SaladDay · Sep 29, 2026 · Sep 29, 2026 · Sep 29, 2026
diff --git a/README.md b/README.md
@@ -6,73 +6,68 @@
 
 An open-source, self-hosted implementation of the OpenAI Agents API with multiple native harnesses.
 
-[Get started](#quick-start) · [Documentation](#documentation) · [Call the API](docs/getting-started/quickstart.md) · [Contributing](CONTRIBUTING.md)
+[Install](#install) · [Call the API](docs/getting-started/quickstart.md) · [Documentation](#documentation) · [Contributing](CONTRIBUTING.md)
 
 **English** · [简体中文](README.zh-CN.md)
 
 </div>
 
-Choose Codex, Claude Code or MiniMax Code as your execution engine. Sandbox providers,
-model providers and harnesses connect through defined protocols and thin adapters,
-so you can add or replace components without changing Core orchestration.
+## What it is
 
-## Quick start
+OpenAgentCore runs AI agents on your own infrastructure behind the OpenAI Agents API.
 
-On a Linux amd64 host with Docker and Python 3.9+, install the latest stable release:
+- **Same API as OpenAI.** Point the official OpenAI SDK, or plain HTTP, at your
+  installation. No new client to learn.
+- **Your choice of agent.** Each Session runs a native harness: Codex, Claude Code or
+  MiniMax Code, with the model provider you configure.
+- **Your choice of machine.** Agents work in a managed sandbox (Docker, microsandbox
+  or E2B), or on your own Linux, macOS or Windows machine.
+- **Every part is replaceable.** Sandboxes, harnesses and model providers plug in
+  through defined protocols.
+
+## Install
+
+On a Linux amd64 host with Docker and Python 3.9+:
 
 ```sh
 curl -fsSL https://github.com/MiniMax-AI/parsar-core/releases/latest/download/install.sh | bash
 ```
 
-You can customize the listen address, ports and deployment settings with these [installation options](docs/getting-started/install-options.md).
+Then:
 
-1. [Install Core and Web](docs/getting-started/install.md) on a Linux host. The guide
-   covers prerequisites, release download, local trials and HTTPS setup.
-2. Sign in to Web with the installer-created Core key. Configure a model provider,
-   create a Project and issue its API key. For managed execution,
-   [add a node or configure E2B](docs/getting-started/nodes.md).
-3. [Run your first Session](docs/getting-started/quickstart.md) with the pinned Python
-   SDK. The walkthrough checks authentication, submits a task and waits for its result.
+1. **Sign in to Web**, the admin console, with the Core key the installer created.
+2. **Set a default model** and **issue a Project API key**.
+3. **Add execution capacity:** a node, E2B, or your own machine.
+4. **[Run your first Session](docs/getting-started/quickstart.md)** with the OpenAI SDK.
 
-To execute on your own Linux, macOS or Windows machine, follow the
-[self-hosted Runtime guide](docs/getting-started/self-hosted.md).
+The [installation guide](docs/getting-started/install.md) covers each step, HTTPS
+and a quick local trial. Listen addresses, ports and other options: [installation options](docs/getting-started/install-options.md).
 
 ## How it fits together
 
 ![OpenAgentCore architecture](docs/assets/architecture.png)
 
-Core exposes two APIs. Applications use the public **Agents API** (`/v1`), the same
-protocol as OpenAI's. Operators use the private **Core API** (`/core/v1`) through
-Web. Core manages Sessions and execution state. Runtime prepares Skills and MCP tools,
-then runs the selected harness. Sandbox providers manage environments; model providers
-serve inference requests. Each connection is a defined protocol, so any component
-can be replaced on its own.
+Core exposes two APIs:
 
-Managed Providers supply Linux environments. Self-hosted daemons run on Linux,
-macOS and Windows, subject to the selected Harness's
-[platform support](docs/self-hosted-native.md#platforms-and-prerequisites). The daemon uses
-its starting account's permissions; isolation belongs to an outer sandbox.
-Releasing an executor does not destroy its Environment.
+| API | Path | Used by |
+| --- | --- | --- |
+| **Agents API** | `/v1` | Your applications. Same protocol as OpenAI's |
+| **Core API** | `/core/v1` | Operators, through Web |
 
-See the [coverage record](contracts/agents-api/README.md) for supported API operations
-and native harness differences.
+Core keeps all state. The Runtime runs the chosen harness inside the Environment.
+Each connection is a defined protocol, so any part can be replaced on its own. See
+the [architecture guide](docs/architecture.md).
 
