Clarify task mirror and dataset usage

README.md

@@ -1,31 +1,65 @@
 ---
-license: mit
+pretty_name: PACE-Bench
 language:
   - en
-pretty_name: PACE-Bench
+license: mit
+size_categories:
+  - n<1K
+task_categories:
+  - text-generation
 tags:
   - benchmark
-  - physics
-  - code-generation
   - agents
+  - agent-evaluation
   - self-evolving-agents
+  - physics
+  - physical-reasoning
+  - code
+  - code-generation
+  - executable-design
   - simulation
+  - box2d
+  - dynamic-environments
+citation: |
+  @misc{zhan2026pacebench,
+    title={PACE-Bench: Benchmarking Physics Adaptation via Code Evolution in Dynamic Environments},
+    author={Yuhao Zhan and Bingxiang He and Zecong Tang and Chaojun Xiao},
+    year={2026},
+    howpublished={\url{https://github.com/thunlp/PACE-Bench}}
+  }
+source_datasets: []
 ---
 
+> **Task mirror only.** This dataset repository contains the 36 executable task definitions. The CLI, shared runtime, evaluation engine, self-evolving methods, reporting code, and coding-agent sandbox live in the [PACE-Bench GitHub repository](https://github.com/thunlp/PACE-Bench).
+
+<details>
+<summary>Mirror provenance</summary>
+
+- Source: [`src/pace_bench/tasks/categories`](https://github.com/thunlp/PACE-Bench/tree/main/src/pace_bench/tasks/categories)
+- Mirrored source commit: [`eeab7d6`](https://github.com/yuhao-zhan/PACE-Bench/commit/eeab7d6b5233468c10f8bb094fe77fb90575af74)
+- Included: 36 base tasks and `primitives_api.json`
+- Excluded: shared runtime, evaluation methods, generated results, caches, and local artifacts
+
+</details>
+
 # PACE-Bench
 
 **PACE-Bench: Benchmarking Physics Adaptation via Code Evolution in Dynamic Environments** evaluates whether an agent can adapt an executable physical design after its environment changes.
 
-## Overview
+[![GitHub](https://img.shields.io/badge/GitHub-Code-181717?logo=github)](https://github.com/thunlp/PACE-Bench)
+[![License](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/thunlp/PACE-Bench/blob/main/LICENSE)
+[![Python](https://img.shields.io/badge/Python-3.10-blue.svg)](https://www.python.org/)
+
+## What is PACE-Bench?
 
-PACE-Bench contains **144 source-to-target adaptation pairs across six physics domains**. Each pair preserves the same task goal and interface:
+PACE-Bench contains **144 source-to-target adaptation pairs across six physics domains**. Each pair keeps the goal and interface fixed:
 
-1. A code-driven design succeeds in a source environment.
-2. The same design fails in a mutated target environment.
-3. The agent receives diagnostic sandbox feedback and iteratively revises the design.
+1. A **code-driven design** succeeds in the source environment.
+2. The same design fails in a **mutated target environment**.
+3. The agent uses **diagnostic sandbox feedback** to revise the design.
 4. The adapted design must succeed under the target physics.
 
-| Property | Count |
+| Benchmark scale | Count |
 | --- | ---: |
 | Physics domains | 6 |
 | Base tasks | 36 |
@@ -33,107 +67,107 @@ PACE-Bench contains **144 source-to-target adaptation pairs across six physics d
 | Evaluation environments | 180 |
 | Source-to-target pairs | 144 |
 
-The six domains cover **statics, kinematics, dynamics, granular/fluid interaction, control, and exotic physics**.
+## What is included here?
 
-## Repository contents
+| Domain | Prefix | Tasks |
+| --- | --- | ---: |
+| Statics / Equilibrium | `S` | 6 |
+| Kinematics / Linkages | `K` | 6 |
+| Dynamics / Energy | `D` | 6 |
+| Granular / Fluid Interaction | `F` | 6 |
+| Cybernetics / Control | `C` | 6 |
+| Exotic Physics | `E` | 6 |
 
 ```text
 tasks/
-├── Category1_Statics_Equilibrium/
-├── Category2_Kinematics_Linkages/
-├── Category3_Dynamics_Energy/
-├── Category4_Granular_FluidInteraction/
-├── Category5_Cybernetics_Control/
-├── Category6_ExoticPhysics/
+├── Category1_Statics_Equilibrium/S_01 ... S_06/
+├── Category2_Kinematics_Linkages/K_01 ... K_06/
+├── Category3_Dynamics_Energy/D_01 ... D_06/
+├── Category4_Granular_FluidInteraction/F_01 ... F_06/
+├── Category5_Cybernetics_Control/C_01 ... C_06/
+├── Category6_ExoticPhysics/E_01 ... E_06/
 └── primitives_api.json
 ```
 
