diff --git a/README.md b/README.md
index db883f0aba7359869b67c284e0129c57a5e07a57..71549395ed7d7d35b3e1bf899894fdff1d02a6b2 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,5 @@
 ---
-pretty_name: Value Model Benchmark Training Data
+pretty_name: RoboValue Training and Evaluation Data
 language:
 - en
 - zh
@@ -9,16 +9,28 @@ tags:
 - robovalue
 - value-model-benchmark
 - training-data
+- evaluation-data
+- diagnostic-test-set
 - simulation
 - real-world
 - full-shot
 - one-shot
+configs:
+- config_name: real-world-test-30
+  default: true
+  data_files:
+  - split: test
+    path: evaluation/real-world/test-30/episode_catalog.parquet
+- config_name: simulation-test-30
+  data_files:
+  - split: test
+    path: evaluation/simulation/test-30/episode_catalog.parquet
 ---
 
 <div align="center">
   <img src="https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/resolve/main/assets/robovalue-logo.png" alt="RoboValue" width="420" />
-  <h1>Training Data for Robotic Value Models</h1>
-  <p><strong>Simulation &amp; Real-World · Full-Shot &amp; One-Shot</strong></p>
+  <h1>RoboValue Training and Evaluation Data</h1>
+  <p><strong>Training Demonstrations · Small-Scale Real-World &amp; Simulation Public Test Sets</strong></p>
   <p>
     <a href="https://arxiv.org/abs/2610.26663"><img src="https://img.shields.io/badge/arXiv-Paper-red?logo=arxiv" alt="RoboValue paper on arXiv" /></a>
     <a href="https://github.com/RoboValue-Benchmark/RoboValue"><img src="https://img.shields.io/badge/GitHub-RoboValue-24292F?logo=github" alt="RoboValue GitHub" /></a>
@@ -30,10 +42,10 @@ tags:
 
 RoboValue provides expert demonstrations for **robotic value models**, covering **15 simulation tasks** and **20 real-world tasks**. Both domains offer Full-Shot and One-Shot subsets in the shared **LeRobot Dataset v3.0** format.
 
-All four training subsets are publicly available. [The paper](https://arxiv.org/abs/2610.26663) and current leaderboard report **Zero-Shot and One-Shot evaluations**.
+All four training subsets are publicly available. Two **small-scale public diagnostic test sets** are organized separately under `evaluation/`, with **30 real-world trajectories and 30 simulation trajectories**. Each domain has four tasks and 90 synchronized camera videos. Together the test subsets contain **60 trajectories, 44,647 time steps, and 180 videos**. [The paper](https://arxiv.org/abs/2610.26663) and current leaderboard report **Zero-Shot and One-Shot evaluations**.
 
 <p align="center">
-  <a href="#overview">Overview</a> · <a href="#simulation">Simulation</a> · <a href="#real-world">Real-World</a> · <a href="#repository-layout">Repository</a> · <a href="#download-and-reading">Download &amp; Read</a>
+  <a href="#overview">Overview</a> · <a href="#simulation">Simulation</a> · <a href="#real-world">Real-World Training</a> · <a href="#public-evaluation">Public Test Sets</a> · <a href="#repository-layout">Repository</a> · <a href="#download-and-reading">Download &amp; Read</a>
 </p>
 
 ## 📊 1. Dataset Overview <a name="overview"></a>
@@ -48,11 +60,36 @@ All four training subsets are publicly available. [The paper](https://arxiv.org/
 | ▦ **Full-Shot** | 100 per task | Training or fine-tuning on the complete expert collection |
 | ◉ **One-Shot** | 1 per task | Reference conditioning or task-specific adaptation |
 
-Across all four subsets, the release contains **3,535 episodes, 2,348,375 synchronized time steps, and 10,605 camera videos**. The two One-Shot subsets account for **35 episodes, 24,442 time steps, and 105 camera videos**.
+Across all four training subsets, the release contains **3,535 episodes, 2,348,375 synchronized time steps, and 10,605 camera videos**. The two One-Shot subsets account for **35 episodes, 24,442 time steps, and 105 camera videos**.
 
-> **HF preview:** The automatic preview counts video files as rows, including one showcase clip. Use the episode and time-step totals here and the [LeRobot loader](#download-and-reading) for training.
 
-## 🟦 2. Simulation <a name="simulation"></a>
+> **HF preview:** The explicit `real-world-test-30/test` and `simulation-test-30/test` configurations each contain **one row per test trajectory (30 rows)**. Select a configuration to browse its task, trajectory type, applicable metrics, and three camera video paths. Real-world is the default. These catalogs are browsing indices; native per-frame model input is read with LeRobot. Auxiliary JSON reports and navigation documents are excluded from the preview.
+
+### Public Test Sets <a name="public-evaluation"></a>
+
+Training demonstrations and public test trajectories have separate directories and purposes:
+
+| Collection | Location | Scale | Purpose |
+| --- | --- | --- | --- |
+| Simulation / real-world training | `data/<domain>/{full-shot,one-shot}` | Four training subsets listed above | Expert demonstrations for training or reference conditioning |
+| [Real-world public test set](evaluation/real-world/test-30/README.md) | `evaluation/real-world/test-30` | **4 tasks / 30 trajectories / 27,498 time steps / 90 videos** | Small-scale In-Domain diagnostic evaluation |
+| [Simulation public test set](evaluation/simulation/test-30/README.md) | `evaluation/simulation/test-30` | **4 tasks / 30 trajectories / 17,149 time steps / 90 videos** | Small-scale In-Domain diagnostic evaluation |
+
+The real-world subset contains **12 desk**, **12 flower-and-diffuser**, **3 drum**, and **3 button** trajectories. The simulation subset contains **12 pen-holder**, **12 mug-hanging**, **3 press-by-number**, and **3 block-swapping** trajectories. Both supply images and English instructions, with evaluation annotations stored separately. Each subset has its own local task and episode indices, independent of training and of the other test subset. They provide partial diagnostic coverage rather than a complete leaderboard test release.
+
+| Coverage | Real-world | Simulation |
+| --- | --- | --- |
+| TGA-CT, TGA-CF, VOC, Cycle-VOC, VS | Each uses 4 ED episodes | Each uses 4 ED episodes |
+| SA / SIA | 24 / 12 episodes | 24 / 12 episodes |
+| TRR | 12 episodes / 4 three-role groups | 12 episodes / 4 three-role groups |
+| CSVC | 12 episodes / 10 solution groups | 12 episodes / 6 order groups |
+| FPL | 8 ER/EC episodes | Original FPL fields retained; no formal FPL cohort |
+| VOC-MEM | 6 complete counting histories | 6 complete memory histories; no annotated counting-subtask intervals |
+
+See the [real-world metric coverage and trajectory index](evaluation/real-world/test-30/README.md#metric-coverage) and [simulation metric coverage and trajectory index](evaluation/simulation/test-30/README.md#metric-coverage). Simulation ED/MS terminal labels and semantic alignment are user-attested; TRR/MEM terminal-label evidence retains the source status of pending independent verification. The simulation README documents these annotation evidence states.
+
+
+## 🟦 2. Simulation Training <a name="simulation"></a>
 
 ### 2.1 Overview
 
@@ -166,7 +203,7 @@ Loaded images use **CHW (channels, height, width)** order.
 
 **Subtask annotations:** [58 paper-defined segments](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/annotations/subtasks/README.md) label all **8,080 frames**, with one subtask per frame. These annotations accompany the training demonstrations and are separate from benchmark test-set labels. [`dataset_labeler`-compatible JSON](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145/data/simulation/one-shot/annotations/subtasks/dataset_labeler) uses the same subtasks and boundaries as the frame labels.
 
-## 🟧 3. Real-World <a name="real-world"></a>
+## 🟧 3. Real-World Training <a name="real-world"></a>
 
 ### 3.1 Overview
 
@@ -316,12 +353,23 @@ data/
 └── real-world/
     ├── full-shot/                2,000 episodes · 20 tasks
     └── one-shot/                 20 episodes · 1 per task
+evaluation/
+├── simulation/test-30/           30 trajectories · 4 tasks
+│   └── meta/, data/, videos/, annotations/, README files and catalog
+└── real-world/test-30/            30 trajectories · 4 tasks
+    ├── meta/                     Native LeRobot v3 metadata
+    ├── data/                     Frame references
+    ├── videos/                   Three synchronized camera streams
+    ├── annotations/              Separate evaluation labels
+    ├── episode_catalog.parquet   One browsing row per trajectory
+    ├── README.md / README_zh.md   Task and metric documentation
+    └── checksums.sha256           File integrity manifest
 ```
 
-Each subset directory is an independent **LeRobot** dataset root (`root`), containing per-step Parquet data, three original camera streams, and metadata.
+Each released training or public test subset directory is an independent **LeRobot** dataset root (`root`). Both test subsets have frame references, RGB videos, and English instructions, with evaluation labels alongside them; they have no robot state/action vectors. The primary view is the head camera for real-world and the front camera for simulation.
 
 <details>
-<summary><strong>Subset files and metadata</strong></summary>
+<summary><strong>Training subset files and metadata</strong></summary>
 
 | File or directory | Purpose |
 | --- | --- |
@@ -352,10 +400,12 @@ Select one `prefix` to download only that subset. Sizes use decimal GB.
 | 🟦 **Simulation One-Shot** | `data/simulation/one-shot` | 15 / 8,080 | ≈0.50 GB |
 | 🟧 **Real-World Full-Shot** | `data/real-world/full-shot` | 2,000 / 1,534,321 | ≈23.13 GB |
 | 🟧 **Real-World One-Shot** | `data/real-world/one-shot` | 20 / 16,362 | ≈0.22 GB |
+| **Real-World Public Test** | `evaluation/real-world/test-30` | 30 / 27,498 | ≈0.38 GB |
+| **Simulation Public Test** | `evaluation/simulation/test-30` | 30 / 17,149 | ≈0.595 GB |
 
 ### 5.2 Download and read
 
-This example loads the smaller **Simulation One-Shot** subset and returns states, actions, and all three camera frames. To switch subsets, change `prefix` to the corresponding path in the table. Public data can be downloaded anonymously, and this example automatically reuses an existing local Hugging Face login. If anonymous downloads are rate-limited, run `hf auth login` and retry.
+This example loads the smaller **Simulation One-Shot** subset and returns states, actions, and all three camera frames. To switch training subsets, change `prefix` to the corresponding training path in the table. For the public test set, use the separate image-and-instruction example below. Public data can be downloaded anonymously, and this example automatically reuses an existing local Hugging Face login. If anonymous downloads are rate-limited, run `hf auth login` and retry.
 
 The examples were tested with **Python 3.12**, **LeRobot 0.4.2**, and **PyAV 15.1.0**:
 
@@ -473,4 +523,35 @@ Each subset contains `checksums.sha256`. Run this command from the subset direct
 shasum -a 256 -c checksums.sha256
 ```
 
+### 5.5 Download and read a public test subset
+
+Choose `evaluation/real-world/test-30` or `evaluation/simulation/test-30` to download one public test subset. The example is pinned to `578593ef28ee7a2d861ebf38162c928291b0d4a9`, which contains both test domains; downloading and loading use the same revision. The original training-data revision shown above predates this test release.
+
+```python
+from pathlib import Path
+from huggingface_hub import snapshot_download
+from lerobot.datasets.lerobot_dataset import LeRobotDataset
+
+repo_id = "wzlllong/value-model-benchmark-training-data"
+prefix = "evaluation/real-world/test-30"
+revision = "578593ef28ee7a2d861ebf38162c928291b0d4a9"
+snapshot = snapshot_download(
+    repo_id=repo_id, repo_type="dataset", revision=revision,
+    allow_patterns=[f"{prefix}/**"], local_dir="./robovalue-data",
+)
+root = Path(snapshot) / prefix
+dataset = LeRobotDataset(
+    repo_id=repo_id, root=root, revision=revision,
+    video_backend="pyav", tolerance_s=1e-4,
+)
+sample = dataset[0]
+value_input = {
+    "images": {camera: sample[camera] for camera in dataset.meta.camera_keys},
+    "instruction": sample["task"],
+}
+print(dataset.num_episodes, dataset.num_frames)  # real-world: 30 27498; simulation: 30 17149
+```
+
+The native metadata retains `train: 0:30` as its LeRobot container split. Both public test subsets are intended for **testing**, and the HF browsing index uses the semantic `test` split. Load evaluation annotations explicitly from `root / "annotations"`; do not pass labels, success flags, trajectory types, metric memberships, or frame references to the model. History-based models can use `delta_timestamps` within each episode. See the [real-world README](evaluation/real-world/test-30/README.md) or [simulation README](evaluation/simulation/test-30/README.md) for annotation joins, metric cohorts, and integrity checks. The catalogs share 12 columns; `video_primary` refers to head/front respectively, and the native camera keys preserve those view meanings.
+
 **Publication authorization:** All data in this dataset were authorized before public release.
diff --git a/README_zh.md b/README_zh.md
index 6996eff4f2670fe9b3a9b7bfb8fccf5b01f13770..aea24fc0cc7144f736c377b1c2acfff8967cf794 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -1,7 +1,7 @@
 <div align="center">
   <img src="https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/resolve/main/assets/robovalue-logo.png" alt="RoboValue" width="420" />
-  <h1>机器人价值模型训练数据集</h1>
-  <p><strong>Simulation &amp; Real-World · Full-Shot &amp; One-Shot</strong></p>
+  <h1>RoboValue 训练与公开测试数据</h1>
+  <p><strong>训练示例 · 小规模真机与仿真公开测试集</strong></p>
   <p>
     <a href="https://arxiv.org/abs/2610.26663"><img src="https://img.shields.io/badge/arXiv-Paper-red?logo=arxiv" alt="RoboValue paper on arXiv" /></a>
     <a href="https://github.com/RoboValue-Benchmark/RoboValue"><img src="https://img.shields.io/badge/GitHub-RoboValue-24292F?logo=github" alt="RoboValue GitHub" /></a>
@@ -13,10 +13,10 @@
 
 RoboValue 提供面向**机器人价值模型**的专家示例，覆盖 **15 个仿真任务**和 **20 个真实世界任务**。两个领域均提供 Full-Shot 与 One-Shot，采用统一的 **LeRobot Dataset v3.0** 格式。
 
-本仓库的四个训练子集均已完整公开。[论文](https://arxiv.org/abs/2610.26663)与当前排行榜只报告 **Zero-Shot 和 One-Shot 评测结果**。
+本仓库的四个训练子集均已完整公开。另在独立的 `evaluation/` 目录组织两个**小规模公开诊断测试集**：**真机30条、仿真30条轨迹**，每个领域各含4个任务、90个同步相机视频。两个测试子集合计 **60条轨迹、44,647个时间步和180个视频**。[论文](https://arxiv.org/abs/2610.26663)与当前排行榜只报告 **Zero-Shot 和 One-Shot 评测结果**。
 
 <p align="center">
-  <a href="#overview">数据总览</a> · <a href="#simulation">仿真世界</a> · <a href="#real-world">真实世界</a> · <a href="#repository-layout">仓库目录</a> · <a href="#download-and-reading">下载与读取</a>
+  <a href="#overview">数据总览</a> · <a href="#simulation">仿真世界</a> · <a href="#real-world">真实世界训练数据</a> · <a href="#public-evaluation">公开测试集</a> · <a href="#repository-layout">仓库目录</a> · <a href="#download-and-reading">下载与读取</a>
 </p>
 
 ## 📊 1. 数据总览 <a name="overview"></a>
@@ -31,11 +31,36 @@ RoboValue 提供面向**机器人价值模型**的专家示例，覆盖 **15 个
 | ▦ **Full-Shot** | 每任务 100 条 | 使用完整专家示例进行训练或微调 |
 | ◉ **One-Shot** | 每任务 1 条 | 以单条任务示例进行参考条件输入或任务适配 |
 
-四个子集合计 **3,535 条轨迹、2,348,375 个同步时间步、10,605 个相机视频**，其中 One-Shot 合计 **35 条轨迹、24,442 个时间步、105 个相机视频**。
+四个训练子集合计 **3,535 条轨迹、2,348,375 个同步时间步、10,605 个相机视频**，其中 One-Shot 合计 **35 条轨迹、24,442 个时间步、105 个相机视频**。
 
-> **HF 预览说明：**自动预览按视频文件计数，其中包含 1 个展示视频。训练规模请查看这里的轨迹数与时间步数，并按[LeRobot 读取示例](#download-and-reading)加载数据。
 
-## 🟦 2. 仿真世界 <a name="simulation"></a>
+> **HF 预览说明：**显式配置的 `real-world-test-30/test` 和 `simulation-test-30/test` 均按测试轨迹计数，**每条轨迹一行、每个配置30行**。切换配置可查看任务、轨迹类型、适用指标和三机位视频路径，默认显示真机。这些目录用于浏览；实际逐帧模型输入仍通过 LeRobot 读取。辅助JSON报告与导航说明不进入预览。
+
+### 公开测试集 <a name="public-evaluation"></a>
+
+训练示例与公开测试轨迹分别存放，用途明确区分：
+
+| 数据集合 | 目录 | 规模 | 用途 |
+| --- | --- | --- | --- |
+| 仿真／真机训练数据 | `data/<domain>/{full-shot,one-shot}` | 上述四个训练子集 | 用于训练或示例参考输入的专家示范 |
+| [真机公开测试集](evaluation/real-world/test-30/README_zh.md) | `evaluation/real-world/test-30` | **4任务／30轨迹／27,498时间步／90视频** | 小规模 In-Domain 诊断评测 |
+| [仿真公开测试集](evaluation/simulation/test-30/README_zh.md) | `evaluation/simulation/test-30` | **4任务／30轨迹／17,149时间步／90视频** | 小规模 In-Domain 诊断评测 |
+
+真机子集包含**书桌12条、花艺与香薰12条、敲鼓3条和按钮3条**；仿真子集包含**笔筒12条、悬挂马克杯12条、依数字按按钮3条和交换积木3条**。两域均提供图像与英文指令，评测标注独立存放。任务和轨迹编号仅在各自子集内有效，与训练及另一个测试子集的编号独立。两个子集提供部分诊断覆盖，规模与覆盖范围小于完整排行榜测试集。
+
+| 指标覆盖 | 真机 | 仿真 |
+| --- | --- | --- |
+| TGA-CT、TGA-CF、VOC、Cycle-VOC、VS | 各4条 ED | 各4条 ED |
+| SA／SIA | 24／12条 | 24／12条 |
+| TRR | 12条／4个三角色组 | 12条／4个三角色组 |
+| CSVC | 12条／10个方案组 | 12条／6个顺序组 |
+| FPL | 8条 ER/EC | 原FPL字段保留，未建立正式FPL集合 |
+| VOC-MEM | 6条完整计数历史 | 6条完整记忆历史，未提供计数子任务区间 |
+
+请查看[真机指标覆盖与逐轨迹索引](evaluation/real-world/test-30/README_zh.md#metric-coverage)和[仿真指标覆盖与逐轨迹索引](evaluation/simulation/test-30/README_zh.md#metric-coverage)。仿真 ED/MS 的终局标签和语义对齐来自用户确认；TRR/MEM 的终局标签保留源标注中“待独立验证”的证据状态，详情见仿真说明。
+
+
+## 🟦 2. 仿真训练数据 <a name="simulation"></a>
 
 ### 2.1 总览
 
@@ -149,7 +174,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 
 **子任务标注：**[58 个论文子任务区间](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/annotations/subtasks/README.md)覆盖全部 **8,080 帧**，每帧对应一个子任务。标注用于这些训练示例，与评测集标签分开。 另提供 [`dataset_labeler` 兼容 JSON](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145/data/simulation/one-shot/annotations/subtasks/dataset_labeler)，与逐帧标签使用相同的子任务和边界。
 