 ## Documentation
 
-For a complete application example using the Parsar product UI, see
-[`example/parsar`](example/parsar/README.md): model, Skill, MCP and runtime management, reusable Agents, and independent
-Sessions backed by the public API.
-
-| Start here | Purpose |
+| I want to | Start with |
 | --- | --- |
-| [Documentation index](docs/getting-started/README.md) | Installation, usage and administration reading paths |
-| [Architecture](docs/architecture.md) | Components, the three API namespaces and a Session end to end |
-| [User guide](docs/user-guide.md) | Sessions, Skills/Plugins/MCP, files, cancellation and recovery |
-| [Configuration](docs/configuration.md) | Operator settings and model configuration |
-| [API reference](docs/api/README.md) | Application, administration and machine APIs |
-| [Developer guide](docs/development.md) | Repository map, local setup, builds and validation |
-| [Add a Harness](contracts/agents-api/harness-onboarding.md) | Start with [agent/harness.go](apps/parsar-daemon/internal/agent/harness.go), then adapter implementation and acceptance |
-| [Core–Runtime protocol](docs/runtime-protocol.md) | Lifecycle, capability preparation and execution |
-| [Add a Sandbox Provider](docs/sandbox-provider.md) | Environment creation and resource ownership |
-
-Before changing code, read [the contributor rules](CONTRIBUTING.md).
+| Install and operate an installation | [Installation](docs/getting-started/install.md), then [operations](docs/getting-started/operations.md) |
+| Build an application on the API | [Quickstart](docs/getting-started/quickstart.md), then the [Agents API guide](docs/api/public-agent-api.md) |
+| See a complete application | [Examples](docs/examples.md) |
+| Run agents on my own machine | [Self-hosted execution](docs/getting-started/self-hosted.md) |
+| Understand the design | [Architecture](docs/architecture.md) |
+| Add a sandbox, harness or other component | [Developer guide](docs/development.md) |
+
+All pages: [documentation index](docs/getting-started/README.md). Before changing
+code, read the [contributor rules](CONTRIBUTING.md).
diff --git a/README.zh-CN.md b/README.zh-CN.md
@@ -6,62 +6,63 @@
 
 OpenAI Agents API 的开源实现，支持多种原生执行引擎，可部署在自己的基础设施上。
 
-[快速开始](#快速开始) · [文档](#文档) · [调用 API](docs/getting-started/quickstart.md) · [参与贡献](CONTRIBUTING.md)
+[安装](#安装) · [调用 API](docs/getting-started/quickstart.md) · [文档](#文档) · [参与贡献](CONTRIBUTING.md)
 
 [English](README.md) · **简体中文**
 
 </div>
 
-你可以选择 Codex、Claude Code 或 MiniMax Code 作为执行引擎。沙箱、模型供应商和
-Harness 都通过明确的协议和薄适配层接入，新增或替换组件无需修改 Core 的编排逻辑。
+## 这是什么
 
-## 快速开始
+OpenAgentCore 在你自己的基础设施上运行 AI Agent，对外提供 OpenAI Agents API。
 
-在已准备 Docker 和 Python 3.9+ 的 Linux amd64 主机上，一条命令安装最新正式版：
+- **与 OpenAI 相同的 API。** 官方 OpenAI SDK 或直接 HTTP 调用，改一下地址即可，无需学习新客户端。
+- **自选 Agent。** 每个 Session 运行一个原生 Harness：Codex、Claude Code 或 MiniMax Code，
+  使用你配置的模型供应商。
+- **自选机器。** Agent 可以在托管沙箱（Docker、microsandbox 或 E2B）里工作，
+  也可以在你自己的 Linux、macOS 或 Windows 机器上工作。
+- **每个部件都可替换。** 沙箱、Harness 和模型供应商都通过既定协议接入。
+
+## 安装
+
+在已准备 Docker 和 Python 3.9+ 的 Linux amd64 主机上：
 
 ```sh
 curl -fsSL https://github.com/MiniMax-AI/parsar-core/releases/latest/download/install.sh | bash
 ```
 
-你可以通过[安装配置选项](docs/getting-started/install-options.md)自定义监听地址、端口和部署方式。
+然后：
 
-1. 在 Linux 主机上[安装 Core 和 Web](docs/getting-started/install.md)。安装指南包含环境要求、
-   发行包下载、本地试用和 HTTPS 配置。
-2. 用安装器生成的 Core key 登录 Web，配置模型提供方，创建 Project 并签发应用 API key。
-   使用托管环境时，先[添加节点或配置 E2B](docs/getting-started/nodes.md)。
-3. 跟随[第一个 Session 示例](docs/getting-started/quickstart.md)，安装指定版本的 Python SDK，
-   验证访问、提交任务并等待执行结果。
+1. 用安装器生成的 Core key **登录 Web**（管理控制台）。
+2. **设置默认模型**，并**签发 Project API key**。
+3. **添加执行资源**：节点、E2B，或你自己的机器。
+4. 用 OpenAI SDK **[运行第一个 Session](docs/getting-started/quickstart.md)**。
 
-要在自己的 Linux、macOS 或 Windows 机器上执行任务，请阅读
-[自托管 Runtime 指南](docs/getting-started/self-hosted.md)。
+[安装指南](docs/getting-started/install.md)详细介绍每一步，以及 HTTPS 配置和本地快速试用。监听地址、端口等参数见[安装配置选项](docs/getting-started/install-options.md)。
 
