLI 接入，方便不同 Agent 读写、维护与复用记忆。
 
 ## 🧭 设计理念
 
-ReMe 的设计围绕三件事展开：把记忆落到可读写的文件，把知识从原始材料渐进抽象为长期记忆，再用显式链接把知识组织成 Agent 可以展开和推理的关系图。
+ReMe 的设计围绕三件事展开：把记忆落到可读写的文件中，把知识从原始材料渐进抽象为长期记忆，再用显式链接把知识组织成可供 Agent
+展开和推理的关系图。
 
-- **基础：Memory as File**。ReMe 不把长期记忆锁在黑盒数据库或隐式 prompt 中，而是以 Markdown、JSONL、YAML 和资源文件承载记忆。文件既是用户可直接检查、修改和迁移的知识资产，也是 Agent 可读写、可索引、可链接的操作界面。
-- **核心：渐进式知识抽象**。原始对话和资料先保存在 `session/` 与 `resource/` 中，`auto_memory` 和 `auto_resource` 将它们加工为 `daily/` 中的浅层记忆，再由 `auto_dream` 抽取、合并和修正为 `digest/` 中的长期知识。这个过程不是一次性总结，而是从原始知识到浅加工、再到深加工的持续沉淀。
-- **创新：从语义相似到关系图谱**。ReMe 使用 wikilink 表达显式知识关系，让记忆之间不只依赖 embedding 的语义相似，还能表达因果、上下游、来源、依赖、竞争等结构化关系。例如在金融场景中，可以把企业、行业、商品和事件连接成上游、下游、影响和风险链路，支持 Agent 从一个命中节点沿图谱渐进式展开上下文。
+- **基础：Memory as File**。ReMe 不把长期记忆锁在黑盒数据库或隐式 prompt 中，而是使用 Markdown、JSONL、YAML
+  和资源文件承载记忆。文件既是用户可直接检查、修改和迁移的知识资产，也是 Agent 可读写、可索引、可链接的操作界面。
+- **核心：渐进式知识抽象**。原始对话和资料先保存在 `session/` 与 `resource/` 中，`auto_memory` 和 `auto_resource` 将它们加工为
+  `daily/` 中的浅层记忆，再由 `auto_dream` 抽取、合并和修正为 `digest/` 中的长期知识。这个过程不是一次性总结，而是从原始材料到浅加工记忆、再到深加工知识的持续沉淀。
+- **创新：从语义相似到关系图谱**。ReMe 使用 wikilink 表达显式知识关系，让记忆之间不再只依赖 embedding
+  的语义相似性，还能表达因果、上下游、来源、依赖、竞争等结构化关系。例如在金融场景中，可以把企业、行业、商品和事件连接成上游、下游、影响和风险链路，支持
+  Agent 从一个命中节点沿图谱渐进展开上下文。
 
 <details>
 <summary><b>适用场景</b></summary>
@@ -93,14 +98,14 @@ EOF
 reme start
 ```
 
-默认服务地址是 `127.0.0.1:2333`。如果端口被占用，可以指定其它端口：
+默认服务地址是 `127.0.0.1:2333`。如果端口被占用，可以指定其他端口：
 
 ```bash
 reme start service.port=8181
 # reme start vault_dir=/tmp/reme-demo service.port=8181
 ```
 
-启动后可以检查服务状态；如果使用了自定义端口，请把下面 URL 中的 `2333` 替换为对应端口。
+启动后可以检查服务状态；如果使用了自定义端口，请将下面 URL 中的 `2333` 替换为对应端口。
 
