diff --git a/docs/source/en/user_guide/getting_started/installation.md b/docs/source/en/user_guide/getting_started/installation.md
index 78b6cf81..431fef3f 100644
--- a/docs/source/en/user_guide/getting_started/installation.md
+++ b/docs/source/en/user_guide/getting_started/installation.md
@@ -49,7 +49,7 @@ Install the runtime environment from the repository root (on Windows, run `insta
 sh install.sh
 ```
 
-This auto-detects your GPU vendor (NVIDIA → CUDA, AMD → ROCm) and installs the runtime workspace packages, the matching PyTorch wheels, the required SKRL Torch provider, and the built-in FastSAC algorithm. Runtime installation is selective: development tools, docs, RSL-RL, SKRL JAX, and other optional extras are not installed unless requested.
+This auto-detects your GPU vendor (NVIDIA → CUDA, AMD → ROCm) and installs the runtime workspace packages, the matching PyTorch wheels, the required SKRL Torch provider, and the built-in FastSAC algorithm. On Linux, `install.sh` also installs Intel TBB by default for Numba parallel kernels, including with `--all` and either GPU profile. Other platforms do not enable TBB by default for runtime installation. Development tools, docs, RSL-RL, SKRL JAX, and other optional extras are not installed unless requested.
 
 ### Activate the Environment
 
@@ -96,7 +96,7 @@ workspace packages and supported development extras. Backend flags select or add
 | `--skrl-torch` | — | Compatibility flag; SKRL Torch is already required by the root package |
 | `--skrl-jax` | — | Add SKRL on JAX backend, Linux only |
 | `--rslrl` | — | Add RSL-RL on PyTorch backend while retaining required SKRL |
-| `--tbb` | — | Install Intel TBB for the numba parallel kernels; recommended for training on many-core servers (64+ cores), auto-activates once installed |
+| `--tbb` | — | Explicitly install Intel TBB for Numba parallel kernels; already enabled by default in `install.sh` on Linux, auto-activates once installed |
 | `--docs` | — | Add the toolchain (sphinx) needed to build the documentation locally |
 | `-h`, `--help` | — | Show the help message |
 
diff --git a/docs/source/zh_CN/user_guide/getting_started/installation.md b/docs/source/zh_CN/user_guide/getting_started/installation.md
index 269efa23..ae08b9f8 100644
--- a/docs/source/zh_CN/user_guide/getting_started/installation.md
+++ b/docs/source/zh_CN/user_guide/getting_started/installation.md
@@ -50,7 +50,7 @@ sh install.sh
 ```
 
 该命令会自动探测 GPU 厂商（NVIDIA → CUDA，AMD → ROCm），安装运行环境所需的 workspace package、对应的
-PyTorch wheel、必需的 SKRL Torch provider 以及内置的 FastSAC 算法。运行环境采用选择性安装：开发工具、文档工具、RSL-RL、SKRL JAX 和其他可选 extra 不会自动安装。
+PyTorch wheel、必需的 SKRL Torch provider 以及内置的 FastSAC 算法。Linux 上，`install.sh` 默认还会为 Numba 并行 kernel 安装 Intel TBB，`--all` 和两种 GPU 配置均包含 TBB；其他平台的默认运行环境安装不会启用 TBB。开发工具、文档工具、RSL-RL、SKRL JAX 和其他可选 extra 不会自动安装。
 
 :::{dropdown} 配置国内镜像源（可选）
 :animate: fade-in
@@ -116,7 +116,7 @@ workspace plugin；`--all` 才会安装全部 workspace package 与支持的开
 | `--skrl-torch` | — | 兼容性参数；SKRL Torch 已由根项目作为必需依赖提供 |
 | `--skrl-jax` | — | 添加 SKRL（JAX）训练后端，仅 Linux |
 | `--rslrl` | — | 添加 RSL-RL（PyTorch）训练后端，同时保留必需的 SKRL |
-| `--tbb` | — | 为 numba 并行 kernel 安装 Intel TBB 线程层；多核服务器（64 核以上）训练推荐启用，安装后自动生效 |
+| `--tbb` | — | 显式为 Numba 并行 kernel 安装 Intel TBB 线程层；Linux 上的 `install.sh` 已默认启用，安装后自动生效 |
 | `--docs` | — | 追加本地构建文档所需的工具链（Sphinx） |
 | `-h`、`--help` | — | 显示帮助 |
 
diff --git a/install.sh b/install.sh
index e2755669..b48bacbe 100755
--- a/install.sh
+++ b/install.sh
@@ -11,8 +11,9 @@
 #
 # Built-in FastSAC and SKRL on Torch are always installed. --skrl-jax adds
 # the JAX runtime, and --rslrl adds the RSLRL plugin; multiple flags combine.
-# --tbb installs Intel TBB so numba parallel kernels use its threading layer
-# (avoids the OpenMP per-region thread-wakeup storm on many-core hosts).
+# Linux installs Intel TBB by default so numba parallel kernels use its threading
+# layer (avoids the OpenMP per-region thread-wakeup storm on many-core hosts).
+# --tbb remains available to explicitly request TBB on other platforms.
 
 set -e
 
@@ -27,7 +28,7 @@ usage() {
     echo "  --skrl-torch           Training backend: SKRL on PyTorch (default)"
     echo "  --skrl-jax             Training backend: SKRL on JAX (Linux only)"
     echo "  --rslrl                Training backend: RSL-RL on PyTorch"
-    echo "  --tbb                  Install Intel TBB for numba parallel kernels (recommended on many-core hosts)"
+    echo "  --tbb                  Install Intel TBB for numba parallel kernels (default on Linux)"
     echo "  -h, --help             Show this help"
 }
 
@@ -142,6 +143,7 @@ if [ -z "$GPU" ]; then
 fi
 
 case "$(uname -s 2>/dev/null)" in
+    Linux) IS_WINDOWS=""; TBB=1 ;;
     MINGW*|MSYS*|CYGWIN*) IS_WINDOWS=1 ;;
     *) IS_WINDOWS="" ;;
 esac
@@ -151,10 +153,13 @@ if [ "$GPU" = rocm ] && [ -n "$IS_WINDOWS" ]; then
     exit 1
 fi
 
+TBB_EXTRA=""
+[ -n "$TBB" ] && TBB_EXTRA=" --extra tbb"
+
 if [ -n "$ALL" ]; then
     if [ "$GPU" = rocm ]; then
         set -x
-        uv sync --all-packages --all-groups --extra rocm --extra rslrl --extra unitree --extra docs
+        uv sync --all-packages --all-groups --extra rocm --extra rslrl --extra unitree --extra docs$TBB_EXTRA
     else
         set -x
         uv sync --all-packages --all-groups --all-extras --no-extra rocm
@@ -164,7 +169,7 @@ else
     [ -n "$SKRL_JAX" ] && EXTRAS="$EXTRAS --extra skrl-jax"
     [ -n "$RSLRL" ] && EXTRAS="$EXTRAS --extra rslrl"
     [ -n "$DOCS" ] && EXTRAS="$EXTRAS --extra docs"
-    [ -n "$TBB" ] && EXTRAS="$EXTRAS --extra tbb"
+    EXTRAS="$EXTRAS$TBB_EXTRA"
     set -x
     uv sync --no-default-groups --extra "$GPU"$EXTRAS
 fi