 ## 组件关系
 
 ![OpenAgentCore 架构](docs/assets/architecture.png)
 
-Core 对外提供两组 API：应用调用公开的 **Agents API**（`/v1`），与 OpenAI 协议一致；
-管理员通过 Web 调用私有的 **Core API**（`/core/v1`）。Core 管理 Session 和执行状态；
-Runtime 准备 Skill 和 MCP 工具并运行所选引擎；沙箱供应商管理运行环境，模型供应商提供推理服务。
-各部件之间都通过既定协议连接，任何一个都可以单独替换。
+Core 对外提供两组 API：
 
-托管 Provider 提供 Linux 环境；自托管 daemon 支持 Linux、macOS 和 Windows，
-具体组合见 [Harness 平台支持表](docs/self-hosted-native.md#platforms-and-prerequisites)。
-daemon 使用启动账户的权限，隔离由外层沙箱负责。释放执行器不会销毁 Environment。
+| API | 路径 | 调用方 |
+| --- | --- | --- |
+| **Agents API** | `/v1` | 你的应用，与 OpenAI 协议一致 |
+| **Core API** | `/core/v1` | 管理员，通过 Web 调用 |
 
-已支持的 API 操作和原生引擎差异见[协议覆盖记录](contracts/agents-api/README.md)。
+所有状态都由 Core 保存；Runtime 在 Environment 中运行所选 Harness。各部件之间都通过既定协议连接，
+任何一个都可以单独替换。详见[架构说明](docs/architecture.md)。
 
 ## 文档
 
-| 入口 | 内容 |
+| 我想要 | 从这里开始 |
 | --- | --- |
-| [文档目录](docs/getting-started/README.md) | 安装、使用和运维的阅读路径 |
-| [架构](docs/architecture.md) | 各组件、三组 API 与一个 Session 的完整流程 |
-| [使用指南](docs/user-guide.md) | Session、Skill/Plugin/MCP、文件、取消与恢复 |
-| [配置参考](docs/configuration.md) | 部署设置和模型配置 |
-| [API 参考](docs/api/README.md) | 应用、管理与机器接口 |
-| [开发指南](docs/development.md) | 仓库结构、开发环境、构建与验证 |
-| [接入 Harness](contracts/agents-api/harness-onboarding.md) | 适配器实现与验收 |
-| [Core–Runtime 协议](docs/runtime-protocol.md) | 生命周期、能力准备与执行 |
-| [接入 Sandbox Provider](docs/sandbox-provider.md) | 环境创建与资源管理 |
-
-修改代码前请阅读[贡献规范](CONTRIBUTING.md)。
+| 安装并运维 | [安装指南](docs/getting-started/install.md)，然后看[运维](docs/getting-started/operations.md) |
+| 基于 API 开发应用 | [快速开始](docs/getting-started/quickstart.md)，然后看 [Agents API 指南](docs/api/public-agent-api.md) |
+| 看一个完整的应用 | [示例](docs/examples.md) |
+| 在自己的机器上运行 Agent | [自托管执行](docs/getting-started/self-hosted.md) |
+| 了解设计 | [架构说明](docs/architecture.md) |
+| 接入新的沙箱、Harness 或其他组件 | [开发指南](docs/development.md) |
+
+全部文档见[文档目录](docs/getting-started/README.md)。修改代码前请阅读[贡献规范](CONTRIBUTING.md)。
diff --git a/apps/docs/content/docs/bootstrap-projects-keys.mdx b/apps/docs/content/docs/bootstrap-projects-keys.mdx
@@ -67,18 +67,9 @@ and display only. Keep deployment, application, node and provider credentials ou
 
 ## Projects and application keys
 
-Installation creates no Project or application key. An administrator creates a
-Project and issues named keys on the console's **Projects and keys** page, which
-uses the [administrator API](https://github.com/MiniMax-AI/parsar-core/blob/f45a4198aca79bf252412c55cad3647f5d704515/contracts/agents-api/admin-api.md), or with that
-API directly.
-The Project owns one tenant and one principal; its keys share assets and permissions.
-Writes retain each key's provenance. All Projects and application keys live in
-PostgreSQL, independently of deployment configuration.
-
-Issuance returns plaintext once; Core stores its digest. Deliver the new key to the
-application privately. Rotate by issuing a replacement in the same Project and
-revoking the old key. Archive disables every key while retaining assets and admitted
-work. Ordinary metadata reads cannot recover plaintext.
+Installation creates no Project or key. Create them on **Projects and keys** or
+through the [administrator API](https://github.com/MiniMax-AI/parsar-core/blob/f45a4198aca79bf252412c55cad3647f5d704515/contracts/agents-api/admin-api.md); see
+[Projects and API keys](/troubleshooting#projects-and-api-keys).
 
 ## Verification and diagnosis