-## 🟧 3. 真实世界 <a name="real-world"></a>
+## 🟧 3. 真实世界训练数据 <a name="real-world"></a>
 
 ### 3.1 总览
 
@@ -299,12 +324,23 @@ data/
 └── real-world/
     ├── full-shot/                2,000 条 · 20 个任务
     └── one-shot/                 20 条 · 每任务 1 条
+evaluation/
+├── simulation/test-30/           30条轨迹 · 4个任务
+│   └── meta/、data/、videos/、annotations/、说明与目录
+└── real-world/test-30/            30条轨迹 · 4个任务
+    ├── meta/                     原生 LeRobot v3 元数据
+    ├── data/                     逐帧引用
+    ├── videos/                   三路同步相机视频
+    ├── annotations/              独立评测标注
+    ├── episode_catalog.parquet   每条轨迹一行的浏览索引
+    ├── README.md / README_zh.md   任务与指标说明
+    └── checksums.sha256           文件完整性清单
 ```
 
-每个子集目录都是独立的 **LeRobot** 数据根目录（`root`），内部包含逐时间步 Parquet、三路原始相机视频及元数据。
+已发布的训练及公开测试子集目录均为独立的 **LeRobot** 数据根目录（`root`）。两个测试子集保留逐帧引用、RGB视频和英文指令，评测标注另行存放，不含机器人状态／动作向量。真机主视角是头部，仿真主视角是正面。
 
 <details>
-<summary><strong>子集文件结构与元数据</strong></summary>
+<summary><strong>训练子集文件结构与元数据</strong></summary>
 
 | 文件或目录 | 用途 |
 | --- | --- |
@@ -335,10 +371,12 @@ data/
 | 🟦 **仿真 One-Shot** | `data/simulation/one-shot` | 15 / 8,080 | ≈0.50 GB |
 | 🟧 **真机 Full-Shot** | `data/real-world/full-shot` | 2,000 / 1,534,321 | ≈23.13 GB |
 | 🟧 **真机 One-Shot** | `data/real-world/one-shot` | 20 / 16,362 | ≈0.22 GB |
+| **真机公开测试集** | `evaluation/real-world/test-30` | 30 / 27,498 | ≈0.38 GB |
+| **仿真公开测试集** | `evaluation/simulation/test-30` | 30 / 17,149 | ≈0.595 GB |
 
 ### 5.2 下载并读取
 
-以下示例读取较小的 **仿真 One-Shot**，返回状态、动作及三路相机帧。切换子集时，将 `prefix` 改为上表中的对应路径。公开数据可匿名下载，示例会自动复用本机已有的 Hugging Face 登录。若匿名下载遇到限流，可先运行 `hf auth login` 后重试。
+以下示例读取较小的 **仿真 One-Shot**，返回状态、动作及三路相机帧。切换训练子集时，将 `prefix` 改为上表中的对应训练路径。公开测试集请使用下方单独的图像和指令读取示例。公开数据可匿名下载，示例会自动复用本机已有的 Hugging Face 登录。若匿名下载遇到限流，可先运行 `hf auth login` 后重试。
 
 以下示例已在 **Python 3.12**、**LeRobot 0.4.2** 与 **PyAV 15.1.0** 环境中验证：
 
@@ -456,4 +494,35 @@ batch 包含状态、动作、任务指令与三路相机观测。模型的输
 shasum -a 256 -c checksums.sha256
 ```
 