-Each domain contains six tasks. Every task directory includes:
+Each task package contains:
 
 | File | Role |
 | --- | --- |
 | `agent.py` | Source and four target reference solutions |
 | `environment.py` | Box2D world, primitives, and mutable physics |
-| `evaluator.py` | Success criteria, scores, constraints, and metrics |
+| `evaluator.py` | Success criteria, score, constraints, and raw metrics |
 | `feedback.py` | Diagnostic feedback derived from measured metrics |
 | `prompt.py` | Task description, exposed values, and primitive API |
 | `renderer.py` | Evaluation-neutral visualization |
-| `stages.py` | Four target mutations and visibility-aware prompt updates |
-
-These files are **executable benchmark definitions**, not a conventional row-based dataset. The Hugging Face Dataset Viewer is therefore not the main interface.
+| `stages.py` | Four target mutations and prompt updates |
 
-## Download
+These are **executable benchmark definitions**, not a conventional row-based dataset. The Dataset Viewer is therefore not the primary interface.
 
-Download the complete snapshot:
+## Download the task mirror
 
 ```python
 from huggingface_hub import snapshot_download
 
-dataset_path = snapshot_download(
-    repo_id="YuhaoZhan/PACE-Bench",
-    repo_type="dataset",
-)
-print(dataset_path)
-```
-
-Download only the executable tasks:
-
-```python
-from huggingface_hub import snapshot_download
-
-tasks_path = snapshot_download(
+path = snapshot_download(
     repo_id="YuhaoZhan/PACE-Bench",
     repo_type="dataset",
     allow_patterns=["tasks/**"],
 )
+print(path)
 ```
 
-You can also clone the dataset repository:
+Or clone it directly:
 
 ```bash
 git clone https://huggingface.co/datasets/YuhaoZhan/PACE-Bench
 ```
 
-## Running the benchmark
+Use this mirror when you need to inspect, archive, or distribute the task definitions without the full evaluation stack.
 
-The task definitions depend on the PACE-Bench runtime, evaluator, and shared prompt infrastructure. Install and run the full benchmark from the official code repository:
+## Run the benchmark
+
+The Hugging Face mirror is **not standalone**. For evaluation, install the complete GitHub repository with [uv](https://docs.astral.sh/uv/):
 
 ```bash
 git clone https://github.com/thunlp/PACE-Bench.git
 cd PACE-Bench
-conda create -n pace-bench python=3.10 -y
-conda activate pace-bench
-python -m pip install -r requirements.txt
+
+uv venv .venv --python 3.10
+source .venv/bin/activate  # Windows: .venv\Scripts\activate
+uv pip install -r requirements.txt
 
 pace-bench list --task S_01
 pace-bench validate --task S_01
 ```
 
-See the [PACE-Bench GitHub repository](https://github.com/thunlp/PACE-Bench) for evaluation commands, supported providers and methods, result reporting, and coding-agent evaluation.
+The GitHub checkout already contains the same task definitions. You do **not** need to download this mirror separately to run PACE-Bench.
 
 ## Intended use
 
-PACE-Bench is intended for:
-
-- evaluating adaptation after controlled physical environment changes;
-- studying feedback-driven code evolution and self-evolving agents;
-- comparing context-, memory-, search-, and parameter-based methods;
-- analyzing physical reasoning, redesign, exploration, and convergence failures.
+- Evaluate adaptation after controlled physical environment changes
+- Study feedback-driven code evolution and self-evolving agents
+- Compare context-, memory-, search-, and parameter-based methods
+- Analyze physical reasoning, redesign, exploration, and convergence failures
+- Inspect or extend executable task definitions
 
 ## Scope and limitations
 
-- The current release focuses on **2D rigid-body systems in Box2D**.
-- It does not cover 3D or deformable physics, full fluids, perception, navigation, or multi-agent coordination.
-- Prompts and diagnostic feedback are currently English-only.
-- Generated solutions should be evaluated on a dedicated host without unrelated credentials.
+- **Physics:** 2D rigid-body systems in Box2D
+- **Language:** English prompts and diagnostic feedback
+- **Not covered:** 3D/deformable physics, full fluids, perception, navigation, and multi-agent coordination
+- **Execution safety:** run generated code on a dedicated evaluator host without unrelated credentials
+
+## Issues and contributions
+
+The Hugging Face repository is a distribution mirror. Please open task issues, fixes, and pull requests in the [GitHub repository](https://github.com/thunlp/PACE-Bench).
 
 ## License
 
-PACE-Bench is released under the **MIT License**.
+PACE-Bench is released under the [MIT License](https://github.com/thunlp/PACE-Bench/blob/main/LICENSE).
 
 ## Citation
 
-The paper citation will be added when the public preprint is available. Until then, please cite the project repository:
+The public preprint link will be added after release. Until then, please cite the project:
 
 ```bibtex
 @misc{zhan2026pacebench,