docs: clarify that frontend source is not in this public repo

CLAUDE.md

@@ -4,7 +4,7 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
 
 ## Project Overview
 
-Sico is an open-source AI agent platform with three main services that communicate via gRPC and a bidirectional "reverse RPC" pattern. The backend handles HTTP APIs and persistence, the core handles AI/LLM orchestration, and the frontend provides a React dashboard.
+Sico is an open-source AI agent platform with three main services that communicate via gRPC and a bidirectional "reverse RPC" pattern. The backend handles HTTP APIs and persistence, the core handles AI/LLM orchestration, and the frontend provides a React dashboard (frontend codebase is not opensourced). 
 
 ## Build & Run Commands
 
@@ -41,19 +41,6 @@ uv run ruff format .           # format
 ```
 Requires Python >=3.13. Uses `uv` for dependency management (pyproject.toml + uv.lock).
 
-### Frontend (React + pnpm)
-```bash
-cd frontend
-pnpm install                   # install dependencies
-pnpm dev                       # start dev server (vite)
-pnpm build                     # production build (tsc -b && vite build)
-pnpm lint                      # eslint
-pnpm lint:fix
-pnpm format                    # prettier
-pnpm format:check
-```
-Single-package React app (package name `sico-frontend`, private). Uses Vite + Tailwind + styled-components + React Router. TypeScript path alias `@` → `frontend/src/`.
-
 ### Protobuf Code Generation
 All `.proto` files live in `proto/`. Generation scripts are run from the `proto/` directory:
 ```bash
@@ -121,14 +108,6 @@ Key patterns:
 - **`app/pb/`** — Auto-generated protobuf/betterproto2 stubs (do not edit manually).
 - **`app/utils/`** — Shared utilities: Redis, caching, eventbus, response builders.
 
-### Frontend Structure (TypeScript/React — `frontend/`)
-
-- Single-package React app rooted at `frontend/` (not a monorepo). Package name `sico-frontend`, private, managed with pnpm.
-- **`src/`** — app source: `pages/`, `components/`, `api/`, `hooks/`, `utils/`, `assets/`; `App.tsx` + `main.tsx` + `PlatformRouter.tsx` entry.
-- **`public/`** — static assets (includes `pdfjs/` worker).
-- **`proto-types/src/`** — generated TS types from protobuf (do not edit manually; emitted by `bash gen.sh` in `proto/`).
-- Uses Vite, Tailwind CSS, styled-components, React Router, and `@` path alias mapped to `src/`.
-
 ### Sandbox System
 
 The sandbox subsystem manages isolated environments (Android emulators, AIO containers) for agent tool execution. Sandboxes are pooled and leased to agent instances. The `sandbox/emulator/` directory contains the Android emulator sandbox implementation (Python).

README.md

@@ -196,7 +196,6 @@ make kind-down                  # tear down and delete local cluster data
 sico/
 ├── backend/              # Go HTTP + gRPC service (Gin, GORM, Wire)
 ├── core/                 # Python agent orchestration service (asyncio, grpclib)
-├── frontend/             # Packaged/deployment frontend assets (source package is separate)
 ├── proto/                # Protobuf definitions shared by all services
 ├── sandbox/              # Sandbox runtimes (Android emulator, ...)
 ├── skills/               # Packaged Digital Worker skills

docs/technical_report.md

@@ -129,7 +129,7 @@ Sico separates AI orchestration from data persistence with a protobuf-driven gRP
 |---------|----------|-----------|---------------|
 | **Backend** | Go | Gin | HTTP API gateway, JWT/Casbin auth for operator-facing APIs, sandbox-client HMAC auth, data persistence, reverse gRPC server |
 | **Core** | Python | asyncio | Agent orchestration, LLM invocation, tool execution, Experience Learning; no direct MySQL access, with runtime state in workspace files and memory/vector stores |
-| **Frontend** | - | - | Operator-facing web client for human users (not open source) |
+| **Frontend** | TypeScript | React / Vite | Operator-facing web client for human users; source code is not currently published in this repository and is distributed separately as a packaged archive |
 
 Sico uses two services because AI orchestration and platform responsibilities evolve at different speeds and benefit from different runtimes. The Backend service is implemented in Go for high-throughput HTTP handling. The Core service is implemented in Python to support rapid iteration across the AI/LLM ecosystem. This separation decouples deployment cycles and allows each service to optimize for its primary workload.