+### 5.5 下载并读取公开测试子集
+
+选择 `evaluation/real-world/test-30` 或 `evaluation/simulation/test-30`，仅下载其中一个公开测试子集。下方示例固定到包含两个测试集的版本 `578593ef28ee7a2d861ebf38162c928291b0d4a9`，下载和加载使用同一提交。上方训练示例的旧版本早于本测试集发布。
+
+```python
+from pathlib import Path
+from huggingface_hub import snapshot_download
+from lerobot.datasets.lerobot_dataset import LeRobotDataset
+
+repo_id = "wzlllong/value-model-benchmark-training-data"
+prefix = "evaluation/real-world/test-30"
+revision = "578593ef28ee7a2d861ebf38162c928291b0d4a9"
+snapshot = snapshot_download(
+    repo_id=repo_id, repo_type="dataset", revision=revision,
+    allow_patterns=[f"{prefix}/**"], local_dir="./robovalue-data",
+)
+root = Path(snapshot) / prefix
+dataset = LeRobotDataset(
+    repo_id=repo_id, root=root, revision=revision,
+    video_backend="pyav", tolerance_s=1e-4,
+)
+sample = dataset[0]
+value_input = {
+    "images": {camera: sample[camera] for camera in dataset.meta.camera_keys},
+    "instruction": sample["task"],
+}
+print(dataset.num_episodes, dataset.num_frames)  # 真机：30 27498；仿真：30 17149
+```
+
+原生元数据保留 `train: 0:30` 作为 LeRobot 容器划分，两个公开子集的用途均为**测试**，HF 浏览索引使用语义上的 `test` 划分。请显式读取 `root / "annotations"` 中的标注；成功标记、轨迹类型、指标归属和逐帧引用不作为模型观测输入。依赖历史的模型可通过 `delta_timestamps` 在每条轨迹内读取时序窗口。标注关联、指标归属与完整性检查见[真机说明](evaluation/real-world/test-30/README_zh.md)或[仿真说明](evaluation/simulation/test-30/README_zh.md)。两域轨迹目录采用相同12列，`video_primary` 分别指向头部／正面视频；原生相机键保留各自的机位含义。
+
 **发布授权：**本数据集全部数据均经授权后公开发布。
diff --git a/evaluation/real-world/test-30/README.md b/evaluation/real-world/test-30/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e06f6a0eb8366e73c2f10640cfa4d6a774913a05
--- /dev/null
+++ b/evaluation/real-world/test-30/README.md
@@ -0,0 +1,183 @@
+# RoboValue Small-Scale Real-World Public Test Set
+
+[简体中文](README_zh.md) · [Repository overview](../../../README.md) · [Browse all 30 trajectories](TRAJECTORIES.md) · [Parquet catalog](episode_catalog.parquet)
+
+This **in-domain diagnostic test subset** contains **30 complete real-world trajectories across four tasks**, including standard demonstrations, alternative successful solutions, errors, recoveries, and counting histories. It provides visual inputs, English instructions, and separate evaluation annotations for **11 metric entry points**. Its purpose is to make metric behavior inspectable and support small-scale evaluation; its task and solution coverage is smaller than the complete RoboValue leaderboard test set.
+
+The subset is stored under `evaluation/real-world/test-30/`, separately from the repository's training demonstrations in `data/`. The four tasks belong to existing real-world task categories; evaluation coverage is defined by the metric cohorts below. Native metadata retains `train: 0:30` for LeRobot container compatibility; the release's intended use and HF trajectory-catalog split are **test**.
+
+## Tasks and trajectories
+
+| Local task index | Task | Episodes | Local episode indices |
+|---:|---|---:|---|
+| 0 | Organize Desktop Workstation | 12 | 0–11 |
+| 1 | Arrange Flowers and Reed Diffuser | 12 | 12–23 |
+| 2 | Strike Drum Five Times | 3 | 24–26 |
+| 3 | Press Button Five Times | 3 | 27–29 |
+
+There are **27,498 synchronized time steps at 30 FPS** and **90 HEVC videos**: one head-camera, one left-wrist, and one right-wrist video per episode. Time steps are counted once, rather than once per camera. Head videos are **640 × 400**, and wrist videos are **640 × 528**. The visual-input source package is approximately **382 MB (0.38 GB, decimal)**; the release adds lightweight documentation and catalogs. The subset contains **22 successful and 8 unsuccessful episodes**. Complete trajectories and history are retained, including unsuccessful episodes.
+
+Local `task_index` values 0–3 and `episode_index` values 0–29 belong to this subset. They must not be joined directly to the independent indices of the training subsets. No prior episode or collection-source identifiers are included.
+
+<a id="metric-coverage"></a>
+
+## Which trajectories evaluate which metrics?
+
+[`annotations/metric_membership.json`](annotations/metric_membership.json) is the **authoritative metric membership**, even when other annotation fields exist on an episode. The same episode can participate in several metrics, so the counts below must not be added to obtain the dataset size.
+
+| Metric / code key | What it evaluates | Eligible trajectories | Episodes / groups | Supporting annotations |
+|---|---|---|---|---|
+| TGA-CT / `tga_easy` | Distinguishing the correct task instruction from other tasks | Desk and flower ED | 4 episodes | `tasks.json`, `task_candidates.json` (14 candidate instructions) |
+| TGA-CF / `tga_hard` | Distinguishing the task goal from counterfactual instructions | Desk and flower ED | 4 episodes | `tasks.json` (4 counterfactual instructions per regular task) |
+| VOC / `voc` | Value ordering along forward task progress | Desk and flower ED | 4 episodes | Subtask intervals and sampling anchors in `episodes.jsonl` |
+| Cycle-VOC / `cycle_voc` | Value ordering along forward and reverse task progress | Desk and flower ED | 4 episodes | Complete trajectories, subtask intervals, and sampling anchors in `episodes.jsonl` |
+| VS / `vs` | Stability of the forward value curve | Desk and flower ED | 4 episodes | The same forward trajectories and sampling basis used by Cycle-VOC |
+| SA / `sa` | Distinguishing terminal task success from failure | All desk and flower episodes | 24 episodes: 16 successful, 8 unsuccessful | `success` in `episodes.jsonl` |
+| SIA / `sia` | Identifying the semantic subtask being performed | Desk and flower ED/MS | 12 episodes | Subtask descriptions in `tasks.json` and local intervals in `episodes.jsonl` |
+| CSVC / `csvc` | Consistency of semantic value increments across successful solutions | Desk and flower ED/MS | 12 episodes / 10 solution groups | `csvc_solutions.json`: groups, semantic/object order, and subtask intervals |
+| TRR / `trr` | Distinguishing effective recovery, ineffective recovery, and error continuation | Desk and flower ER/IR/EC | 12 episodes / 4 three-role groups | `trr_groups.json` and failure/recovery stage intervals in `episodes.jsonl` |
+| FPL / `fpl` | Locating the onset of the target error | Selected desk and flower ER/EC | 8 episodes: 4 ER, 4 EC | `fpl_annotations.json`: target subtask, failure interval, and `failure_onset_frame` |
+| VOC-MEM / `voc_mem` | Value ordering for repeated-action counting using complete history | Drum and button MEM | 6 episodes, all successful | Counting subtask intervals and sampling anchors in `episodes.jsonl` |
+
+All four ED episodes are `0, 1, 12, 14`. Counting episodes are `24–29`. For a per-episode list, inspect [`episode_catalog.parquet`](episode_catalog.parquet), whose `metrics` column is derived from the membership file.
+
+| Trajectory type | Meaning | Count | Applicable metrics in this release |
+|---|---|---:|---|
+| ED | Standard successful demonstration | 4 | TGA-CT, TGA-CF, VOC, Cycle-VOC, VS, SA, SIA, CSVC |
+| MS | Successful alternative solution | 8 | SA, SIA, CSVC |
+| ER | Effective recovery | 4 | SA, TRR, FPL |
+| IR | Ineffective recovery | 4 | SA, TRR |
+| EC | Error continuation | 4 | SA, TRR, FPL |
+| MEM | Complete counting-history episode | 6 | VOC-MEM |
+
+FPL's eight episodes all contain a target error, but the four ER episodes ultimately succeed; they are not eight terminal failures. Each TRR group has one ER, one IR, and one EC member; their roles correspond to `r_plus`, `r_zero`, and `r_minus`. Each regular task has five CSVC solution groups: one standard-repeat group containing two ED instances, and four alternative groups containing one MS instance each. This is **10 groups and 12 instances**, not 12 distinct solutions or exhaustive solution coverage. The six MEM episodes provide successful counting histories; counting failures and counting recovery are not covered.
+
+## Files and annotation semantics
+
+```text
+meta/info.json                         Native format, features, FPS, and path templates
+meta/tasks.parquet                     English instructions indexed by task_index
+meta/episodes/chunk-000/file-000.parquet Native episode lengths and video references
+data/chunk-000/file-*.parquet           Native frame-reference records
+videos/observation.images.top_head/    Head-camera videos
+videos/observation.images.hand_left/   Left-wrist videos
+videos/observation.images.hand_right/  Right-wrist videos
+annotations/                          Separate English evaluation labels
+episode_catalog.parquet               One browsing/index row per episode
+checksums.sha256                       Release-file integrity manifest
+```
+
+Each native frame record contains only `timestamp`, `frame_index`, `episode_index`, `index`, and `task_index`. They locate frames and instructions; they are not model observations. Timestamps are seconds relative to the episode start. This visual export contains no robot state/action vectors, reserved robot interfaces, collection timestamps, collection software versions, or source identities. `codebase_version: v3.0` identifies the native format, and `robot_type` is null. Numeric normalization statistics are omitted because there are no numeric observation features.
+
+Video container/encoder metadata and HEVC supplemental messages were removed by stream copying. Frames were not re-encoded, cropped, resampled, or reordered; decoded pixels and frame timing were preserved. This release copies the final visual-input export unchanged.
+
+| Annotation file | Contents |
+|---|---|
+| [`tasks.json`](annotations/tasks.json) | Four English task instructions, semantic subtask IDs/descriptions, and available counterfactual instructions |
+| [`episodes.jsonl`](annotations/episodes.jsonl) | Thirty success flags, trajectory types, complete per-episode annotation objects, action segments, keyframes, and available flower identities |
+| [`trr_groups.json`](annotations/trr_groups.json) | Four three-role groups and their target subtasks |
+| [`fpl_annotations.json`](annotations/fpl_annotations.json) | Eight selected target errors, target subtasks, and error-onset frames |
+| [`csvc_solutions.json`](annotations/csvc_solutions.json) | Solution groups, semantic/object order, and per-instance subtask intervals |
+| [`metric_membership.json`](annotations/metric_membership.json) | Exact episode/task cohorts for the 11 metric entry points |
+| [`task_candidates.json`](annotations/task_candidates.json) | Fourteen English task candidates for cross-task goal assessment |
+
+All annotation frame indices are local and zero-based. Evaluation intervals use **half-open** `[start_frame, end_frame_exclusive)` ranges. Existing action/keyframe `end_frame_index` endpoint values are retained as supplied; do not silently convert their convention. Semantic subtask IDs describe subtasks, and `group_index`/`solution_index` describe evaluation relationships rather than collection sources.
+
+The per-episode `annotations` object retains available `subtask_segments`, `fpl`, `trr`, `voc`, and `voc_mem` entries. TRR stage keys include `failure_span`, `recovery_span`, `recovery_success_span`, `recovery_failed_span`, and `continue_span`, as applicable. VOC/VOC-MEM entries are **sampling anchors**, not ground-truth value/progress scores or model predictions. Keyframe `label` is an event annotation; `frame_type_name` retains the existing marker category. Flower identities are auxiliary object labels; ordinal flower subtasks keep their existing semantics. Missing detailed physical error labels are not invented.
+
+Annotations are read explicitly and are not automatically added to native LeRobot samples. The presence of a `voc` field on MS/ER/IR/EC does not expand their formal VOC/Cycle-VOC/VS membership; an IR episode is not in the formal FPL cohort.
+
+## Trajectory catalog and HF preview
+
+The repository's `real-world-test-30` configuration exposes a **`test` split with 30 episode rows**, explicitly selecting `episode_catalog.parquet`. Auxiliary JSON reports and navigation documents are not preview datasets. This episode catalog is a browsing index, while LeRobot provides the native per-time-step samples. [`TRAJECTORIES.md`](TRAJECTORIES.md) also lists all 30 episodes, their eligible metrics, and direct links to the three camera videos.
+
+| Field | Type | Meaning |
+|---|---|---|
+| `episode_index`, `task_index` | `int64` | Public indices local to this subset |
+| `task_name`, `instruction` | `string` | English display task name and original English instruction |
+| `trajectory_type` | `string` | ED, MS, ER, IR, EC, or MEM |
+| `success` | `bool` | Terminal task-success annotation |
+| `num_frames` | `int64` | Episode time-step count, counted once across cameras |
+| `duration_s` | `float64` | Episode duration (`num_frames / fps`) |
+| `video_primary`, `video_left_wrist`, `video_right_wrist` | `string` | Video-file paths relative to this subset root |
+| `metrics` | `list[string]` | Eligible metric code keys from `metric_membership.json` |
+
+The catalog's video columns are file references, not decoded model observations. Path references and labels are for navigation/evaluation, not inputs to the value model.
+
+## Download and load
+
+The example is pinned to `578593ef28ee7a2d861ebf38162c928291b0d4a9`, which contains both public test sets, and downloads only this subset. Download and load using the same fixed revision.
+
+```python
+from pathlib import Path
+from huggingface_hub import snapshot_download
+
+repo_id = "wzlllong/value-model-benchmark-training-data"
+prefix = "evaluation/real-world/test-30"
+revision = "578593ef28ee7a2d861ebf38162c928291b0d4a9"  # Fixed data revision containing both test domains.
+snapshot = snapshot_download(
+    repo_id=repo_id,
+    repo_type="dataset",
+    revision=revision,
+    allow_patterns=[f"{prefix}/**"],
+    local_dir="./robovalue-data",
+)
+root = Path(snapshot) / prefix
+```
+
+For an extracted local upload package, use `root = Path("upload/evaluation/real-world/test-30")`. In either case, `root` must contain `meta/`, `data/`, and `videos/`. Install LeRobot with its PyAV video backend, then load the complete native subset:
+
+```python
+from lerobot.datasets.lerobot_dataset import LeRobotDataset
+
+dataset = LeRobotDataset(
+    repo_id="wzlllong/value-model-benchmark-training-data",
+    root=root,
+    video_backend="pyav",
+    tolerance_s=1e-4,
+)
+item = dataset[0]
+camera_keys = [
+    "observation.images.top_head",
+    "observation.images.hand_left",
+    "observation.images.hand_right",
+]
+value_input = {
+    "images": {key: item[key] for key in camera_keys},
+    "instruction": item["task"],
+}
+print(dataset.num_episodes, dataset.num_frames)  # 30, 27498
+```
+
+Loaded camera images use CHW order: head `[3, 400, 640]`, wrists `[3, 528, 640]`. Send **only the selected camera images and instruction** to the value model. Success flags, trajectory types, subtask/solution/group labels, indices, timestamps, and file paths are not model observations. History-based models can request earlier frames through LeRobot's `delta_timestamps`; retain their episode alignment and ordering.
+
+Read labels and metric eligibility separately using the same local episode index:
+
+```python
+import json
+
+episode_index = int(item["episode_index"])
+episodes = {
+    row["episode_index"]: row
+    for row in (
+        json.loads(line)
+        for line in (root / "annotations/episodes.jsonl").read_text().splitlines()
+        if line.strip()
+    )
+}
+membership = json.loads(
+    (root / "annotations/metric_membership.json").read_text()
+)["metrics"]
+labels = episodes[episode_index]
+eligible_metrics = [
+    key for key, cohort in membership.items()
+    if episode_index in cohort["episode_indices"]
+]
+assert int(item["task_index"]) == labels["task_index"]
+```
+
+From the subset directory, verify the release-file hashes with:
+
+```bash
+shasum -a 256 -c checksums.sha256
+```
diff --git a/evaluation/real-world/test-30/README_zh.md b/evaluation/real-world/test-30/README_zh.md
new file mode 100644
index 0000000000000000000000000000000000000000..a20598379ebe4c19a888427682a54739ff4c14ab
--- /dev/null
+++ b/evaluation/real-world/test-30/README_zh.md
@@ -0,0 +1,183 @@
+# RoboValue 小规模真机公开测试集
+
+[English](README.md) · [仓库概览](../../../README_zh.md) · [查看全部30条轨迹](TRAJECTORIES.md) · [Parquet目录](episode_catalog.parquet)
+
+这是一个**真实世界 In-Domain 诊断测试子集**，包含 **4 个任务、30 条完整轨迹**，涵盖标准示范、多种成功方案、错误、恢复和完整计数历史。数据提供图像、英语任务指令及独立评测标注，支持 **11 个指标入口**，便于检查指标行为和开展小规模评测。它的任务与方案覆盖范围小于完整 RoboValue 排行榜测试集。
+
+本子集位于 `evaluation/real-world/test-30/`，与仓库 `data/` 下的训练示范分区存放，覆盖已有的4个真机任务类别；评测范围以下方各指标的正式轨迹集合为准。为兼容 LeRobot 容器，原生元数据保留 `train: 0:30`；本次发布的用途及 HF 逐轨迹目录划分均为 **test（测试）**。
+
+## 任务与轨迹
+
+| 子集内任务编号 | 任务 | 轨迹数 | 子集内轨迹编号 |
+|---:|---|---:|---|
+| 0 | 整理桌面工作区（Organize Desktop Workstation） | 12 | 0–11 |
+| 1 | 插花与摆放藤条香薰（Arrange Flowers and Reed Diffuser） | 12 | 12–23 |
+| 2 | 敲鼓五次（Strike Drum Five Times） | 3 | 24–26 |
+| 3 | 按按钮五次（Press Button Five Times） | 3 | 27–29 |
+
+数据包含 **27,498 个同步时间步，30 FPS，90 个 HEVC 视频**：每条轨迹各有头部、左手腕、右手腕三个同步视角。时间步按轨迹计数一次，不按机位重复累加。头部视频尺寸为 **640 × 400**，两路腕部视频均为 **640 × 528**。视觉输入源目录约 **382 MB（0.38 GB，十进制）**；本次发布另增加少量说明和目录文件。共 **22 条最终成功、8 条最终失败**；所有轨迹与历史均完整保留，包括失败轨迹。
+
+`task_index` 0–3 和 `episode_index` 0–29 都是本子集内编号，不能直接与训练子集的独立编号关联。文件中不包含原轨迹编号或采集来源标识。
+
+<a id="metric-coverage"></a>
+
+## 哪些轨迹用于哪些指标？
+
+[`annotations/metric_membership.json`](annotations/metric_membership.json) 是**唯一权威的指标归属表**。即使某条轨迹还含有其他标注字段，也应按该文件筛选正式评测集合。同一轨迹可参加多个指标，不能把下表的轨迹数相加作为数据集总量。
+
+| 指标／代码键 | 评测用途 | 适用轨迹 | 轨迹数／组数 | 对应标注 |
+|---|---|---|---|---|
+| TGA-CT／`tga_easy` | 从不同任务的指令中辨别正确任务目标 | 书桌、花艺 ED | 4条 | `tasks.json`、`task_candidates.json`（14个候选指令） |
+| TGA-CF／`tga_hard` | 区分原任务目标与反事实任务指令 | 书桌、花艺 ED | 4条 | `tasks.json`（每个常规任务4条反事实指令） |
+| VOC／`voc` | 检查正向任务进展的价值顺序 | 书桌、花艺 ED | 4条 | `episodes.jsonl` 中的子任务区间和采样锚点 |
+| Cycle-VOC／`cycle_voc` | 检查正向及反向播放下的进展价值顺序 | 书桌、花艺 ED | 4条 | 完整轨迹、子任务区间、采样锚点 |
+| VS／`vs` | 检查正向价值曲线的稳定性 | 书桌、花艺 ED | 4条 | 与 Cycle-VOC 共享的正向轨迹和采样依据 |
+| SA／`sa` | 区分最终任务成功与失败 | 书桌、花艺全部轨迹 | 24条：16成功、8失败 | `episodes.jsonl` 中的 `success` |
+| SIA／`sia` | 识别当前执行的语义子任务 | 书桌、花艺 ED/MS | 12条 | `tasks.json` 的子任务描述及 `episodes.jsonl` 的局部区间 |
+| CSVC／`csvc` | 检查不同成功方案中的语义价值增量一致性 | 书桌、花艺 ED/MS | 12条／10个方案组 | `csvc_solutions.json` 中的分组、语义／物体顺序及子任务区间 |
+| TRR／`trr` | 区分有效恢复、无效恢复和错误延续 | 书桌、花艺 ER/IR/EC | 12条／4个三角色组 | `trr_groups.json` 及 `episodes.jsonl` 的失败／恢复阶段区间 |
+| FPL／`fpl` | 定位目标错误的发生起点 | 选定的书桌、花艺 ER/EC | 8条：4 ER、4 EC | `fpl_annotations.json` 中的目标子任务、错误区间、`failure_onset_frame` |
+| VOC-MEM／`voc_mem` | 利用完整历史判断重复动作的计数进展顺序 | 敲鼓、按钮 MEM | 6条，全部最终成功 | `episodes.jsonl` 中的计数子任务区间和采样锚点 |
+
+4条 ED 的编号为 `0、1、12、14`；计数轨迹的编号为 `24–29`。每条轨迹的适用指标也可在 [`episode_catalog.parquet`](episode_catalog.parquet) 的 `metrics` 列查看，该列由权威归属表反向生成。
+
+| 轨迹类型 | 含义 | 数量 | 本次发布适用指标 |
+|---|---|---:|---|
+| ED | 标准成功示范 | 4 | TGA-CT、TGA-CF、VOC、Cycle-VOC、VS、SA、SIA、CSVC |
+| MS | 成功的替代方案 | 8 | SA、SIA、CSVC |
+| ER | 有效恢复 | 4 | SA、TRR、FPL |
+| IR | 无效恢复 | 4 | SA、TRR |
+| EC | 错误延续 | 4 | SA、TRR、FPL |
+| MEM | 保留完整历史的计数轨迹 | 6 | VOC-MEM |
+
+FPL 的8条均含目标错误，但4条 ER 最终恢复成功，不能把它们称为8条最终失败轨迹。每个 TRR 组包含 ER、IR、EC 各一条，对应 `r_plus`、`r_zero`、`r_minus`。CSVC 每个常规任务有5个方案组：1个标准重复组含2条 ED，另4个替代方案组各含1条 MS；合计 **10个方案组、12个实例**，不是12种不同解法，也不是所有可能方案。6条 MEM 当前全部成功，覆盖成功计数历史，尚未覆盖计数失败或计数恢复。
+
+## 文件与标注语义
+
+```text
+meta/info.json                         原生格式、字段、FPS与路径模板
+meta/tasks.parquet                     按task_index索引的英语指令
+meta/episodes/chunk-000/file-000.parquet 原生轨迹长度与视频引用
+data/chunk-000/file-*.parquet           原生逐帧定位记录
+videos/observation.images.top_head/    头部视频
+videos/observation.images.hand_left/   左手腕视频
+videos/observation.images.hand_right/  右手腕视频
+annotations/                          独立英语评测标注
+episode_catalog.parquet               每条轨迹一行的浏览索引
+checksums.sha256                       发布文件完整性清单
+```
+
+原生逐帧记录仅含 `timestamp`、`frame_index`、`episode_index`、`index` 和 `task_index`，用于定位帧和指令，不是模型观测。`timestamp` 是从轨迹开始计算的秒数。视觉导出不含机器人状态／动作向量、预留机器人接口、采集时间、采集软件版本或来源标识。`codebase_version: v3.0` 是原生格式标识，`robot_type` 为 null；因不存在数值观测特征，未生成数值归一化统计。
+
+视频容器／编码器元数据和 HEVC 补充消息已通过流复制移除。图像未经重新编码、裁剪、重采样或重排，解码像素和帧时间轴均保留。本次整理直接复制最终视觉输入导出，数据内容不变。
+
+| 标注文件 | 内容 |
+|---|---|
+| [`tasks.json`](annotations/tasks.json) | 4个英语任务指令、语义子任务编号／描述及已有反事实指令 |
+| [`episodes.jsonl`](annotations/episodes.jsonl) | 30条成功标记、轨迹类型、完整逐轨迹标注、动作片段、关键帧及已有花朵身份标注 |
+| [`trr_groups.json`](annotations/trr_groups.json) | 4个三角色分组及目标子任务 |
+| [`fpl_annotations.json`](annotations/fpl_annotations.json) | 8个选定目标错误、目标子任务及错误起点 |
+| [`csvc_solutions.json`](annotations/csvc_solutions.json) | 方案分组、语义／物体顺序及各实例的子任务区间 |
+| [`metric_membership.json`](annotations/metric_membership.json) | 11个指标入口的精确任务／轨迹集合 |
+| [`task_candidates.json`](annotations/task_candidates.json) | 14个用于跨任务目标辨别的英语候选任务指令 |
+
+所有标注帧编号均为本轨迹内从0开始的局部编号。评测区间采用**左闭右开** `[start_frame, end_frame_exclusive)`；已有动作／关键帧 `end_frame_index` 的端点值按原标注保留，不应自行转换约定。语义子任务编号用于描述子任务；`group_index` 和 `solution_index` 用于表达评测关系，不是采集来源标识。
+
+逐轨迹 `annotations` 对象保留已有 `subtask_segments`、`fpl`、`trr`、`voc` 和 `voc_mem` 字段。TRR 阶段区间视轨迹包含 `failure_span`、`recovery_span`、`recovery_success_span`、`recovery_failed_span`、`continue_span`。VOC／VOC-MEM 条目是**采样锚点**，不是逐帧真实价值／进度分数或模型预测。关键帧 `label` 为事件标注，`frame_type_name` 保留已有标记类别。花朵身份为辅助物体标注，按第几朵定义的子任务语义保持不变；缺失的详细物理错误标签不会被补造。
+
+标注需显式读取，LeRobot 不会自动把它们加入 sample。MS/ER/IR/EC 即使含有 `voc` 字段，也不属于本次正式 VOC／Cycle-VOC／VS 集合；IR 不属于正式 FPL 集合。
+
+## 逐轨迹目录与 HF 预览
+
+仓库的 `real-world-test-30` 配置显式指向 `episode_catalog.parquet`，提供 **30行、划分为 `test` 的轨迹预览**。辅助验证 JSON 和导航说明不作为预览数据。目录每行代表一条轨迹；实际逐时间步样本由 LeRobot 读取。[`TRAJECTORIES.md`](TRAJECTORIES.md) 另提供30条轨迹的逐条表格、适用指标及三个机位的视频链接。
+
+| 字段 | 类型 | 含义 |
+|---|---|---|
+| `episode_index`、`task_index` | `int64` | 本子集内的公开编号 |
+| `task_name`、`instruction` | `string` | 英语展示任务名与原英语任务指令 |
+| `trajectory_type` | `string` | ED、MS、ER、IR、EC或MEM |
+| `success` | `bool` | 最终任务成功标记 |
+| `num_frames` | `int64` | 轨迹时间步数，三个机位只计一次 |
+| `duration_s` | `float64` | 轨迹时长（`num_frames / fps`） |
+| `video_primary`、`video_left_wrist`、`video_right_wrist` | `string` | 相对于本子集根目录的视频文件路径 |
+| `metrics` | `list[string]` | 由 `metric_membership.json` 提供的指标代码键 |
+
+目录里的视频列是文件引用，不是已解码的模型观测。文件路径及标签用于浏览和评测，不作为价值模型输入。
+
+## 单独下载与加载
+
+以下示例固定到包含两个公开测试集的版本 `578593ef28ee7a2d861ebf38162c928291b0d4a9`，仅下载本子集。下载和加载使用同一提交。
+
+```python
+from pathlib import Path
+from huggingface_hub import snapshot_download
+
+repo_id = "wzlllong/value-model-benchmark-training-data"
+prefix = "evaluation/real-world/test-30"
+revision = "578593ef28ee7a2d861ebf38162c928291b0d4a9"  # 包含两域测试集的固定发布版本。
+snapshot = snapshot_download(
+    repo_id=repo_id,
+    repo_type="dataset",
+    revision=revision,
+    allow_patterns=[f"{prefix}/**"],
+    local_dir="./robovalue-data",
+)
+root = Path(snapshot) / prefix
+```
+