 ```bash
 reme version
@@ -108,9 +113,10 @@ curl -s http://127.0.0.1:2333/version -H 'Content-Type: application/json' -d '{}
 ```
 
 ### 快速接入
+
 ReMe 通过 **SKILL.md + CLI + hook（可选）** 接入支持的 Agent 框架。典型接入方式如下：
 
-- 为 Agent 添加 [memory skill](reme/skills/reme_memory/SKILL.md) ，并授予Agent 调用 CLI 的权限。
+- 为 Agent 添加 [memory skill](skills/reme_memory/SKILL.md)，并授予 Agent 调用 CLI 的权限。
 - 在 Agent hook 中按需调用 `auto_memory` 和 `proactive`，让对话自动沉淀为 daily 记忆，并在合适时机读取主动提醒。
 - `auto_index` 与 `auto_resource` 由文件监控自动触发，负责索引维护和资源加工。
 - `auto_dream` 由定时任务触发，将 daily 记忆进一步整理为可长期复用的 digest 记忆。
@@ -157,7 +163,8 @@ ReMe 将**记忆视为文件**，让原始对话和外部资料从 `session/`、
 
 ### 自动记忆流程
 
-ReMe 的自动记忆流程把原始对话和资料逐步加工成可检索、可追溯、可长期复用的文件化记忆。常规运行时，索引与资源处理由后台监听维护，对话记忆由 Agent hook 触发，长期整理与主动提醒则通过定时任务或按需调用完成。
+ReMe 的自动记忆流程会把原始对话和资料逐步加工成可检索、可追溯、可长期复用的文件化记忆。常规运行时，后台监听负责维护索引和处理资源，Agent
+hook 负责触发对话记忆，长期整理与主动提醒则通过定时任务或按需调用完成。
 
 <details>
 <summary><b>查看自动记忆能力表</b></summary>
@@ -170,7 +177,7 @@ ReMe 的自动记忆流程把原始对话和资料逐步加工成可检索、可
 | [`auto_memory`](docs/zh/auto_memory.md)     | Agent after-reply hook；也可按需调用 | 保存对话原文，并把有长期价值的信息整理成 `daily/<date>/<session_id>.md` 记忆卡片。                                               | 必填：`messages`；可选：`session_id`、`memory_hint`        |
 | [`auto_resource`](docs/zh/auto_resource.md) | 资源监听自动触发；也可按需调用               | 解读 `resource/<date>/` 下的资源变更，生成或更新同名 daily 资源卡片。                                                        | 必填：`changes`；每项可含 `path`、`file_path`、`change`      |
 | [`auto_dream`](docs/zh/auto_dream.md)       | 定时任务 `dream_cron`；也可按需调用      | 扫描指定日期的 daily 输入，抽取长期记忆单元并整合进 `digest/`，同时写入 `daily/<date>/interests.yaml`。                             | `date`、`hint`、`topic_count`、`topic_diversity_days` |
-| [`proactive`](docs/zh/proactive.md)         | Agent 主动提醒前按需读取               | 读取 `auto_dream` 生成的 `interests.yaml`，把当天值得关注的主题暴露给上层 Agent；是否提醒用户由调用方决定。                                | `date`、`include_content`                           |
+| [`proactive`](docs/zh/proactive.md)         | Agent 主动提醒前按需读取               | 读取 `auto_dream` 生成的 `interests.yaml`，将当天值得关注的主题暴露给上层 Agent；是否提醒用户由调用方决定。                                | `date`、`include_content`                           |
 
 </details>
 
@@ -195,7 +202,8 @@ ReMe 的自动记忆流程把原始对话和资料逐步加工成可检索、可
 
 ### Vault 操作接口
 
-ReMe 通过统一的 CLI / service job 接口操作 vault。Agent 通常只需要使用检索读取、写入编辑和自动记忆相关命令；更底层的索引、frontmatter 和文件操作接口主要用于维护、调试或高级集成。
+ReMe 通过统一的 CLI / Service Job 接口操作 vault。Agent 通常只需要使用检索、读取、写入、编辑和自动记忆相关命令；更底层的索引、frontmatter
+和文件操作接口主要用于维护、调试或高级集成。
 
 <details>
 <summary><b>查看 Vault 操作接口表</b></summary>
@@ -212,7 +220,7 @@ ReMe 通过统一的 CLI / service job 接口操作 vault。Agent 通常只需
 | 检索读取  | `traverse`                           | 从指定路径出发遍历 wikilink 图谱。                                                    | 必填：`path`；可选：`depth`、`direction`                       |
 | 检索读取  | `read`                               | 读取 vault 下的 Markdown 文件。                                                  | 必填：`path`；可选：`start_line`、`end_line`                   |
 | 检索读取  | `read_image`                         | 读取 vault 下的图片文件并返回 base64。                                                | 必填：`path`                                              |
-| 索引维护  | `reindex`                            | 清空 file store，并基于现有文件重建索引。                                                | 配置项：`watch_dirs`、`watch_suffixes`                      |
+| 索引维护  | `reindex`                            | 清空文件存储索引，并基于现有文件重建索引。                                                     | 配置项：`watch_dirs`、`watch_suffixes`                      |
 | Daily | `daily_create`                       | 创建 daily session note：`daily/<date>/<session_id>.md` 或 `daily/<date>.md`。 | `session_id`、`date`                                    |
 | Daily | `daily_list`                         | 列出某一天的 notes。                                                             | `date`                                                 |
 | Daily | `daily_reindex`                      | 重建 day-index 页面 `daily/<date>.md`。                                        | `date`                                                 |
@@ -239,7 +247,7 @@ ReMe 通过统一的 CLI / service job 接口操作 vault。Agent 通常只需
   `docs(zh): update quick start`。
 - **提交前检查**：提交 PR 前请尽量运行 `pre-commit run --all-files` 和 `pytest`；如有依赖 LLM、embedding 或外部服务的测试无法运行，请在
   PR 中说明。
-- **获取帮助**：Bugs 和功能请求使用 [GitHub Issues](https://github.com/agentscope-ai/ReMe/issues)，项目文档见
+- **获取帮助**：如需反馈 Bug 或功能请求，请使用 [GitHub Issues](https://github.com/agentscope-ai/ReMe/issues)；项目文档见
   [https://reme.agentscope.io/](https://reme.agentscope.io/)。
 
 ### 贡献者