+若使用解压后的本地上传包，设置 `root = Path("upload/evaluation/real-world/test-30")`。`root` 应直接包含 `meta/`、`data/` 和 `videos/`。安装带 PyAV 视频后端的 LeRobot 后，读取完整原生数据集：
+
+```python
+from lerobot.datasets.lerobot_dataset import LeRobotDataset
+
+dataset = LeRobotDataset(
+    repo_id="wzlllong/value-model-benchmark-training-data",
+    root=root,
+    video_backend="pyav",
+    tolerance_s=1e-4,
+)
+item = dataset[0]
+camera_keys = [
+    "observation.images.top_head",
+    "observation.images.hand_left",
+    "observation.images.hand_right",
+]
+value_input = {
+    "images": {key: item[key] for key in camera_keys},
+    "instruction": item["task"],
+}
+print(dataset.num_episodes, dataset.num_frames)  # 30, 27498
+```
+
+加载后的图像使用 CHW 顺序：头部 `[3, 400, 640]`，腕部 `[3, 528, 640]`。价值模型仅接收**所选机位图像和指令**。成功标记、轨迹类型、子任务／方案／分组标签、编号、时间戳及文件路径均不是模型观测。需要历史的模型可使用 LeRobot `delta_timestamps` 读取更早帧，并保持轨迹内的时间顺序和对齐。
+
+通过同一局部轨迹编号，单独读取标签和指标归属：
+
+```python
+import json
+
+episode_index = int(item["episode_index"])
+episodes = {
+    row["episode_index"]: row
+    for row in (
+        json.loads(line)
+        for line in (root / "annotations/episodes.jsonl").read_text().splitlines()
+        if line.strip()
+    )
+}
+membership = json.loads(
+    (root / "annotations/metric_membership.json").read_text()
+)["metrics"]
+labels = episodes[episode_index]
+eligible_metrics = [
+    key for key, cohort in membership.items()
+    if episode_index in cohort["episode_indices"]
+]
+assert int(item["task_index"]) == labels["task_index"]
+```
+
+在子集目录中运行以下命令检查发布文件哈希：
+
+```bash
+shasum -a 256 -c checksums.sha256
+```
diff --git a/evaluation/real-world/test-30/TRAJECTORIES.md b/evaluation/real-world/test-30/TRAJECTORIES.md
new file mode 100644
index 0000000000000000000000000000000000000000..b785a78bc221c681976851a3128476dc569ec8ef
--- /dev/null
+++ b/evaluation/real-world/test-30/TRAJECTORIES.md
@@ -0,0 +1,52 @@
+# Real-World Test-30: Trajectory Index / 真机30条轨迹索引
+
+[English documentation](README.md) · [中文说明](README_zh.md)
+
+One row represents one complete trajectory. Three video links refer to its synchronized camera views.
+每行是一条完整轨迹，三个视频链接是同一轨迹的同步机位。指标列表仅由正式 `annotations/metric_membership.json` 生成。
+
+Episode/task indices are local to this subset; they are independent of the training data and the other test domain.
+轨迹和任务编号仅在本子集中有效，与训练集及另一测试领域的编号独立。
+
+| Task index | Task / 任务 | Episodes / 轨迹数 |
+| ---: | --- | ---: |
+| 0 | Organize Desktop Workstation / 整理书桌 | 12 |
+| 1 | Arrange Flowers and Reed Diffuser / 花艺与香薰 | 12 |
+| 2 | Strike Drum Five Times / 敲鼓五次 | 3 |
+| 3 | Press Button Five Times / 按按钮五次 | 3 |
+
+| Episode | Task | Type | Final success / 最终成功 | Frames | Duration (s) | Head / 头部 | Left wrist / 左腕 | Right wrist / 右腕 | Metrics / 指标 |
+| ---: | ---: | --- | --- | ---: | ---: | --- | --- | --- | --- |
+| 0 | 0 | ED | True / 是 | 1029 | 34.300 | [Video](videos/observation.images.top_head/chunk-000/file-000.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-000.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-000.mp4) | TGA-CT, TGA-CF, VOC, Cycle-VOC, VS, SA, SIA, CSVC |
+| 1 | 0 | ED | True / 是 | 1045 | 34.833 | [Video](videos/observation.images.top_head/chunk-000/file-001.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-001.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-001.mp4) | TGA-CT, TGA-CF, VOC, Cycle-VOC, VS, SA, SIA, CSVC |
+| 2 | 0 | MS | True / 是 | 998 | 33.267 | [Video](videos/observation.images.top_head/chunk-000/file-002.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-002.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-002.mp4) | SA, SIA, CSVC |
+| 3 | 0 | MS | True / 是 | 892 | 29.733 | [Video](videos/observation.images.top_head/chunk-000/file-003.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-003.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-003.mp4) | SA, SIA, CSVC |
+| 4 | 0 | MS | True / 是 | 818 | 27.267 | [Video](videos/observation.images.top_head/chunk-000/file-004.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-004.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-004.mp4) | SA, SIA, CSVC |
+| 5 | 0 | MS | True / 是 | 982 | 32.733 | [Video](videos/observation.images.top_head/chunk-000/file-005.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-005.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-005.mp4) | SA, SIA, CSVC |
+| 6 | 0 | ER | True / 是 | 1146 | 38.200 | [Video](videos/observation.images.top_head/chunk-000/file-006.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-006.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-006.mp4) | SA, TRR, FPL |
+| 7 | 0 | IR | False / 否 | 1161 | 38.700 | [Video](videos/observation.images.top_head/chunk-000/file-007.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-007.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-007.mp4) | SA, TRR |
+| 8 | 0 | EC | False / 否 | 906 | 30.200 | [Video](videos/observation.images.top_head/chunk-000/file-008.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-008.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-008.mp4) | SA, TRR, FPL |
+| 9 | 0 | EC | False / 否 | 817 | 27.233 | [Video](videos/observation.images.top_head/chunk-000/file-009.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-009.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-009.mp4) | SA, TRR, FPL |
+| 10 | 0 | IR | False / 否 | 937 | 31.233 | [Video](videos/observation.images.top_head/chunk-000/file-010.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-010.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-010.mp4) | SA, TRR |
+| 11 | 0 | ER | True / 是 | 922 | 30.733 | [Video](videos/observation.images.top_head/chunk-000/file-011.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-011.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-011.mp4) | SA, TRR, FPL |
+| 12 | 1 | ED | True / 是 | 934 | 31.133 | [Video](videos/observation.images.top_head/chunk-000/file-012.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-012.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-012.mp4) | TGA-CT, TGA-CF, VOC, Cycle-VOC, VS, SA, SIA, CSVC |
+| 13 | 1 | EC | False / 否 | 905 | 30.167 | [Video](videos/observation.images.top_head/chunk-000/file-013.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-013.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-013.mp4) | SA, TRR, FPL |
+| 14 | 1 | ED | True / 是 | 939 | 31.300 | [Video](videos/observation.images.top_head/chunk-000/file-014.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-014.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-014.mp4) | TGA-CT, TGA-CF, VOC, Cycle-VOC, VS, SA, SIA, CSVC |
+| 15 | 1 | MS | True / 是 | 1048 | 34.933 | [Video](videos/observation.images.top_head/chunk-000/file-015.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-015.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-015.mp4) | SA, SIA, CSVC |
+| 16 | 1 | IR | False / 否 | 1081 | 36.033 | [Video](videos/observation.images.top_head/chunk-000/file-016.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-016.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-016.mp4) | SA, TRR |
+| 17 | 1 | EC | False / 否 | 856 | 28.533 | [Video](videos/observation.images.top_head/chunk-000/file-017.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-017.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-017.mp4) | SA, TRR, FPL |
+| 18 | 1 | MS | True / 是 | 1032 | 34.400 | [Video](videos/observation.images.top_head/chunk-000/file-018.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-018.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-018.mp4) | SA, SIA, CSVC |
+| 19 | 1 | MS | True / 是 | 936 | 31.200 | [Video](videos/observation.images.top_head/chunk-000/file-019.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-019.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-019.mp4) | SA, SIA, CSVC |
+| 20 | 1 | ER | True / 是 | 1265 | 42.167 | [Video](videos/observation.images.top_head/chunk-000/file-020.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-020.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-020.mp4) | SA, TRR, FPL |
+| 21 | 1 | IR | False / 否 | 1130 | 37.667 | [Video](videos/observation.images.top_head/chunk-000/file-021.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-021.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-021.mp4) | SA, TRR |
+| 22 | 1 | MS | True / 是 | 1002 | 33.400 | [Video](videos/observation.images.top_head/chunk-000/file-022.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-022.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-022.mp4) | SA, SIA, CSVC |
+| 23 | 1 | ER | True / 是 | 1291 | 43.033 | [Video](videos/observation.images.top_head/chunk-000/file-023.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-023.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-023.mp4) | SA, TRR, FPL |
+| 24 | 2 | MEM | True / 是 | 575 | 19.167 | [Video](videos/observation.images.top_head/chunk-000/file-024.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-024.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-024.mp4) | VOC-MEM |
+| 25 | 2 | MEM | True / 是 | 560 | 18.667 | [Video](videos/observation.images.top_head/chunk-000/file-025.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-025.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-025.mp4) | VOC-MEM |
+| 26 | 2 | MEM | True / 是 | 590 | 19.667 | [Video](videos/observation.images.top_head/chunk-000/file-026.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-026.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-026.mp4) | VOC-MEM |
+| 27 | 3 | MEM | True / 是 | 572 | 19.067 | [Video](videos/observation.images.top_head/chunk-000/file-027.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-027.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-027.mp4) | VOC-MEM |
+| 28 | 3 | MEM | True / 是 | 587 | 19.567 | [Video](videos/observation.images.top_head/chunk-000/file-028.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-028.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-028.mp4) | VOC-MEM |
+| 29 | 3 | MEM | True / 是 | 542 | 18.067 | [Video](videos/observation.images.top_head/chunk-000/file-029.mp4) | [Video](videos/observation.images.hand_left/chunk-000/file-029.mp4) | [Video](videos/observation.images.hand_right/chunk-000/file-029.mp4) | VOC-MEM |
+
+Duration is frame count divided by FPS, counted once per episode. Files and evaluation labels are for navigation and scoring; model observations are images and the instruction.
+时长为帧数除以帧率，每条轨迹只计一次。文件路径和评测标签用于浏览与评分；模型观测为图像和指令。
diff --git a/evaluation/real-world/test-30/annotations/csvc_solutions.json b/evaluation/real-world/test-30/annotations/csvc_solutions.json
new file mode 100644
index 0000000000000000000000000000000000000000..e6fdf39929e8a3e10617b9c7cc3b0cb9e1c0967f
--- /dev/null
+++ b/evaluation/real-world/test-30/annotations/csvc_solutions.json
@@ -0,0 +1,678 @@
+{
+  "tasks": [
+    {
+      "task_index": 0,
+      "solutions": [
+        {
+          "solution_index": 0,
+          "episode_indices": [
+            0,
+            1
+          ],
+          "semantic_order": [
+            "001",
+            "002",
+            "003",
+            "004",
+            "005"
+          ],
+          "object_order": [
+            "pen",
+            "eraser",
+            "drawer",
+            "lamp_switch",
+            "lamp_plug"
+          ],
+          "solution_kind": "standard_repeat_group",
+          "instances": [
+            {
+              "episode_index": 0,
+              "subtask_segments": [
+                {
+                  "id": "001",
+                  "start_frame": 19,
+                  "end_frame_exclusive": 199,
+                  "object_id": "pen"
+                },
+                {
+                  "id": "002",
+                  "start_frame": 199,
+                  "end_frame_exclusive": 329,
+                  "object_id": "eraser"
+                },
+                {
+                  "id": "003",
+                  "start_frame": 329,
+                  "end_frame_exclusive": 493,
+                  "object_id": "drawer"
+                },
+                {
+                  "id": "004",
+                  "start_frame": 493,
+                  "end_frame_exclusive": 633,
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+}
diff --git a/evaluation/real-world/test-30/annotations/episodes.jsonl b/evaluation/real-world/test-30/annotations/episodes.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..9ae348e9d0e9f88ef15062ffc3960f26967726ab
--- /dev/null
+++ b/evaluation/real-world/test-30/annotations/episodes.jsonl
@@ -0,0 +1,30 @@
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diff --git a/evaluation/real-world/test-30/annotations/fpl_annotations.json b/evaluation/real-world/test-30/annotations/fpl_annotations.json
new file mode 100644
index 0000000000000000000000000000000000000000..35ce279cb7ee01c088e79a55e0744f09f29808a5
--- /dev/null
+++ b/evaluation/real-world/test-30/annotations/fpl_annotations.json
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diff --git a/evaluation/real-world/test-30/annotations/metric_membership.json b/evaluation/real-world/test-30/annotations/metric_membership.json
new file mode 100644
index 0000000000000000000000000000000000000000..7f7a841448002eeadb616b2943e7328300103ba6
--- /dev/null
+++ b/evaluation/real-world/test-30/annotations/metric_membership.json
@@ -0,0 +1,186 @@
+{
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diff --git a/evaluation/real-world/test-30/annotations/task_candidates.json b/evaluation/real-world/test-30/annotations/task_candidates.json
new file mode 100644
index 0000000000000000000000000000000000000000..ad67ce2041183187fa07accfa5383f2e5a905079
--- /dev/null
+++ b/evaluation/real-world/test-30/annotations/task_candidates.json
@@ -0,0 +1,62 @@
+{
+  "candidates": [
+    {
+      "candidate_index": 0,
+      "instruction": "Place the teacup on the cat-head mat, the teapot on the yellow mat, the lid on the teapot, the tongs in their holder, and the canister on the round mat. Complete these placements in any order, provided the teapot is placed before its lid."
+    },
+    {
+      "candidate_index": 1,
+      "instruction": "Place the pink, white, and yellow flowers consecutively in the vase, in any order. Place the diffuser bottle on the coaster and insert the reed stick into it, in either order. Either diffuser action may occur before or after the flower sequence, but neither may occur between flower placements.",
+      "task_index": 1
+    },
+    {
+      "candidate_index": 2,
+      "instruction": "Place the three seasoning jars on the two-tier rack in any order, on either tier and in any positions."
+    },
+    {
+      "candidate_index": 3,
+      "instruction": "Hold the pen holder with its opening upward, insert all four pens one by one in any order, then place the filled holder upright."
+    },
+    {
+      "candidate_index": 4,
+      "instruction": "Insert the three plastic plates into the rack in any order and in any slots."
+    },
+    {
+      "candidate_index": 5,
+      "instruction": "Center and align the closed book in the target rectangle. Place the pen along the spine of the open book, close the book, and stack it on the first book."
+    },
+    {
+      "candidate_index": 6,
+      "instruction": "Open the upper drawer, cap the lipstick, and place the lipstick and eyebrow pencil inside. Close the drawer once both are inside. Along the way, place the serum and cleansing oil in the storage area above, in either order—before or after closing the drawer."
+    },
+    {
+      "candidate_index": 7,
+      "instruction": "Place the pen in the holder, place the eraser in the open drawer and close it, switch off the lamp, and unplug it. These actions may be performed in any order, except that the lamp must be switched off before it is unplugged.",
+      "task_index": 0
+    },
+    {
+      "candidate_index": 8,
+      "instruction": "Place the wireless mouse, then the wired earphones, in the cardboard box. Cover both items with bubble wrap."
+    },
+    {
+      "candidate_index": 9,
+      "instruction": "Place the pot, with the spatula inside, on the induction cooker so that most of the pot is over the cooking surface. Turn the handle toward the camera, move the spatula to the basket, and cover the pot with the lid."
+    },
+    {
+      "candidate_index": 10,
+      "instruction": "Place the pig bun on the left, the yellow steamed bun on the right, and the black steamed bun at the front of the upper tier of the two already assembled, in that order. Add the empty tier on top, place the large bun in its center, then cover the steamer with the lid."
+    },
+    {
+      "candidate_index": 11,
+      "instruction": "Take the plate, bowl, fork, and knife out of the crate. Place the plate face up in the lower center of the placemat and the bowl open side up in the upper center, in front of the plate. Place the fork on the left and the knife on the right, with the fork tines and knife tip pointing toward the front. Complete these actions in any order."
+    },
+    {
+      "candidate_index": 12,
+      "instruction": "Place the red block on the yellow drawer, the yellow block on the white drawer, and the blue block on the dark-green drawer, in that order."
+    },
+    {
+      "candidate_index": 13,
+      "instruction": "Place the three colored blocks on the plate one at a time in the order red, green, then blue. Tilt the loaded plate to pour all three blocks into the box."
+    }
+  ]
+}
diff --git a/evaluation/real-world/test-30/annotations/tasks.json b/evaluation/real-world/test-30/annotations/tasks.json
new file mode 100644
index 0000000000000000000000000000000000000000..929a69492f8f64a08389ffa150e35dbe7e460d17
--- /dev/null
+++ b/evaluation/real-world/test-30/annotations/tasks.json
@@ -0,0 +1,148 @@
+{
+  "tasks": [
+    {
+      "task_index": 0,
+      "instruction": "Place the pen in the holder, place the eraser in the open drawer and close it, switch off the lamp, and unplug it. These actions may be performed in any order, except that the lamp must be switched off before it is unplugged.",
+      "subtasks": [
+        {
+          "id": "001",
+          "description": "Place the pen in the pen holder."
+        },
+        {
+          "id": "002",
+          "description": "Place the eraser in the storage box."
+        },
+        {
+          "id": "003",
+          "description": "Close the storage box."
+        },
+        {
+          "id": "004",
+          "description": "Turn off the desk lamp."
+        },
+        {
+          "id": "005",
+          "description": "Unplug the desk lamp."
+        }
+      ],
+      "counterfactual_instructions": [
+        {
+          "id": "001",
+          "description": "Place the eraser in the pen holder, place the pen in the open drawer and close it, switch off the lamp, and unplug it. These actions may be performed in any order, except that the lamp must be switched off before it is unplugged."
+        },
+        {
+          "id": "002",
+          "description": "Place the pen in the holder, place the eraser in the open drawer and leave the drawer open, switch off the lamp, and unplug it. These actions may be performed in any order, except that the lamp must be switched off before it is unplugged."
+        },
+        {
+          "id": "003",
+          "description": "Place the pen beside the holder, place the eraser in the open drawer and close it, switch off the lamp, and unplug it. These actions may be performed in any order, except that the lamp must be switched off before it is unplugged."
+        },
+        {
+          "id": "004",
+          "description": "Switch off the lamp and unplug it before placing the pen in the holder or the eraser in the open drawer. Close the drawer after placing the eraser, and switch off the lamp before unplugging it."
+        }
+      ]
+    },
+    {
+      "task_index": 1,
+      "instruction": "Place the pink, white, and yellow flowers consecutively in the vase, in any order. Place the diffuser bottle on the coaster and insert the reed stick into it, in either order. Either diffuser action may occur before or after the flower sequence, but neither may occur between flower placements.",
+      "subtasks": [
+        {
+          "id": "001",
+          "description": "Insert the first flower into the vase."
+        },
+        {
+          "id": "002",
+          "description": "Insert the second flower into the vase."
+        },
+        {
+          "id": "003",
+          "description": "Insert the third flower into the vase."
+        },
+        {
+          "id": "004",
+          "description": "Place the reed diffuser bottle on the coaster."
+        },
+        {
+          "id": "005",
+          "description": "Insert the diffuser reed into the reed diffuser bottle."
+        }
+      ],
+      "counterfactual_instructions": [
+        {
+          "id": "001",
+          "description": "Place the pink, white, and yellow paintbrushes consecutively in the vase, in any order. Place the diffuser bottle on the coaster and insert the reed stick into it, in either order. Either diffuser action may occur before or after the paintbrush sequence, but neither may occur between paintbrush placements."
+        },
+        {
+          "id": "002",
+          "description": "Place the pink, white, and yellow flowers consecutively in the vase, in any order. Place the diffuser bottle on the coaster and leave the reed stick beside the bottle, in either order. Either diffuser action may occur before or after the flower sequence, but neither may occur between flower placements."
+        },
+        {
+          "id": "003",
+          "description": "Place the pink, white, and yellow flowers consecutively in the vase, in any order. Place the diffuser bottle beside the coaster and insert the reed stick into it, in either order. Either diffuser action may occur before or after the flower sequence, but neither may occur between flower placements."
+        },
+        {
+          "id": "004",
+          "description": "Place the pink and white flowers consecutively in the vase, in any order, and leave the yellow flower on the table. Place the diffuser bottle on the coaster and insert the reed stick into it, in either order. Either diffuser action may occur before or after the flower sequence, but neither may occur between flower placements."
+        }
+      ]
+    },
+    {
+      "task_index": 2,
+      "instruction": "Pick up the drumstick and strike the center of the drumhead 5 times continuously.",
+      "subtasks": [
+        {
+          "id": "001",
+          "description": "Strike the center of the drum for the first time."
+        },
+        {
+          "id": "002",
+          "description": "Strike the center of the drum for the second time."
+        },
+        {
+          "id": "003",
+          "description": "Strike the center of the drum for the third time."
+        },
+        {
+          "id": "004",
+          "description": "Strike the center of the drum for the fourth time."
+        },
+        {
+          "id": "005",
+          "description": "Strike the center of the drum for the fifth time."
+        },
+        {
+          "id": "006",
+          "description": "Place the drumstick on the table."
+        }
+      ]
+    },
+    {
+      "task_index": 3,
+      "instruction": "Press the button 5 times, fully releasing it and returning to the waiting position after each press.",
+      "subtasks": [
+        {
+          "id": "001",
+          "description": "Press the button for the first time."
+        },
+        {
+          "id": "002",
+          "description": "Press the button for the second time."
+        },
+        {
+          "id": "003",
+          "description": "Press the button for the third time."
+        },
+        {
+          "id": "004",
+          "description": "Press the button for the fourth time."
+        },
+        {
+          "id": "005",
+          "description": "Press the button for the fifth time."
+        }
+      ]
+    }
+  ]
+}
diff --git a/evaluation/real-world/test-30/annotations/trr_groups.json b/evaluation/real-world/test-30/annotations/trr_groups.json
new file mode 100644
index 0000000000000000000000000000000000000000..79d2b32230d3911ddcefa73c7d647f307bb3e898
--- /dev/null
+++ b/evaluation/real-world/test-30/annotations/trr_groups.json
@@ -0,0 +1,44 @@
+{
+  "groups": [
+    {
+      "group_index": 0,
+      "task_index": 0,
+      "target_subtask_id": "001",
+      "members": {
+        "ER": 6,
+        "IR": 7,
+        "EC": 8
+      }
+    },
+    {
+      "group_index": 1,
+      "task_index": 0,
+      "target_subtask_id": "002",
+      "members": {
+        "ER": 11,
+        "IR": 10,
+        "EC": 9
+      }
+    },
+    {
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+      }
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+      }
+    }
+  ]
+}
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new file mode 100644
index 0000000000000000000000000000000000000000..e2e31b579e7185bf52c20f4086c9705a8b36c081
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diff --git a/evaluation/simulation/README.md b/evaluation/simulation/README.md
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+# RoboValue Simulation Public Test Sets
+
+[简体中文](README_zh.md) · [Repository overview](../../README.md)
+
+Public simulation diagnostic subsets are stored here, separately from training demonstrations under `data/simulation/`.
+
+| Subset | Tasks | Trajectories | Time steps | Videos | Format |
+| --- | ---: | ---: | ---: | ---: | --- |
+| [Test-30](test-30/README.md) | 4 | 30 | 17,149 | 90 | Visual-input LeRobot v3.0 |
+
+[Test-30 metric coverage](test-30/README.md#metric-coverage) · [Trajectory and video index](test-30/TRAJECTORIES.md) · [Real-world Test-30](../real-world/test-30/README.md)
+
+Each released subset is an independent dataset root. Future simulation subsets can be added beneath this directory with their own data, annotations, documentation, and browsing configuration.
diff --git a/evaluation/simulation/README_zh.md b/evaluation/simulation/README_zh.md
new file mode 100644
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@@ -0,0 +1,13 @@
+# RoboValue 仿真公开测试集
+
+[English](README.md) · [仓库总览](../../README_zh.md)
+
+本目录存放仿真公开诊断测试子集，与 `data/simulation/` 下的训练示范分开。
+
+| 子集 | 任务 | 轨迹 | 时间步 | 视频 | 格式 |
+| --- | ---: | ---: | ---: | ---: | --- |
+| [Test-30](test-30/README_zh.md) | 4 | 30 | 17,149 | 90 | 视觉输入型 LeRobot v3.0 |
+
+[Test-30 指标覆盖](test-30/README_zh.md#metric-coverage) · [轨迹与视频索引](test-30/TRAJECTORIES.md) · [真机 Test-30](../real-world/test-30/README_zh.md)
+
+每个已发布子集均为独立的数据根目录。后续仿真子集可继续放在本目录下，分别提供数据、标注、说明和浏览配置。
diff --git a/evaluation/simulation/test-30/README.md b/evaluation/simulation/test-30/README.md
new file mode 100644
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@@ -0,0 +1,185 @@
+# RoboValue Small-Scale Simulation Public Test Set
+
+[简体中文](README_zh.md) · [Repository overview](../../../README.md) · [Simulation subsets](../README.md) · [All 30 trajectories](TRAJECTORIES.md) · [Parquet catalog](episode_catalog.parquet)
+
+This **In-Domain diagnostic test subset** contains **30 complete simulation trajectories across four tasks**. It provides RGB video inputs, English instructions, and separate annotations for **10 metric entry points**. Standard demonstrations, alternative orders, error/recovery branches, and complete memory histories are retained. Its task and solution coverage is smaller than the complete RoboValue leaderboard test set.
+
+The subset is stored under `evaluation/simulation/test-30/`, separately from training demonstrations in `data/`. Local episode and task indices belong to this subset. Native metadata retains `train: 0:30` for LeRobot container compatibility; the intended use and HF trajectory-catalog split are **test**.
+
+## Tasks and trajectories
+
+| Local task index | Task | Episodes | Local episode indices |
+| ---: | --- | ---: | --- |
+| 0 | Fill Pen Holder | 12 | 0–11 |
+| 1 | Hang Mugs | 12 | 12–23 |
+| 2 | Press By Number | 3 | 24–26 |
+| 3 | Swap Blocks | 3 | 27–29 |
+
+The subset contains **17,149 synchronized time steps at 25 FPS** and **90 AV1 videos**, approximately **0.595 GB (decimal)**. Every episode has one front view and two wrist views, all **640 × 480**, with no audio. Time steps and duration are counted once per episode, not once per camera. Full episodes and their causal history are preserved.
+
+Trajectory types are **ED4 / MS8 / ER4 / IR4 / EC4 / MEM6**. Stored terminal-success labels comprise **22 true and 8 false**. These label counts describe supplied annotations: ED/MS labels and semantic alignment are user-attested, while the 12 TRR branches and 6 MEM episodes retain the status **pending independent terminal evidence**. Technical video/loader checks do not upgrade these statuses to independently certified terminal outcomes. The evidence is preserved per episode and in [`annotation_provenance.json`](annotations/annotation_provenance.json).
+
+`task_index` 0–3 and `episode_index` 0–29 are public local indices. They are independent of training and real-world test subset indices. Source episode identifiers, collection dates, and acquisition paths are absent.
+
+<a id="metric-coverage"></a>
+
+## Which trajectories evaluate which metrics?
+
+[`annotations/metric_membership.json`](annotations/metric_membership.json) is the authoritative membership file. The same asset can participate in several metrics: **86 metric-member references correspond to 30 stored episodes**.
+
+| Metric / code key | What it evaluates | Eligible trajectories | Episodes / groups | Supporting annotations |
+| --- | --- | --- | --- | --- |
+| TGA-CT / `tga_easy` | Distinguishing the correct task from other task instructions | Pen-holder and mug ED | 4 | `tasks.json`, `task_candidates.json` (13 original candidates) |
+| TGA-CF / `tga_hard` | Distinguishing the original goal from counterfactual instructions | Pen-holder and mug ED | 4 | `tasks.json` (4 counterfactual instructions per regular task) |
+| VOC / `voc` | Value ordering along forward task progress | Pen-holder and mug ED | 4 | Original subtask intervals and sampling anchors in `episodes.jsonl` |
+| Cycle-VOC / `cycle_voc` | Value ordering along forward and reverse task progress | Pen-holder and mug ED | 4 | Complete episodes, original intervals, and sampling anchors |
+| VS / `vs` | Stability of the forward value curve | Pen-holder and mug ED | 4 | Same forward episodes and sampling basis used by Cycle-VOC |
+| SA / `sa` | Comparing terminal values under supplied success/failure labels | All pen-holder and mug trajectories | 24; 64 same-task pairs | Stored labels and evidence states in `episodes.jsonl`, original pairings in `sa_pairs.jsonl` |
+| SIA / `sia` | Identifying the chronological semantic subtask being performed | Pen-holder and mug ED/MS | 12 | Original subtask descriptions and intervals |
+| TRR / `trr` | Distinguishing effective recovery, ineffective recovery, and error continuation | Pen-holder and mug ER/IR/EC | 12 / 4 three-role groups | `trr_groups.json`, original failure/recovery stages in `episodes.jsonl` |
+| CSVC / `csvc` | Consistency of semantic value increments across execution orders | Pen-holder and mug ED/MS | 12 / 6 order groups | `csvc_solutions.json`, independent `semantic_alignment.json` |
+| VOC-MEM / `voc_mem` | History-dependent value ordering in repeated or sequential actions | Press-by-number and swap-blocks MEM | 6 | Complete videos and original `voc_mem` sampling anchors |
+
+The four ED episodes are `0, 1, 12, 13`; MEM episodes are `24–29`. The catalog's `metrics` column is generated from this membership file. Counts across metrics overlap and must not be summed to obtain the number of trajectories.
+
+| Trajectory type | Supplied role | Count | Applicable metrics |
+| --- | --- | ---: | --- |
+| ED | Standard successful demonstration | 4 | TGA-CT, TGA-CF, VOC, Cycle-VOC, VS, SA, SIA, CSVC |
+| MS | Successful alternative order | 8 | SA, SIA, CSVC |
+| ER | Effective recovery branch | 4 | SA, TRR |
+| IR | Ineffective recovery branch | 4 | SA, TRR |
+| EC | Error-continuation branch | 4 | SA, TRR |
+| MEM | Complete memory-history episode | 6 | VOC-MEM |
+
+Original FPL fields remain inside per-episode annotations where supplied. This subset has **no formal FPL cohort or FPL metric entry**. TRR groups preserve their members and stages; no unannotated target subtask is inferred. MEM task subtask tables and per-episode `subtask_segments` are **empty as supplied**: sampling anchors and complete history are available, but counting-subtask intervals or per-frame progress ground truth have not been added.
+
+## Chronological and cross-order semantic annotations
+
+SIA uses the original chronological subtask numbering and intervals. CSVC additionally uses stable object/action identities recorded in [`semantic_alignment.json`](annotations/semantic_alignment.json). Both annotation layers are retained; cross-order semantic alignment does not replace or renumber the chronological labels.
+
+Each regular task has **three order groups**, with **two executions per group**: the standard ED order and two alternative MS orders. Together they form **6 groups and 12 episodes**. Their grouping, color order, semantic action order, and per-instance intervals are preserved in [`csvc_solutions.json`](annotations/csvc_solutions.json). This is partial order coverage, not exhaustive coverage of all legal solutions. Supplied evidence for success, independent execution, object identity, and legal order remains user attestation.
+
+Left/right roles are preserved by episode. Standard pen-holder executions use right-arm insertion with left-arm holding; alternative executions use left-arm insertion with right-arm holding. Mug color/action identities and recorded arm assignments are retained. Arms and video views are not mirrored or normalized across order groups.
+
+## Files and annotation semantics
+
+```text
+meta/info.json                         Native format, features, FPS, path templates
+meta/tasks.parquet                     English instructions indexed by task_index
+meta/episodes/chunk-000/file-000.parquet Episode lengths and camera/video references
+data/chunk-000/file-*.parquet           Native per-frame location records
+videos/observation.images.front/       Front-view videos
+videos/observation.images.wrist_left/  Left-wrist videos
+videos/observation.images.wrist_right/ Right-wrist videos
+annotations/                          Separate evaluation annotations
+episode_catalog.parquet               One browsing row per episode
+TRAJECTORIES.md                        Human-readable trajectory and video index
+checksums.sha256                       Release-file integrity manifest
+```
+
+Native data records contain only `timestamp`, `frame_index`, `episode_index`, `index`, and `task_index`. Original float32 episode-relative timestamps and local frame indices are retained; public episode/task indices and the cumulative global `index` are rebuilt. These fields locate images and instructions, rather than providing model observations.
+
+`codebase_version: v3.0` identifies the native format, and `robot_type` is null. State/action vectors, old robot feature metadata, collection information, and source identifiers are omitted. Numeric normalization statistics are omitted because the export has no numeric observation features. Container/encoder additions are cleared with stream copying; frames are not re-encoded, resized, cropped, resampled, or reordered.
+
+| Annotation file | Contents |
+| --- | --- |
+| [`tasks.json`](annotations/tasks.json) | Four local task indices, original English instructions, chronological subtask descriptions, and counterfactual instructions |
+| [`episodes.jsonl`](annotations/episodes.jsonl) | Thirty local episode/task indices, trajectory roles, stored success labels and evidence states, complete original annotation objects |
+| [`metric_membership.json`](annotations/metric_membership.json) | Exact local episode/task cohorts for the 10 metric entry points |
+| [`task_candidates.json`](annotations/task_candidates.json) | Complete 13-instruction cross-task pool and candidate correspondence |
+| [`trr_groups.json`](annotations/trr_groups.json) | Four local groups, ER/IR/EC members, branch roles, and stage intervals |
+| [`csvc_solutions.json`](annotations/csvc_solutions.json) | Six order groups, two executions per group, color/semantic order, and instance relationships |
+| [`semantic_alignment.json`](annotations/semantic_alignment.json) | Stable object/action identities, original chronological IDs, semantic segments, and left/right roles |
+| [`sa_pairs.jsonl`](annotations/sa_pairs.jsonl) | Original 64 same-task success/failure pairings mapped to local indices |
+| [`annotation_provenance.json`](annotations/annotation_provenance.json) | Supplied attestation and verification-evidence meaning, with local episode references |
+
+All frame indices are local and zero-based. Intervals retain their original endpoint values. `start_frame` / `end_frame_exclusive` ranges and legacy FPL `failure_start` / `failure_end` ranges are interpreted as **half-open `[start, end)`**, without adding one to the end. Existing event and action endpoint conventions are retained.
+
+The `annotations` object in each episode preserves the original annotation content. Source-reference fields are mapped to public local episode/group indices. Sampling `frame_index` entries are anchors, not ground-truth value/progress scores or model predictions. Semantic IDs name object/action concepts, and group/solution indices express evaluation relationships rather than acquisition identities.
+
+## Trajectory catalog and HF preview
+
+The `simulation-test-30` configuration explicitly exposes a **`test` split with 30 episode rows** from `episode_catalog.parquet`. Per-frame samples are read with LeRobot. Auxiliary reports and navigation documents are excluded from preview discovery. [`TRAJECTORIES.md`](TRAJECTORIES.md) lists every episode's eligible metrics and direct links to all three camera videos.
+
+Both public test domains use the same 12 catalog columns:
+
+| Field | Type | Meaning |
+| --- | --- | --- |
+| `episode_index`, `task_index` | `int64` | Indices local to this subset |
+| `task_name`, `instruction` | `string` | English display task name and original instruction |
+| `trajectory_type` | `string` | ED, MS, ER, IR, EC, or MEM |
+| `success` | `bool` | Supplied terminal-success label; read its evidence state separately |
+| `num_frames` | `int64` | Episode time-step count, counted once across views |
+| `duration_s` | `float64` | Duration (`num_frames / fps`) |
+| `video_primary`, `video_left_wrist`, `video_right_wrist` | `string` | Paths relative to this subset root; primary is front for simulation, head for real-world |
+| `metrics` | `list[string]` | Eligible code keys from the formal membership file |
+
+Video paths and labels support browsing and evaluation. They are not decoded model observations. Stored success-label evidence is available through the matching entry in `annotations/episodes.jsonl` and the provenance file.
+
+## Download and load
+
+The example is pinned to `578593ef28ee7a2d861ebf38162c928291b0d4a9`, which contains both public test sets, and downloads only this subset. Download and load using the same fixed revision.
+
+```python
+from pathlib import Path
+from huggingface_hub import snapshot_download
+from lerobot.datasets.lerobot_dataset import LeRobotDataset
+
+repo_id = "wzlllong/value-model-benchmark-training-data"
+prefix = "evaluation/simulation/test-30"
+revision = "578593ef28ee7a2d861ebf38162c928291b0d4a9"
+snapshot = snapshot_download(
+    repo_id=repo_id,
+    repo_type="dataset",
+    revision=revision,
+    allow_patterns=[f"{prefix}/**"],
+    local_dir="./robovalue-data",
+)
+root = Path(snapshot) / prefix
+dataset = LeRobotDataset(
+    repo_id=repo_id,
+    root=root,
+    revision=revision,
+    video_backend="pyav",
+    tolerance_s=1e-4,
+)
+item = dataset[0]
+value_input = {
+    "images": {camera: item[camera] for camera in dataset.meta.camera_keys},
+    "instruction": item["task"],
+}
+print(dataset.num_episodes, dataset.num_frames)  # 30, 17149
+```
+
+For an extracted local upload package, set `root = Path("upload/evaluation/simulation/test-30")` and load it with the same constructor, omitting the remote `revision` argument. The root must directly contain `meta/`, `data/`, and `videos/`. Camera keys are `observation.images.front`, `observation.images.wrist_left`, and `observation.images.wrist_right`; loaded images use CHW shape `[3, 480, 640]`.
+
+Send selected images and the instruction to the value model. Read annotation labels, groups, arm roles, trajectory types, stored success flags, and metric membership separately. Native location fields and catalog paths are routing metadata, rather than model observations. History-based models can use `delta_timestamps` to request earlier frames in episode order.
+
+```python
+import json
+
+episodes = {
+    row["episode_index"]: row
+    for row in (
+        json.loads(line)
+        for line in (root / "annotations/episodes.jsonl").read_text().splitlines()
+        if line.strip()
+    )
+}
+episode_index = int(item["episode_index"])
+labels = episodes[episode_index]
+assert int(item["task_index"]) == labels["task_index"]
+membership = json.loads(
+    (root / "annotations/metric_membership.json").read_text()
+)["metrics"]
+eligible_metrics = [
+    key for key, cohort in membership.items()
+    if episode_index in cohort["episode_indices"]
+]
+```
+
+From the subset directory, check the release-file hashes:
+
+```bash
+shasum -a 256 -c checksums.sha256
+```
diff --git a/evaluation/simulation/test-30/README_zh.md b/evaluation/simulation/test-30/README_zh.md
new file mode 100644
index 0000000000000000000000000000000000000000..1084f6f3298cb7bb010ba51ed8b8fadc88b20c22
--- /dev/null
+++ b/evaluation/simulation/test-30/README_zh.md
@@ -0,0 +1,185 @@
+# RoboValue 小规模仿真公开测试集
+
+[English](README.md) · [仓库总览](../../../README_zh.md) · [仿真子集](../README_zh.md) · [全部30条轨迹](TRAJECTORIES.md) · [Parquet目录](episode_catalog.parquet)
+
+这是一个 **In-Domain 诊断测试子集**，包含 **4个任务、30条完整仿真轨迹**，提供RGB视频输入、英文指令，以及独立存放的 **10个指标入口**所需标注。标准示范、替代执行顺序、错误／恢复分支和完整记忆历史均保留。它的任务与方案覆盖范围小于完整 RoboValue 排行榜测试集。
+
+本子集位于 `evaluation/simulation/test-30/`，与 `data/` 下的训练示范分开。任务和轨迹编号仅在本子集内有效。原生元数据保留 `train: 0:30` 以兼容 LeRobot 容器；公开用途及HF逐轨迹目录划分为 **test（测试）**。
+
+## 任务与轨迹
+
+| 子集内任务编号 | 任务 | 轨迹数 | 子集内轨迹编号 |
+| ---: | --- | ---: | --- |
+| 0 | 装填笔筒（Fill Pen Holder） | 12 | 0–11 |
+| 1 | 悬挂马克杯（Hang Mugs） | 12 | 12–23 |
+| 2 | 依照数字按按钮（Press By Number） | 3 | 24–26 |
+| 3 | 交换积木（Swap Blocks） | 3 | 27–29 |
+
+数据包含 **17,149个同步时间步、25 FPS、90个AV1视频**，大小约 **0.595 GB（十进制）**。每条轨迹包含正面、左手腕、右手腕三个同步视角，均为 **640 × 480**、无音频。时间步与时长按每条轨迹计数一次，不按机位累加。完整轨迹及其因果历史均保留。
+
+轨迹类型为 **ED4／MS8／ER4／IR4／EC4／MEM6**。已有终局成功标签共 **22个true、8个false**；这个计数描述的是所提供的标注。ED/MS终局标签和语义对齐来自用户确认；12条TRR分支与6条MEM保留“**终局证据待独立验证**”的状态。视频完整性与加载检查不会将此状态改写为独立认证的终局真值。相关证据保存在每条轨迹及 [`annotation_provenance.json`](annotations/annotation_provenance.json) 中。
+
+`task_index` 0–3、`episode_index` 0–29是公开局部编号，与训练及真机测试子集编号独立。文件不含源轨迹编号、采集日期或来源路径。
+
+<a id="metric-coverage"></a>
+
+## 哪些轨迹用于哪些指标？
+
+[`annotations/metric_membership.json`](annotations/metric_membership.json) 是正式指标归属表。同一条轨迹可参与多个指标，**86次指标成员引用对应30条实际轨迹**。
+
+| 指标／代码键 | 评测用途 | 适用轨迹 | 轨迹数／组数 | 对应标注 |
+| --- | --- | --- | --- | --- |
+| TGA-CT／`tga_easy` | 在不同任务指令中辨别正确目标 | 笔筒、马克杯ED | 4条 | `tasks.json`、`task_candidates.json`（原13个候选） |
+| TGA-CF／`tga_hard` | 区分原目标与反事实任务指令 | 笔筒、马克杯ED | 4条 | `tasks.json`（每个常规任务4条反事实指令） |
+| VOC／`voc` | 检查正向任务进展的价值顺序 | 笔筒、马克杯ED | 4条 | `episodes.jsonl` 原子任务区间及采样锚点 |
+| Cycle-VOC／`cycle_voc` | 检查正向及反向进展的价值顺序 | 笔筒、马克杯ED | 4条 | 完整轨迹、原区间及采样锚点 |
+| VS／`vs` | 检查正向价值曲线的稳定性 | 笔筒、马克杯ED | 4条 | 与Cycle-VOC共享的正向轨迹和采样依据 |
+| SA／`sa` | 在已有成功／失败标签下比较终局价值 | 笔筒、马克杯全部轨迹 | 24条；64个同任务配对 | `episodes.jsonl` 的原标签与证据状态、`sa_pairs.jsonl` 的原配对 |
+| SIA／`sia` | 识别按时间执行的语义子任务 | 笔筒、马克杯ED/MS | 12条 | 原子任务描述及区间 |
+| TRR／`trr` | 区分有效恢复、无效恢复和错误延续 | 笔筒、马克杯ER/IR/EC | 12条／4个三角色组 | `trr_groups.json`、`episodes.jsonl` 原失败／恢复阶段 |
+| CSVC／`csvc` | 检查不同顺序中的语义价值增量一致性 | 笔筒、马克杯ED/MS | 12条／6个顺序组 | `csvc_solutions.json` 与独立 `semantic_alignment.json` |
+| VOC-MEM／`voc_mem` | 重复或顺序动作中依赖历史的价值顺序 | 依数字按按钮、交换积木MEM | 6条 | 完整视频及原 `voc_mem` 采样锚点 |
+
+4条ED编号为 `0、1、12、13`；MEM编号为 `24–29`。轨迹目录的 `metrics` 列由该归属表生成。指标之间会复用轨迹，不能将指标轨迹数相加作为数据总量。
+
+| 轨迹类型 | 原标注角色 | 数量 | 适用指标 |
+| --- | --- | ---: | --- |
+| ED | 标准成功示范 | 4 | TGA-CT、TGA-CF、VOC、Cycle-VOC、VS、SA、SIA、CSVC |
+| MS | 成功替代顺序 | 8 | SA、SIA、CSVC |
+| ER | 有效恢复分支 | 4 | SA、TRR |
+| IR | 无效恢复分支 | 4 | SA、TRR |
+| EC | 错误延续分支 | 4 | SA、TRR |
+| MEM | 保留完整历史的记忆轨迹 | 6 | VOC-MEM |
+
+原标注中已有的FPL字段继续保留，本子集**没有正式FPL集合或FPL指标入口**。TRR保留成员与阶段，不推断未标注的目标子任务。MEM任务子任务表与逐轨迹 `subtask_segments` **按原状保持为空**：数据提供采样锚点和完整历史，未补充计数子任务区间或逐帧进度真值。
+
+## 时间顺序与跨顺序语义标注
+
+SIA使用原时间顺序子任务编号及区间。CSVC另外使用 [`semantic_alignment.json`](annotations/semantic_alignment.json) 中稳定的物体／动作身份。两层标注同时保留，跨顺序语义对齐不覆盖或重新编号原时间顺序标签。
+
+每个常规任务有 **3个顺序组、每组2次执行**：标准ED顺序和两个替代MS顺序。合计 **6个组、12条轨迹**。分组、颜色顺序、语义动作顺序和各次执行区间保存在 [`csvc_solutions.json`](annotations/csvc_solutions.json)。这是部分顺序覆盖，不包含全部可能的合法方案。成功、独立执行、物体身份和合法顺序的已有证据仍标记为用户确认。
+
+左右臂角色按轨迹保留：标准笔筒轨迹使用右臂插笔、左臂持筒；替代轨迹使用左臂插笔、右臂持筒。马克杯颜色／动作身份及原左右臂分工也保留，不对手臂或视频视角做镜像和统一改写。
+
+## 文件与标注语义
+
+```text
+meta/info.json                         原生格式、字段、FPS与路径模板
+meta/tasks.parquet                     按task_index索引的英文指令
+meta/episodes/chunk-000/file-000.parquet 轨迹长度和相机／视频引用
+data/chunk-000/file-*.parquet           原生逐帧定位记录
+videos/observation.images.front/       正面视频
+videos/observation.images.wrist_left/  左手腕视频
+videos/observation.images.wrist_right/ 右手腕视频
+annotations/                          独立评测标注
+episode_catalog.parquet               每条轨迹一行的浏览目录
+TRAJECTORIES.md                        人可读的轨迹与视频索引
+checksums.sha256                       发布文件完整性清单
+```
+
+原生逐帧记录仅含 `timestamp`、`frame_index`、`episode_index`、`index` 和 `task_index`。原float32轨迹内时间戳及局部帧编号保留，公开任务／轨迹编号和累积全局 `index` 重建。这些字段用于定位图像与指令，不是模型观测。
+
+`codebase_version: v3.0` 表示原生格式，`robot_type` 为null。状态／动作向量、旧机器人特征描述、采集信息和来源标识已去除。因视觉导出没有数值观测特征，不提供数值归一化统计。额外容器／编码器信息通过流复制清理，图像未经重新编码、缩放、裁剪、重采样或重排。
+
+| 标注文件 | 内容 |
+| --- | --- |
+| [`tasks.json`](annotations/tasks.json) | 4个局部任务编号、原英文指令、时间顺序子任务及反事实指令 |
+| [`episodes.jsonl`](annotations/episodes.jsonl) | 30条局部任务／轨迹编号、类型、原成功标签与证据状态、完整原标注对象 |
+| [`metric_membership.json`](annotations/metric_membership.json) | 10个正式指标入口的局部任务／轨迹集合 |
+| [`task_candidates.json`](annotations/task_candidates.json) | 原13条跨任务候选池及对应关系 |
+| [`trr_groups.json`](annotations/trr_groups.json) | 4个局部分组、ER/IR/EC成员、分支角色与阶段区间 |
+| [`csvc_solutions.json`](annotations/csvc_solutions.json) | 6个顺序组、每组2次执行、颜色／语义顺序和实例关系 |
+| [`semantic_alignment.json`](annotations/semantic_alignment.json) | 稳定物体／动作身份、原时间顺序编号、语义区间及左右臂角色 |
+| [`sa_pairs.jsonl`](annotations/sa_pairs.jsonl) | 原64个同任务成功／失败配对，映射为局部编号 |
+| [`annotation_provenance.json`](annotations/annotation_provenance.json) | 原有确认与验证证据含义，使用局部轨迹引用 |
+
+帧编号均为从0开始的轨迹内局部编号，所有区间端点保留原值。`start_frame`／`end_frame_exclusive` 和旧FPL的 `failure_start`／`failure_end` 均按**左闭右开 `[start,end)`**解释，不将终点加1。原事件和动作标注的端点约定保留。
+
+每条轨迹的 `annotations` 对象保留完整原标注内容，来源引用字段映射为公开轨迹／分组编号。采样 `frame_index` 是锚点，不是逐帧真实价值／进度分数或模型预测。语义编号表达物体／动作概念，分组和方案编号表达评测关系，不表达采集来源。
+
+## 轨迹目录与HF预览
+
+`simulation-test-30` 配置显式读取 `episode_catalog.parquet`，提供 **`test` 划分、30行轨迹预览**。实际逐帧样本通过LeRobot读取，辅助报告和导航说明不参与自动预览发现。[`TRAJECTORIES.md`](TRAJECTORIES.md) 提供每条轨迹的适用指标及三个机位的视频链接。
+
+两个公开测试领域使用相同的12列：
+
+| 字段 | 类型 | 含义 |
+| --- | --- | --- |
+| `episode_index`、`task_index` | `int64` | 本子集内编号 |
+| `task_name`、`instruction` | `string` | 英文展示任务名及原指令 |
+| `trajectory_type` | `string` | ED、MS、ER、IR、EC或MEM |
+| `success` | `bool` | 原终局成功标签，证据状态单独读取 |
+| `num_frames` | `int64` | 轨迹时间步数，三个机位只计一次 |
+| `duration_s` | `float64` | 时长（`num_frames / fps`） |
+| `video_primary`、`video_left_wrist`、`video_right_wrist` | `string` | 相对子集根目录的路径，主视角为仿真正面／真机头部 |
+| `metrics` | `list[string]` | 正式归属表中的适用指标代码键 |
+
+视频路径和标签用于浏览及评测，不是已解码的模型观测。原成功标签的证据状态可通过 `annotations/episodes.jsonl` 中对应条目及证据文件读取。
+
+## 单独下载与加载
+
+以下示例固定到包含两个公开测试集的版本 `578593ef28ee7a2d861ebf38162c928291b0d4a9`，仅下载本子集。下载和加载使用同一提交。
+
+```python
+from pathlib import Path
+from huggingface_hub import snapshot_download
+from lerobot.datasets.lerobot_dataset import LeRobotDataset
+
+repo_id = "wzlllong/value-model-benchmark-training-data"
+prefix = "evaluation/simulation/test-30"
+revision = "578593ef28ee7a2d861ebf38162c928291b0d4a9"
+snapshot = snapshot_download(
+    repo_id=repo_id,
+    repo_type="dataset",
+    revision=revision,
+    allow_patterns=[f"{prefix}/**"],
+    local_dir="./robovalue-data",
+)
+root = Path(snapshot) / prefix
+dataset = LeRobotDataset(
+    repo_id=repo_id,
+    root=root,
+    revision=revision,
+    video_backend="pyav",
+    tolerance_s=1e-4,
+)
+item = dataset[0]
+value_input = {
+    "images": {camera: item[camera] for camera in dataset.meta.camera_keys},
+    "instruction": item["task"],
+}
+print(dataset.num_episodes, dataset.num_frames)  # 30, 17149
+```
+
+使用本地解压上传包时，设置 `root = Path("upload/evaluation/simulation/test-30")`，使用相同构造方法并省略远程 `revision` 参数。根目录应直接包含 `meta/`、`data/` 和 `videos/`。相机键为 `observation.images.front`、`observation.images.wrist_left`、`observation.images.wrist_right`；加载后图像为CHW顺序 `[3,480,640]`。
+
+价值模型接收所选图像与指令。标签、分组、左右臂角色、类型、成功标记和指标归属单独读取；逐帧定位字段及目录路径用于路由，不是模型观测。需要历史的模型可使用 `delta_timestamps` 按轨迹内顺序读取更早帧。
+
+```python
+import json
+
+episodes = {
+    row["episode_index"]: row
+    for row in (
+        json.loads(line)
+        for line in (root / "annotations/episodes.jsonl").read_text().splitlines()
+        if line.strip()
+    )
+}
+episode_index = int(item["episode_index"])
+labels = episodes[episode_index]
+assert int(item["task_index"]) == labels["task_index"]
+membership = json.loads(
+    (root / "annotations/metric_membership.json").read_text()
+)["metrics"]
+eligible_metrics = [
+    key for key, cohort in membership.items()
+    if episode_index in cohort["episode_indices"]
+]
+```
+
+在本子集目录检查发布文件哈希：
+
+```bash
+shasum -a 256 -c checksums.sha256
+```
diff --git a/evaluation/simulation/test-30/TRAJECTORIES.md b/evaluation/simulation/test-30/TRAJECTORIES.md
new file mode 100644
index 0000000000000000000000000000000000000000..6052a8e11db56421dc5f8fa24cd8e20102a18a84
--- /dev/null
+++ b/evaluation/simulation/test-30/TRAJECTORIES.md
@@ -0,0 +1,55 @@
+# Simulation Test-30: Trajectory Index / 仿真30条轨迹索引
+
+[English documentation](README.md) · [中文说明](README_zh.md)
+
+One row represents one complete trajectory. Three video links refer to its synchronized camera views.
+每行是一条完整轨迹，三个视频链接是同一轨迹的同步机位。指标列表仅由正式 `annotations/metric_membership.json` 生成。
+
+Episode/task indices are local to this subset; they are independent of the training data and the other test domain.
+轨迹和任务编号仅在本子集中有效，与训练集及另一测试领域的编号独立。
+
+The success column preserves stored source labels. ED/MS terminal outcomes are user-confirmed; TRR/MEM terminal evidence remains pending independent verification. See the annotation provenance and README.
+成功列保留源标签。ED/MS终局由用户确认；TRR/MEM终局证据仍待独立核实，详见标注证据及说明。
+
+| Task index | Task / 任务 | Episodes / 轨迹数 |
+| ---: | --- | ---: |
+| 0 | Fill Pen Holder / 装填笔筒 | 12 |
+| 1 | Hang Mugs / 悬挂马克杯 | 12 |
+| 2 | Press By Number / 依照数字按按钮 | 3 |
+| 3 | Swap Blocks / 交换积木 | 3 |
+
+| Episode | Task | Type | Stored success label / 源成功标记 | Frames | Duration (s) | Front / 正面 | Left wrist / 左腕 | Right wrist / 右腕 | Metrics / 指标 |
+| ---: | ---: | --- | --- | ---: | ---: | --- | --- | --- | --- |
+| 0 | 0 | ED | True / 是 | 844 | 33.760 | [Video](videos/observation.images.front/chunk-000/file-000.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-000.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-000.mp4) | TGA-CT, TGA-CF, VOC, Cycle-VOC, VS, SA, SIA, CSVC |
+| 1 | 0 | ED | True / 是 | 753 | 30.120 | [Video](videos/observation.images.front/chunk-000/file-001.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-001.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-001.mp4) | TGA-CT, TGA-CF, VOC, Cycle-VOC, VS, SA, SIA, CSVC |
+| 2 | 0 | MS | True / 是 | 497 | 19.880 | [Video](videos/observation.images.front/chunk-000/file-002.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-002.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-002.mp4) | SA, SIA, CSVC |
+| 3 | 0 | MS | True / 是 | 589 | 23.560 | [Video](videos/observation.images.front/chunk-000/file-003.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-003.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-003.mp4) | SA, SIA, CSVC |
+| 4 | 0 | MS | True / 是 | 466 | 18.640 | [Video](videos/observation.images.front/chunk-000/file-004.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-004.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-004.mp4) | SA, SIA, CSVC |
+| 5 | 0 | MS | True / 是 | 488 | 19.520 | [Video](videos/observation.images.front/chunk-000/file-005.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-005.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-005.mp4) | SA, SIA, CSVC |
+| 6 | 0 | EC | False / 否 | 786 | 31.440 | [Video](videos/observation.images.front/chunk-000/file-006.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-006.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-006.mp4) | SA, TRR |
+| 7 | 0 | ER | True / 是 | 577 | 23.080 | [Video](videos/observation.images.front/chunk-000/file-007.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-007.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-007.mp4) | SA, TRR |
+| 8 | 0 | IR | False / 否 | 773 | 30.920 | [Video](videos/observation.images.front/chunk-000/file-008.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-008.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-008.mp4) | SA, TRR |
+| 9 | 0 | EC | False / 否 | 992 | 39.680 | [Video](videos/observation.images.front/chunk-000/file-009.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-009.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-009.mp4) | SA, TRR |
+| 10 | 0 | ER | True / 是 | 559 | 22.360 | [Video](videos/observation.images.front/chunk-000/file-010.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-010.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-010.mp4) | SA, TRR |
+| 11 | 0 | IR | False / 否 | 1030 | 41.200 | [Video](videos/observation.images.front/chunk-000/file-011.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-011.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-011.mp4) | SA, TRR |
+| 12 | 1 | ED | True / 是 | 583 | 23.320 | [Video](videos/observation.images.front/chunk-000/file-012.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-012.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-012.mp4) | TGA-CT, TGA-CF, VOC, Cycle-VOC, VS, SA, SIA, CSVC |
+| 13 | 1 | ED | True / 是 | 489 | 19.560 | [Video](videos/observation.images.front/chunk-000/file-013.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-013.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-013.mp4) | TGA-CT, TGA-CF, VOC, Cycle-VOC, VS, SA, SIA, CSVC |
+| 14 | 1 | MS | True / 是 | 637 | 25.480 | [Video](videos/observation.images.front/chunk-000/file-014.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-014.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-014.mp4) | SA, SIA, CSVC |
+| 15 | 1 | MS | True / 是 | 566 | 22.640 | [Video](videos/observation.images.front/chunk-000/file-015.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-015.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-015.mp4) | SA, SIA, CSVC |
+| 16 | 1 | MS | True / 是 | 494 | 19.760 | [Video](videos/observation.images.front/chunk-000/file-016.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-016.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-016.mp4) | SA, SIA, CSVC |
+| 17 | 1 | MS | True / 是 | 528 | 21.120 | [Video](videos/observation.images.front/chunk-000/file-017.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-017.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-017.mp4) | SA, SIA, CSVC |
+| 18 | 1 | EC | False / 否 | 460 | 18.400 | [Video](videos/observation.images.front/chunk-000/file-018.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-018.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-018.mp4) | SA, TRR |
+| 19 | 1 | EC | False / 否 | 369 | 14.760 | [Video](videos/observation.images.front/chunk-000/file-019.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-019.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-019.mp4) | SA, TRR |
+| 20 | 1 | ER | True / 是 | 570 | 22.800 | [Video](videos/observation.images.front/chunk-000/file-020.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-020.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-020.mp4) | SA, TRR |
+| 21 | 1 | ER | True / 是 | 534 | 21.360 | [Video](videos/observation.images.front/chunk-000/file-021.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-021.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-021.mp4) | SA, TRR |
+| 22 | 1 | IR | False / 否 | 586 | 23.440 | [Video](videos/observation.images.front/chunk-000/file-022.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-022.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-022.mp4) | SA, TRR |
+| 23 | 1 | IR | False / 否 | 489 | 19.560 | [Video](videos/observation.images.front/chunk-000/file-023.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-023.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-023.mp4) | SA, TRR |
+| 24 | 2 | MEM | True / 是 | 314 | 12.560 | [Video](videos/observation.images.front/chunk-000/file-024.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-024.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-024.mp4) | VOC-MEM |
+| 25 | 2 | MEM | True / 是 | 236 | 9.440 | [Video](videos/observation.images.front/chunk-000/file-025.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-025.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-025.mp4) | VOC-MEM |
+| 26 | 2 | MEM | True / 是 | 372 | 14.880 | [Video](videos/observation.images.front/chunk-000/file-026.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-026.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-026.mp4) | VOC-MEM |
+| 27 | 3 | MEM | True / 是 | 598 | 23.920 | [Video](videos/observation.images.front/chunk-000/file-027.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-027.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-027.mp4) | VOC-MEM |
+| 28 | 3 | MEM | True / 是 | 558 | 22.320 | [Video](videos/observation.images.front/chunk-000/file-028.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-028.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-028.mp4) | VOC-MEM |
+| 29 | 3 | MEM | True / 是 | 412 | 16.480 | [Video](videos/observation.images.front/chunk-000/file-029.mp4) | [Video](videos/observation.images.wrist_left/chunk-000/file-029.mp4) | [Video](videos/observation.images.wrist_right/chunk-000/file-029.mp4) | VOC-MEM |
+
+Duration is frame count divided by FPS, counted once per episode. Files and evaluation labels are for navigation and scoring; model observations are images and the instruction.
+时长为帧数除以帧率，每条轨迹只计一次。文件路径和评测标签用于浏览与评分；模型观测为图像和指令。
diff --git a/evaluation/simulation/test-30/annotations/annotation_provenance.json b/evaluation/simulation/test-30/annotations/annotation_provenance.json
new file mode 100644
index 0000000000000000000000000000000000000000..a321fa20d95a44d06ff242498a659f7e97ec63c0
--- /dev/null
+++ b/evaluation/simulation/test-30/annotations/annotation_provenance.json
@@ -0,0 +1,210 @@
+{
+  "user_attestation": {
+    "episode_indices": [
+      0,
+      1,
+      2,
+      5,
+      3,
+      4,
+      12,
+      13,
+      14,
+      16,
+      15,
+      17
+    ],
+    "source": "explicit user confirmation in task conversation",
+    "confirmed_facts": [
+      "The eight selected candidates genuinely succeed under task terminal conditions and are distinct independent acquisitions.",
+      "Each candidate pair has the same full semantic order and arm assignment; alternative orders are legal, differ from one another and from standard ED.",
+      "Objects can be stably aligned across videos.",
+      "Each main task has two independent same-order ED executions, semantically aligned with MS."
+    ],
+    "automatic_verification": "asset integrity, source boundaries, table/video consistency, loader and query-plan checks only",
+    "capture_run_ids_available": false,
+    "historical_exposure": "unknown"
+  },
+  "terminal_outcomes": [
+    {
+      "episode_index": 0,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 1,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 2,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 3,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 4,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 5,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 6,
+      "success": false,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 7,
+      "success": true,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 8,
+      "success": false,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 9,
+      "success": false,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 10,
+      "success": true,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 11,
+      "success": false,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 12,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 13,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 14,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 15,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 16,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 17,
+      "success": true,
+      "terminal_success_evidence_status": "user_attested_not_automatically_verified",
+      "success_evidence": "user_attestation"
+    },
+    {
+      "episode_index": 18,
+      "success": false,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 19,
+      "success": false,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 20,
+      "success": true,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 21,
+      "success": true,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 22,
+      "success": false,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 23,
+      "success": false,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 24,
+      "success": true,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 25,
+      "success": true,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 26,
+      "success": true,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 27,
+      "success": true,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 28,
+      "success": true,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    },
+    {
+      "episode_index": 29,
+      "success": true,
+      "terminal_success_evidence_status": "pending_independent_terminal_evidence",
+      "success_evidence": "Stored source label retained; import defaults or category rules do not independently establish terminal success."
+    }
+  ]
+}
diff --git a/evaluation/simulation/test-30/annotations/csvc_solutions.json b/evaluation/simulation/test-30/annotations/csvc_solutions.json
new file mode 100644
index 0000000000000000000000000000000000000000..1b42d98e6e29f00c8b94d77461b550ed55016a51
--- /dev/null
+++ b/evaluation/simulation/test-30/annotations/csvc_solutions.json
@@ -0,0 +1,843 @@
+{
+  "tasks": [
+    {
+      "task_index": 0,
+      "solutions": [
+        {
+          "solution_index": 0,
+          "episode_indices": [
+            0,
+            1
+          ],
+          "role": "normal",
+          "solution_kind": "standard_repeat_group",
+          "color_order": [
+            "purple",
+            "blue",
+            "white",
+            "black"
+          ],
+          "semantic_order": [
+            "hold_holder",
+            "insert_purple",
+            "insert_blue",
+            "insert_white",
+            "insert_black",
+            "place_holder"
+          ],
+          "independent_executions": 2,
+          "evidence": "user_attestation",
+          "instances": [
+            {
+              "episode_index": 0,
+              "subtask_segments": [
+                {
+                  "original_subtask_id": "001",
+                  "semantic_id": "hold_holder",
+                  "object_id": "holder",
+                  "action": "hold",
+                  "start_frame": 17,
+                  "end_frame_exclusive": 88,
+                  "arm_roles": {
+                    "left": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "002",
+                  "semantic_id": "insert_purple",
+                  "object_id": "pen_purple",
+                  "action": "insert_into_holder",
+                  "start_frame": 88,
+                  "end_frame_exclusive": 221,
+                  "arm_roles": {
+                    "right": "insert_purple",
+                    "left": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "insert_blue",
+                  "object_id": "pen_blue",
+                  "action": "insert_into_holder",
+                  "start_frame": 221,
+                  "end_frame_exclusive": 362,
+                  "arm_roles": {
+                    "right": "insert_blue",
+                    "left": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "004",
+                  "semantic_id": "insert_white",
+                  "object_id": "pen_white",
+                  "action": "insert_into_holder",
+                  "start_frame": 362,
+                  "end_frame_exclusive": 541,
+                  "arm_roles": {
+                    "right": "insert_white",
+                    "left": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "005",
+                  "semantic_id": "insert_black",
+                  "object_id": "pen_black",
+                  "action": "insert_into_holder",
+                  "start_frame": 541,
+                  "end_frame_exclusive": 752,
+                  "arm_roles": {
+                    "right": "insert_black",
+                    "left": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "006",
+                  "semantic_id": "place_holder",
+                  "object_id": "holder",
+                  "action": "place_on_table",
+                  "start_frame": 752,
+                  "end_frame_exclusive": 808,
+                  "arm_roles": {
+                    "left": "place_holder"
+                  }
+                }
+              ]
+            },
+            {
+              "episode_index": 1,
+              "subtask_segments": [
+                {
+                  "original_subtask_id": "001",
+                  "semantic_id": "hold_holder",
+                  "object_id": "holder",
+                  "action": "hold",
+                  "start_frame": 16,
+                  "end_frame_exclusive": 64,
+                  "arm_roles": {
+                    "left": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "002",
+                  "semantic_id": "insert_purple",
+                  "object_id": "pen_purple",
+                  "action": "insert_into_holder",
+                  "start_frame": 64,
+                  "end_frame_exclusive": 191,
+                  "arm_roles": {
+                    "right": "insert_purple",
+                    "left": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "insert_blue",
+                  "object_id": "pen_blue",
+                  "action": "insert_into_holder",
+                  "start_frame": 191,
+                  "end_frame_exclusive": 333,
+                  "arm_roles": {
+                    "right": "insert_blue",
+                    "left": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "004",
+                  "semantic_id": "insert_white",
+                  "object_id": "pen_white",
+                  "action": "insert_into_holder",
+                  "start_frame": 333,
+                  "end_frame_exclusive": 500,
+                  "arm_roles": {
+                    "right": "insert_white",
+                    "left": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "005",
+                  "semantic_id": "insert_black",
+                  "object_id": "pen_black",
+                  "action": "insert_into_holder",
+                  "start_frame": 500,
+                  "end_frame_exclusive": 668,
+                  "arm_roles": {
+                    "right": "insert_black",
+                    "left": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "006",
+                  "semantic_id": "place_holder",
+                  "object_id": "holder",
+                  "action": "place_on_table",
+                  "start_frame": 668,
+                  "end_frame_exclusive": 715,
+                  "arm_roles": {
+                    "left": "place_holder"
+                  }
+                }
+              ]
+            }
+          ]
+        },
+        {
+          "solution_index": 1,
+          "episode_indices": [
+            2,
+            5
+          ],
+          "role": "diverse",
+          "solution_kind": "diverse_repeat_group",
+          "color_order": [
+            "blue",
+            "white",
+            "black",
+            "purple"
+          ],
+          "semantic_order": [
+            "hold_holder",
+            "insert_blue",
+            "insert_white",
+            "insert_black",
+            "insert_purple",
+            "place_holder"
+          ],
+          "independent_executions": 2,
+          "evidence": "user_attestation",
+          "instances": [
+            {
+              "episode_index": 2,
+              "subtask_segments": [
+                {
+                  "original_subtask_id": "001",
+                  "semantic_id": "hold_holder",
+                  "object_id": "holder",
+                  "action": "hold",
+                  "start_frame": 0,
+                  "end_frame_exclusive": 47,
+                  "arm_roles": {
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "002",
+                  "semantic_id": "insert_blue",
+                  "object_id": "pen_blue",
+                  "action": "insert_into_holder",
+                  "start_frame": 47,
+                  "end_frame_exclusive": 158,
+                  "arm_roles": {
+                    "left": "insert_blue",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "insert_white",
+                  "object_id": "pen_white",
+                  "action": "insert_into_holder",
+                  "start_frame": 158,
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+                  "action": "insert_into_holder",
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+                    "left": "insert_black",
+                    "right": "hold_holder"
+                  }
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+                  "action": "insert_into_holder",
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+                  "end_frame_exclusive": 444,
+                  "arm_roles": {
+                    "left": "insert_purple",
+                    "right": "hold_holder"
+                  }
+                },
+                {
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+                  "object_id": "holder",
+                  "action": "place_on_table",
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+                  "arm_roles": {
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+                  "end_frame_exclusive": 57,
+                  "arm_roles": {
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "002",
+                  "semantic_id": "insert_blue",
+                  "object_id": "pen_blue",
+                  "action": "insert_into_holder",
+                  "start_frame": 57,
+                  "end_frame_exclusive": 120,
+                  "arm_roles": {
+                    "left": "insert_blue",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "insert_white",
+                  "object_id": "pen_white",
+                  "action": "insert_into_holder",
+                  "start_frame": 120,
+                  "end_frame_exclusive": 203,
+                  "arm_roles": {
+                    "left": "insert_white",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "004",
+                  "semantic_id": "insert_black",
+                  "object_id": "pen_black",
+                  "action": "insert_into_holder",
+                  "start_frame": 203,
+                  "end_frame_exclusive": 284,
+                  "arm_roles": {
+                    "left": "insert_black",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "005",
+                  "semantic_id": "insert_purple",
+                  "object_id": "pen_purple",
+                  "action": "insert_into_holder",
+                  "start_frame": 284,
+                  "end_frame_exclusive": 439,
+                  "arm_roles": {
+                    "left": "insert_purple",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "006",
+                  "semantic_id": "place_holder",
+                  "object_id": "holder",
+                  "action": "place_on_table",
+                  "start_frame": 439,
+                  "end_frame_exclusive": 463,
+                  "arm_roles": {
+                    "right": "place_holder"
+                  }
+                }
+              ]
+            }
+          ]
+        },
+        {
+          "solution_index": 2,
+          "episode_indices": [
+            3,
+            4
+          ],
+          "role": "diverse",
+          "solution_kind": "diverse_repeat_group",
+          "color_order": [
+            "blue",
+            "purple",
+            "black",
+            "white"
+          ],
+          "semantic_order": [
+            "hold_holder",
+            "insert_blue",
+            "insert_purple",
+            "insert_black",
+            "insert_white",
+            "place_holder"
+          ],
+          "independent_executions": 2,
+          "evidence": "user_attestation",
+          "instances": [
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+              "episode_index": 3,
+              "subtask_segments": [
+                {
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+                  "semantic_id": "hold_holder",
+                  "object_id": "holder",
+                  "action": "hold",
+                  "start_frame": 0,
+                  "end_frame_exclusive": 55,
+                  "arm_roles": {
+                    "right": "hold_holder"
+                  }
+                },
+                {
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+                  "semantic_id": "insert_blue",
+                  "object_id": "pen_blue",
+                  "action": "insert_into_holder",
+                  "start_frame": 55,
+                  "end_frame_exclusive": 147,
+                  "arm_roles": {
+                    "left": "insert_blue",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "insert_purple",
+                  "object_id": "pen_purple",
+                  "action": "insert_into_holder",
+                  "start_frame": 147,
+                  "end_frame_exclusive": 278,
+                  "arm_roles": {
+                    "left": "insert_purple",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "004",
+                  "semantic_id": "insert_black",
+                  "object_id": "pen_black",
+                  "action": "insert_into_holder",
+                  "start_frame": 278,
+                  "end_frame_exclusive": 391,
+                  "arm_roles": {
+                    "left": "insert_black",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "005",
+                  "semantic_id": "insert_white",
+                  "object_id": "pen_white",
+                  "action": "insert_into_holder",
+                  "start_frame": 391,
+                  "end_frame_exclusive": 541,
+                  "arm_roles": {
+                    "left": "insert_white",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "006",
+                  "semantic_id": "place_holder",
+                  "object_id": "holder",
+                  "action": "place_on_table",
+                  "start_frame": 541,
+                  "end_frame_exclusive": 587,
+                  "arm_roles": {
+                    "right": "place_holder"
+                  }
+                }
+              ]
+            },
+            {
+              "episode_index": 4,
+              "subtask_segments": [
+                {
+                  "original_subtask_id": "001",
+                  "semantic_id": "hold_holder",
+                  "object_id": "holder",
+                  "action": "hold",
+                  "start_frame": 0,
+                  "end_frame_exclusive": 62,
+                  "arm_roles": {
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "002",
+                  "semantic_id": "insert_blue",
+                  "object_id": "pen_blue",
+                  "action": "insert_into_holder",
+                  "start_frame": 62,
+                  "end_frame_exclusive": 142,
+                  "arm_roles": {
+                    "left": "insert_blue",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "insert_purple",
+                  "object_id": "pen_purple",
+                  "action": "insert_into_holder",
+                  "start_frame": 142,
+                  "end_frame_exclusive": 215,
+                  "arm_roles": {
+                    "left": "insert_purple",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "004",
+                  "semantic_id": "insert_black",
+                  "object_id": "pen_black",
+                  "action": "insert_into_holder",
+                  "start_frame": 215,
+                  "end_frame_exclusive": 276,
+                  "arm_roles": {
+                    "left": "insert_black",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "005",
+                  "semantic_id": "insert_white",
+                  "object_id": "pen_white",
+                  "action": "insert_into_holder",
+                  "start_frame": 276,
+                  "end_frame_exclusive": 391,
+                  "arm_roles": {
+                    "left": "insert_white",
+                    "right": "hold_holder"
+                  }
+                },
+                {
+                  "original_subtask_id": "006",
+                  "semantic_id": "place_holder",
+                  "object_id": "holder",
+                  "action": "place_on_table",
+                  "start_frame": 391,
+                  "end_frame_exclusive": 425,
+                  "arm_roles": {
+                    "right": "place_holder"
+                  }
+                }
+              ]
+            }
+          ]
+        }
+      ]
+    },
+    {
+      "task_index": 1,
+      "solutions": [
+        {
+          "solution_index": 0,
+          "episode_indices": [
+            12,
+            13
+          ],
+          "role": "normal",
+          "solution_kind": "standard_repeat_group",
+          "color_order": [
+            "yellow",
+            "white",
+            "purple"
+          ],
+          "semantic_order": [
+            "hang_yellow",
+            "hang_white",
+            "hang_purple"
+          ],
+          "independent_executions": 2,
+          "evidence": "user_attestation",
+          "instances": [
+            {
+              "episode_index": 12,
+              "subtask_segments": [
+                {
+                  "original_subtask_id": "001",
+                  "semantic_id": "hang_yellow",
+                  "object_id": "mug_yellow",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 10,
+                  "end_frame_exclusive": 176,
+                  "arm_roles": {
+                    "left": "hang_yellow"
+                  }
+                },
+                {
+                  "original_subtask_id": "002",
+                  "semantic_id": "hang_white",
+                  "object_id": "mug_white",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 176,
+                  "end_frame_exclusive": 345,
+                  "arm_roles": {
+                    "right": "hang_white"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "hang_purple",
+                  "object_id": "mug_purple",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 345,
+                  "end_frame_exclusive": 549,
+                  "arm_roles": {
+                    "right": "hang_purple"
+                  }
+                }
+              ]
+            },
+            {
+              "episode_index": 13,
+              "subtask_segments": [
+                {
+                  "original_subtask_id": "001",
+                  "semantic_id": "hang_yellow",
+                  "object_id": "mug_yellow",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 12,
+                  "end_frame_exclusive": 131,
+                  "arm_roles": {
+                    "left": "hang_yellow"
+                  }
+                },
+                {
+                  "original_subtask_id": "002",
+                  "semantic_id": "hang_white",
+                  "object_id": "mug_white",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 131,
+                  "end_frame_exclusive": 281,
+                  "arm_roles": {
+                    "right": "hang_white"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "hang_purple",
+                  "object_id": "mug_purple",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 281,
+                  "end_frame_exclusive": 470,
+                  "arm_roles": {
+                    "right": "hang_purple"
+                  }
+                }
+              ]
+            }
+          ]
+        },
+        {
+          "solution_index": 1,
+          "episode_indices": [
+            14,
+            16
+          ],
+          "role": "diverse",
+          "solution_kind": "diverse_repeat_group",
+          "color_order": [
+            "white",
+            "purple",
+            "yellow"
+          ],
+          "semantic_order": [
+            "hang_white",
+            "hang_purple",
+            "hang_yellow"
+          ],
+          "independent_executions": 2,
+          "evidence": "user_attestation",
+          "instances": [
+            {
+              "episode_index": 14,
+              "subtask_segments": [
+                {
+                  "original_subtask_id": "001",
+                  "semantic_id": "hang_white",
+                  "object_id": "mug_white",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 5,
+                  "end_frame_exclusive": 177,
+                  "arm_roles": {
+                    "right": "hang_white"
+                  }
+                },
+                {
+                  "original_subtask_id": "002",
+                  "semantic_id": "hang_purple",
+                  "object_id": "mug_purple",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 177,
+                  "end_frame_exclusive": 441,
+                  "arm_roles": {
+                    "right": "hang_purple"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "hang_yellow",
+                  "object_id": "mug_yellow",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 441,
+                  "end_frame_exclusive": 624,
+                  "arm_roles": {
+                    "left": "hang_yellow"
+                  }
+                }
+              ]
+            },
+            {
+              "episode_index": 16,
+              "subtask_segments": [
+                {
+                  "original_subtask_id": "001",
+                  "semantic_id": "hang_white",
+                  "object_id": "mug_white",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 12,
+                  "end_frame_exclusive": 132,
+                  "arm_roles": {
+                    "right": "hang_white"
+                  }
+                },
+                {
+                  "original_subtask_id": "002",
+                  "semantic_id": "hang_purple",
+                  "object_id": "mug_purple",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 132,
+                  "end_frame_exclusive": 330,
+                  "arm_roles": {
+                    "right": "hang_purple"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "hang_yellow",
+                  "object_id": "mug_yellow",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 330,
+                  "end_frame_exclusive": 492,
+                  "arm_roles": {
+                    "left": "hang_yellow"
+                  }
+                }
+              ]
+            }
+          ]
+        },
+        {
+          "solution_index": 2,
+          "episode_indices": [
+            15,
+            17
+          ],
+          "role": "diverse",
+          "solution_kind": "diverse_repeat_group",
+          "color_order": [
+            "purple",
+            "yellow",
+            "white"
+          ],
+          "semantic_order": [
+            "hang_purple",
+            "hang_yellow",
+            "hang_white"
+          ],
+          "independent_executions": 2,
+          "evidence": "user_attestation",
+          "instances": [
+            {
+              "episode_index": 15,
+              "subtask_segments": [
+                {
+                  "original_subtask_id": "001",
+                  "semantic_id": "hang_purple",
+                  "object_id": "mug_purple",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 8,
+                  "end_frame_exclusive": 205,
+                  "arm_roles": {
+                    "right": "hang_purple"
+                  }
+                },
+                {
+                  "original_subtask_id": "002",
+                  "semantic_id": "hang_yellow",
+                  "object_id": "mug_yellow",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 205,
+                  "end_frame_exclusive": 380,
+                  "arm_roles": {
+                    "left": "hang_yellow"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "hang_white",
+                  "object_id": "mug_white",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 380,
+                  "end_frame_exclusive": 566,
+                  "arm_roles": {
+                    "right": "hang_white"
+                  }
+                }
+              ]
+            },
+            {
+              "episode_index": 17,
+              "subtask_segments": [
+                {
+                  "original_subtask_id": "001",
+                  "semantic_id": "hang_purple",
+                  "object_id": "mug_purple",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 8,
+                  "end_frame_exclusive": 173,
+                  "arm_roles": {
+                    "right": "hang_purple"
+                  }
+                },
+                {
+                  "original_subtask_id": "002",
+                  "semantic_id": "hang_yellow",
+                  "object_id": "mug_yellow",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 173,
+                  "end_frame_exclusive": 376,
+                  "arm_roles": {
+                    "left": "hang_yellow"
+                  }
+                },
+                {
+                  "original_subtask_id": "003",
+                  "semantic_id": "hang_white",
+                  "object_id": "mug_white",
+                  "action": "hang_on_available_hook",
+                  "start_frame": 376,
+                  "end_frame_exclusive": 528,
+                  "arm_roles": {
+                    "right": "hang_white"
+                  }
+                }
+              ]
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "scoring": "Original semantic-gain-symmetric-ratio-v2: normal repeats collapse to one semantic median profile; diverse executions remain separate; no group averaging added."
+}
diff --git a/evaluation/simulation/test-30/annotations/episodes.jsonl b/evaluation/simulation/test-30/annotations/episodes.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..eeca6d848fb0f1b94284418d1ed093610e179a63
--- /dev/null
+++ b/evaluation/simulation/test-30/annotations/episodes.jsonl
@@ -0,0 +1,30 @@
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diff --git a/evaluation/simulation/test-30/annotations/metric_membership.json b/evaluation/simulation/test-30/annotations/metric_membership.json
new file mode 100644
index 0000000000000000000000000000000000000000..89a404a60afb95169ae009a6ce77d5c28aec60de
--- /dev/null
+++ b/evaluation/simulation/test-30/annotations/metric_membership.json
@@ -0,0 +1,170 @@
+{
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diff --git a/evaluation/simulation/test-30/annotations/sa_pairs.jsonl b/evaluation/simulation/test-30/annotations/sa_pairs.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..053b9a38361afefa4ffc050b2fdd9d7f4f0db54c
--- /dev/null
+++ b/evaluation/simulation/test-30/annotations/sa_pairs.jsonl
@@ -0,0 +1,64 @@
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diff --git a/evaluation/simulation/test-30/annotations/semantic_alignment.json b/evaluation/simulation/test-30/annotations/semantic_alignment.json
new file mode 100644
index 0000000000000000000000000000000000000000..93c69752d07d69be79b93ad5b50eff9439823804
--- /dev/null
+++ b/evaluation/simulation/test-30/annotations/semantic_alignment.json
@@ -0,0 +1,910 @@
+{
+  "version": 1,
+  "evidence_basis": "User attestation plus recorded visual mapping; not independent recovery of capture logs.",
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+        "pen_blue": {
+          "color": "blue",
+          "description": "Pale blue broad marker"
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+        "pen_white": {
+          "color": "white",
+          "description": "Slim white pen"
+        },
+        "pen_black": {
+          "color": "black",
+          "description": "Black pen with gold-colored details"
+        }
+      },
+      "semantics": {
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+        },
+        "insert_purple": {
+          "object_id": "pen_purple",
+          "action": "insert_into_holder",
+          "description": "Insert the purple pen into the pen holder."
+        },
+        "insert_blue": {
+          "object_id": "pen_blue",
+          "action": "insert_into_holder",
+          "description": "Insert the blue pen into the pen holder."
+        },
+        "insert_white": {
+          "object_id": "pen_white",
+          "action": "insert_into_holder",
+          "description": "Insert the white pen into the pen holder."
+        },
+        "insert_black": {
+          "object_id": "pen_black",
+          "action": "insert_into_holder",
+          "description": "Insert the black pen into the pen holder."
+        },
+        "place_holder": {
+          "object_id": "holder",
+          "action": "place_on_table",
+          "description": "Place the filled pen holder upright on the table."
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+      }
+    },
+    {
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+          "description": "Yellow mug"
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+        "mug_white": {
+          "color": "white",
+          "description": "White mug with red handle/decoration"
+        },
+        "mug_purple": {
+          "color": "purple",
+          "description": "Pale purple mug"
+        },
+        "rack": {
+          "description": "Mug rack"
+        },
+        "hook_policy": {
+          "description": "Any available legal hook under user-confirmed task semantics; individual physical hooks are not conflated or assigned invented IDs."
+        }
+      },
+      "semantics": {
+        "hang_yellow": {
+          "object_id": "mug_yellow",
+          "action": "hang_on_available_hook",
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+          "action": "hang_on_available_hook",
+          "description": "Hang the white mug on an available hook of the mug rack."
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+        "hang_purple": {
+          "object_id": "mug_purple",
+          "action": "hang_on_available_hook",
+          "description": "Hang the purple mug on an available hook of the mug rack."
+        }
+      }
+    }
+  ],
+  "episodes": [
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+      "episode_index": 0,
+      "task_index": 0,
+      "role": "normal",
+      "solution_index": 0,
+      "semantic_sequence": [
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+        "insert_purple",
+        "insert_blue",
+        "insert_white",
+        "insert_black",
+        "place_holder"
+      ],
+      "segments": [
+        {
+          "original_subtask_id": "001",
+          "semantic_id": "hold_holder",
+          "object_id": "holder",
+          "action": "hold",
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+            "left": "hang_yellow"
+          }
+        },
+        {
+          "original_subtask_id": "003",
+          "semantic_id": "hang_white",
+          "object_id": "mug_white",
+          "action": "hang_on_available_hook",
+          "start_frame": 376,
+          "end_frame_exclusive": 528,
+          "arm_roles": {
+            "right": "hang_white"
+          }
+        }
+      ],
+      "evidence": "user_attestation"
+    }
+  ],
+  "arm_policy": "Preserve per-episode arm roles. Different order groups may use different arms; no arm mirroring or action swapping.",
+  "loader_policy": "Only CSVC uses this semantic overlay; original annotations and regular metric taxonomy remain unchanged."
+}
diff --git a/evaluation/simulation/test-30/annotations/task_candidates.json b/evaluation/simulation/test-30/annotations/task_candidates.json
new file mode 100644
index 0000000000000000000000000000000000000000..a94bfbe55d37d22f11d3cfd10cb28ffabe34dc9b
--- /dev/null
+++ b/evaluation/simulation/test-30/annotations/task_candidates.json
@@ -0,0 +1,58 @@
+{
+  "candidates": [
+    {
+      "candidate_index": 0,
+      "instruction": "Arrange the numbers from left to right to form the largest possible number, and place them on the pad."
+    },
+    {
+      "candidate_index": 1,
+      "instruction": "Pick up the pen holder, place all the pens into it one by one, then put the filled holder back on the table.",
+      "task_index": 0
+    },
+    {
+      "candidate_index": 2,
+      "instruction": "Fold the left sleeve inward toward the opposite chest point, fold the right sleeve inward toward the opposite chest point, then fold the lower hem upward until it is aligned with the shoulders."
+    },
+    {
+      "candidate_index": 3,
+      "instruction": "Hang all three mugs on the mug rack.",
+      "task_index": 1
+    },
+    {
+      "candidate_index": 4,
+      "instruction": "Insert the three tubes into the rack one by one."
+    },
+    {
+      "candidate_index": 5,
+      "instruction": "Pick up two bread slices one by one, place them into the toaster, and press the lever down."
+    },
+    {
+      "candidate_index": 6,
+      "instruction": "Place the alarm clock on the drawer, put the figurine on its stand, place the mouse on the mouse pad, and push the keyboard into the frame."
+    },
+    {
+      "candidate_index": 7,
+      "instruction": "Move the box to the center of the table, then place all the objects into the box."
+    },
+    {
+      "candidate_index": 8,
+      "instruction": "Place the four matching pieces onto the longest peg one by one, place the three matching pieces onto the second-longest peg, place the two matching pieces onto the second-shortest peg, then place the remaining piece onto the shortest peg."
+    },
+    {
+      "candidate_index": 9,
+      "instruction": "Pick up all four bottles one by one and throw them into the dustbin."
+    },
+    {
+      "candidate_index": 10,
+      "instruction": "Stack the three blocks with different textures into one stable pile."
+    },
+    {
+      "candidate_index": 11,
+      "instruction": "Hang the headphones on the headphone stand, close the laptop, then place the closed laptop into the vertical laptop stand."
+    },
+    {
+      "candidate_index": 12,
+      "instruction": "Pick up the broom, pick up and place the dustpan upright on the table, then use the broom to sweep all the objects into the dustpan."
+    }
+  ]
+}
diff --git a/evaluation/simulation/test-30/annotations/tasks.json b/evaluation/simulation/test-30/annotations/tasks.json
new file mode 100644
index 0000000000000000000000000000000000000000..bbf7cacf1adc779b70199760b7eeb9441b1f6df7
--- /dev/null
+++ b/evaluation/simulation/test-30/annotations/tasks.json
@@ -0,0 +1,100 @@
+{
+  "tasks": [
+    {
+      "task_index": 0,
+      "instruction": "Pick up the pen holder, place all the pens into it one by one, then put the filled holder back on the table.",
+      "subtasks": [
+        {
+          "id": "001",
+          "description": "Hold the empty pen holder."
+        },
+        {
+          "id": "002",
+          "description": "Insert the first selected pen into the pen holder."
+        },
+        {
+          "id": "003",
+          "description": "Insert the second selected pen into the pen holder."
+        },
+        {
+          "id": "004",
+          "description": "Insert the third selected pen into the pen holder."
+        },
+        {
+          "id": "005",
+          "description": "Insert the remaining pen into the pen holder."
+        },
+        {
+          "id": "006",
+          "description": "Place the filled pen holder upright on the table."
+        }
+      ],
+      "counterfactual_instructions": [
+        {
+          "id": "counterfactual_1",
+          "description": "Pick up the pen holder, place all the spoons into it one by one, then put the filled holder back on the table."
+        },
+        {
+          "id": "counterfactual_2",
+          "description": "Pick up the pen holder, place all the pens into it one by one, then put the filled holder back on the table upside down."
+        },
+        {
+          "id": "counterfactual_3",
+          "description": "Pick up the pen holder, place all the pens beside it one by one, then put the holder back on the table."
+        },
+        {
+          "id": "counterfactual_4",
+          "description": "Pick up the pen holder, place exactly three pens into it one by one, then put the filled holder back on the table."
+        }
+      ]
+    },
+    {
+      "task_index": 1,
+      "instruction": "Hang all three mugs on the mug rack.",
+      "subtasks": [
+        {
+          "id": "001",
+          "description": "Hang the first cup on an empty hook."
+        },
+        {
+          "id": "002",
+          "description": "Hang the second cup on another empty hook."
+        },
+        {
+          "id": "003",
+          "description": "Hang the third cup on the remaining empty hook."
+        }
+      ],
+      "counterfactual_instructions": [
+        {
+          "id": "counterfactual_1",
+          "description": "Hang all three plates on the mug rack."
+        },
+        {
+          "id": "counterfactual_2",
+          "description": "Stand all three mugs upright on the table."
+        },
+        {
+          "id": "counterfactual_3",
+          "description": "Place all three mugs beside the mug rack."
+        },
+        {
+          "id": "counterfactual_4",
+          "description": "Hang exactly two mugs on the mug rack and leave the remaining mug on the table."
+        }
+      ]
+    },
+    {
+      "task_index": 2,
+      "instruction": "Press the two red buttons the required number of times according to the number cards, then press the blue button to confirm.",
+      "subtasks": [],
+      "counterfactual_instructions": []
+    },
+    {
+      "task_index": 3,
+      "instruction": "Swap the two blocks using the empty mat, pressing the button after each move.",
+      "subtasks": [],
+      "counterfactual_instructions": []
+    }
+  ]
+}
diff --git a/evaluation/simulation/test-30/annotations/trr_groups.json b/evaluation/simulation/test-30/annotations/trr_groups.json
new file mode 100644
index 0000000000000000000000000000000000000000..05a49f731473fedab8cc06db4c2c2bce5d339e53
--- /dev/null
+++ b/evaluation/simulation/test-30/annotations/trr_groups.json
@@ -0,0 +1,248 @@
+{
+  "groups": [
+    {
+      "group_index": 0,
+      "task_index": 0,
+      "members": {
+        "EC": 6,
+        "ER": 7,
+        "IR": 8
+      },
+      "branches": {
+        "EC": {
+          "episode_index": 6,
+          "role": "r_minus",
+          "stages": {
+            "failure_span": {
+              "start_frame": 267,
+              "end_frame_exclusive": 287
+            },
+            "continue_span": {
+              "start_frame": 287,
+              "end_frame_exclusive": 348
+            }
+          }
+        },
+        "ER": {
+          "episode_index": 7,
+          "role": "r_plus",
+          "stages": {
+            "failure_span": {
+              "start_frame": 184,
+              "end_frame_exclusive": 201
+            },
+            "recovery_span": {
+              "start_frame": 201,
+              "end_frame_exclusive": 230
+            },
+            "recovery_success_span": {
+              "start_frame": 230,
+              "end_frame_exclusive": 293
+            }
+          }
+        },
+        "IR": {
+          "episode_index": 8,
+          "role": "r_zero",
+          "stages": {
+            "failure_span": {
+              "start_frame": 239,
+              "end_frame_exclusive": 259
+            },
+            "recovery_span": {
+              "start_frame": 259,
+              "end_frame_exclusive": 306
+            },
+            "recovery_failed_span": {
+              "start_frame": 306,
+              "end_frame_exclusive": 381
+            }
+          }
+        }
+      }
+    },
+    {
+      "group_index": 1,
+      "task_index": 0,
+      "members": {
+        "EC": 9,
+        "ER": 10,
+        "IR": 11
+      },
+      "branches": {
+        "EC": {
+          "episode_index": 9,
+          "role": "r_minus",
+          "stages": {
+            "failure_span": {
+              "start_frame": 848,
+              "end_frame_exclusive": 875
+            },
+            "continue_span": {
+              "start_frame": 875,
+              "end_frame_exclusive": 920
+            }
+          }
+        },
+        "ER": {
+          "episode_index": 10,
+          "role": "r_plus",
+          "stages": {
+            "failure_span": {
+              "start_frame": 387,
+              "end_frame_exclusive": 398
+            },
+            "recovery_span": {
+              "start_frame": 398,
+              "end_frame_exclusive": 459
+            },
+            "recovery_success_span": {
+              "start_frame": 459,
+              "end_frame_exclusive": 512
+            }
+          }
+        },
+        "IR": {
+          "episode_index": 11,
+          "role": "r_zero",
+          "stages": {
+            "failure_span": {
+              "start_frame": 753,
+              "end_frame_exclusive": 787
+            },
+            "recovery_span": {
+              "start_frame": 787,
+              "end_frame_exclusive": 911
+            },
+            "recovery_failed_span": {
+              "start_frame": 911,
+              "end_frame_exclusive": 959
+            }
+          }
+        }
+      }
+    },
+    {
+      "group_index": 2,
+      "task_index": 1,
+      "members": {
+        "EC": 18,
+        "ER": 20,
+        "IR": 22
+      },
+      "branches": {
+        "EC": {
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+          "role": "r_minus",
+          "stages": {
+            "failure_span": {
+              "start_frame": 103,
+              "end_frame_exclusive": 143
+            },
+            "continue_span": {
+              "start_frame": 143,
+              "end_frame_exclusive": 173
+            }
+          }
+        },
+        "ER": {
+          "episode_index": 20,
+          "role": "r_plus",
+          "stages": {
+            "failure_span": {
+              "start_frame": 81,
+              "end_frame_exclusive": 121
+            },
+            "recovery_span": {
+              "start_frame": 121,
+              "end_frame_exclusive": 242
+            },
+            "recovery_success_span": {
+              "start_frame": 242,
+              "end_frame_exclusive": 277
+            }
+          }
+        },
+        "IR": {
+          "episode_index": 22,
+          "role": "r_zero",
+          "stages": {
+            "failure_span": {
+              "start_frame": 84,
+              "end_frame_exclusive": 131
+            },
+            "recovery_span": {
+              "start_frame": 131,
+              "end_frame_exclusive": 226
+            },
+            "recovery_failed_span": {
+              "start_frame": 226,
+              "end_frame_exclusive": 281
+            }
+          }
+        }
+      }
+    },
+    {
+      "group_index": 3,
+      "task_index": 1,
+      "members": {
+        "EC": 19,
+        "ER": 21,
+        "IR": 23
+      },
+      "branches": {
+        "EC": {
+          "episode_index": 19,
+          "role": "r_minus",
+          "stages": {
+            "failure_span": {
+              "start_frame": 297,
+              "end_frame_exclusive": 328
+            },
+            "continue_span": {
+              "start_frame": 328,
+              "end_frame_exclusive": 366
+            }
+          }
+        },
+        "ER": {
+          "episode_index": 21,
+          "role": "r_plus",
+          "stages": {
+            "failure_span": {
+              "start_frame": 343,
+              "end_frame_exclusive": 374
+            },
+            "recovery_span": {
+              "start_frame": 374,
+              "end_frame_exclusive": 496
+            },
+            "recovery_success_span": {
+              "start_frame": 496,
+              "end_frame_exclusive": 531
+            }
+          }
+        },
+        "IR": {
+          "episode_index": 23,
+          "role": "r_zero",
+          "stages": {
+            "failure_span": {
+              "start_frame": 307,
+              "end_frame_exclusive": 343
+            },
+            "recovery_span": {
+              "start_frame": 343,
+              "end_frame_exclusive": 441
+            },
+            "recovery_failed_span": {
+              "start_frame": 441,
+              "end_frame_exclusive": 485
+            }
+          }
+        }
+      }
+    }
+  ]
+}
diff --git a/evaluation/simulation/test-30/checksums.sha256 b/evaluation/simulation/test-30/checksums.sha256
new file mode 100644
index 0000000000000000000000000000000000000000..00b422642848333fae5bafc4fc41bdda0c1de260
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diff --git a/subset_catalog.json b/subset_catalog.json
index 092d4ef7bd3a35e8ea2e7b356ed58e0540ab5e53..c8b38a5723954a1750786ca977af6cd472e79d77 100644
--- a/subset_catalog.json
+++ b/subset_catalog.json
@@ -13,7 +13,8 @@
       "name_zh": "仿真世界",
       "subsets": [
         "simulation-full-shot-data",
-        "simulation-one-shot-data"
+        "simulation-one-shot-data",
+        "simulation-test-30"
       ],
       "platform": "ARX"
     },
@@ -23,7 +24,8 @@
       "name_zh": "真实世界",
       "subsets": [
         "real-world-full-shot-data",
-        "real-world-one-shot-data"
+        "real-world-one-shot-data",
+        "real-world-test-30"
       ],
       "platform": "AgiBot Genie02"
     }
@@ -433,9 +435,181 @@
           "selection": "minimum original episode_id in the 27-episode tea refresh batch"
         }
       ]
+    },
+    {
+      "subset_id": "real-world-test-30",
+      "domain": "real-world",
+      "role": "evaluation",
+      "semantic_split": "test",
+      "availability": "available",
+      "name_en": "Small-Scale Real-World Public Diagnostic Test Set",
+      "name_zh": "小规模真机公开诊断测试集",
+      "path_in_repo": "evaluation/real-world/test-30",
+      "format": "LeRobot v3.0",
+      "tasks": 4,
+      "episodes": 30,
+      "frames": 27498,
+      "fps": 30,
+      "camera_streams_per_episode": 3,
+      "videos": 90,
+      "size_bytes": 382082604,
+      "duration_seconds": 916.6,
+      "splits": {
+        "train": "0:30"
+      },
+      "native_split_note": "train is the LeRobot container split; the collection is intended for evaluation.",
+      "evaluation_scope": "small-scale real-world In-Domain diagnostic subset with partial solution coverage",
+      "model_inputs": [
+        "images",
+        "instruction"
+      ],
+      "annotations": "evaluation/real-world/test-30/annotations",
+      "documentation": {
+        "en": "evaluation/real-world/test-30/README.md",
+        "zh": "evaluation/real-world/test-30/README_zh.md"
+      },
+      "hf_config": "real-world-test-30",
+      "hf_split": "test",
+      "episode_catalog": "evaluation/real-world/test-30/episode_catalog.parquet",
+      "checksums": "evaluation/real-world/test-30/checksums.sha256",
+      "metric_keys": [
+        "tga_easy",
+        "tga_hard",
+        "voc",
+        "cycle_voc",
+        "vs",
+        "sa",
+        "sia",
+        "csvc",
+        "trr",
+        "fpl",
+        "voc_mem"
+      ],
+      "display_task_names": [
+        "Organize Desktop Workstation",
+        "Arrange Flowers and Reed Diffuser",
+        "Strike Drum Five Times",
+        "Press Button Five Times"
+      ],
+      "display_task_names_zh": [
+        "整理书桌工作区",
+        "插花与摆放藤条香薰",
+        "敲鼓五次",
+        "按按钮五次"
+      ],
+      "index_scope": "task_index and episode_index are local to this subset and independent of training subset indices.",
+      "task_episode_counts": [
+        {
+          "task_index": 0,
+          "episodes": 12
+        },
+        {
+          "task_index": 1,
+          "episodes": 12
+        },
+        {
+          "task_index": 2,
+          "episodes": 3
+        },
+        {
+          "task_index": 3,
+          "episodes": 3
+        }
+      ],
+      "primary_camera": "observation.images.top_head",
+      "primary_video_column": "video_primary",
+      "data_revision": "578593ef28ee7a2d861ebf38162c928291b0d4a9"
+    },
+    {
+      "subset_id": "simulation-test-30",
+      "domain": "simulation",
+      "role": "evaluation",
+      "semantic_split": "test",
+      "availability": "available",
+      "name_en": "Small-Scale Simulation Public Diagnostic Test Set",
+      "name_zh": "小规模仿真公开诊断测试集",
+      "path_in_repo": "evaluation/simulation/test-30",
+      "format": "LeRobot v3.0",
+      "tasks": 4,
+      "episodes": 30,
+      "frames": 17149,
+      "fps": 25,
+      "camera_streams_per_episode": 3,
+      "videos": 90,
+      "duration_seconds": 685.96,
+      "splits": {
+        "train": "0:30"
+      },
+      "native_split_note": "train is the LeRobot container split; the collection is intended for evaluation.",
+      "evaluation_scope": "small-scale simulation In-Domain diagnostic subset with partial solution coverage",
+      "model_inputs": [
+        "images",
+        "instruction"
+      ],
+      "annotations": "evaluation/simulation/test-30/annotations",
+      "documentation": {
+        "en": "evaluation/simulation/test-30/README.md",
+        "zh": "evaluation/simulation/test-30/README_zh.md"
+      },
+      "hf_config": "simulation-test-30",
+      "hf_split": "test",
+      "episode_catalog": "evaluation/simulation/test-30/episode_catalog.parquet",
+      "checksums": "evaluation/simulation/test-30/checksums.sha256",
+      "metric_keys": [
+        "tga_easy",
+        "tga_hard",
+        "voc",
+        "cycle_voc",
+        "vs",
+        "sa",
+        "sia",
+        "csvc",
+        "trr",
+        "voc_mem"
+      ],
+      "display_task_names": [
+        "Fill Pen Holder",
+        "Hang Mugs",
+        "Press By Number",
+        "Swap Blocks"
+      ],
+      "display_task_names_zh": [
+        "装填笔筒",
+        "悬挂马克杯",
+        "依照数字按按钮",
+        "交换积木"
+      ],
+      "index_scope": "task_index and episode_index are local to this subset and independent of training and real-world test subset indices.",
+      "task_episode_counts": [
+        {
+          "task_index": 0,
+          "episodes": 12
+        },
+        {
+          "task_index": 1,
+          "episodes": 12
+        },
+        {
+          "task_index": 2,
+          "episodes": 3
+        },
+        {
+          "task_index": 3,
+          "episodes": 3
+        }
+      ],
+      "primary_camera": "observation.images.front",
+      "primary_video_column": "video_primary",
+      "annotation_evidence_note": "ED/MS terminal labels and semantic alignment are user-attested; TRR/MEM terminal-label evidence remains pending independent verification.",
+      "size_bytes": 594582001,
+      "data_revision": "578593ef28ee7a2d861ebf38162c928291b0d4a9"
     }
   ],
   "planned_subsets": [],
   "data_revision": "7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145",
-  "publication_authorization": "All data were authorized before public release."
+  "publication_authorization": "All data were authorized before public release.",
+  "pretty_name": "RoboValue Training and Evaluation Data",
+  "training_data_revision": "7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145",
+  "revision_note": "data_revision and training_data_revision refer to existing training payloads; use the commit containing both public test subsets for evaluation/real-world/test-30 and evaluation/simulation/test-30.",
+  "evaluation_data_revision": "578593ef28ee7a2d861ebf38162c928291b0d4a9"
 }