diff --git a/examples/openarms/unify_task.py b/examples/openarms/unify_task.py
index 30610ca1a..81fe93f95 100644
--- a/examples/openarms/unify_task.py
+++ b/examples/openarms/unify_task.py
@@ -32,7 +32,6 @@ from __future__ import annotations
 
 import argparse
 import logging
-import shutil
 from pathlib import Path
 
 import pandas as pd
@@ -79,71 +78,45 @@ def unify_dataset_tasks(
     logging.info(f"Source dataset: {src_meta.total_episodes} episodes, {src_meta.total_frames} frames")
     logging.info(f"Original tasks: {len(src_meta.tasks)}")
 
-    # Create output directory
-    if output_root.exists():
-        logging.warning(f"Output directory {output_root} exists, removing it")
-        shutil.rmtree(output_root)
-
-    output_root.mkdir(parents=True, exist_ok=True)
-
-    # Copy videos directory (no changes needed)
-    src_videos = input_root / "videos"
-    if src_videos.exists():
-        logging.info("Copying videos...")
-        shutil.copytree(src_videos, output_root / "videos")
+    # Modify in-place (input_root == output_root supported)
+    data_dir = input_root / DATA_DIR
 
     # Process data files - set all task_index to 0
-    logging.info("Processing data files...")
-    src_data_dir = input_root / DATA_DIR
-    dst_data_dir = output_root / DATA_DIR
-    dst_data_dir.mkdir(parents=True, exist_ok=True)
-
-    for src_parquet in tqdm(sorted(src_data_dir.rglob("*.parquet")), desc="Processing data"):
-        rel_path = src_parquet.relative_to(input_root)
-        dst_parquet = output_root / rel_path
-        dst_parquet.parent.mkdir(parents=True, exist_ok=True)
-
-        df = pd.read_parquet(src_parquet)
+    logging.info("Processing data files (in-place)...")
+    for parquet_file in tqdm(sorted(data_dir.rglob("*.parquet")), desc="Processing data"):
+        df = pd.read_parquet(parquet_file)
         df["task_index"] = 0  # All tasks unified to index 0
-        df.to_parquet(dst_parquet)
+        df.to_parquet(parquet_file)
 
     # Process episodes metadata - set all tasks to unified task
-    logging.info("Processing episodes metadata...")
-    src_episodes_dir = input_root / "meta" / "episodes"
-    dst_episodes_dir = output_root / "meta" / "episodes"
-    dst_episodes_dir.mkdir(parents=True, exist_ok=True)
+    logging.info("Processing episodes metadata (in-place)...")
+    episodes_dir = input_root / "meta" / "episodes"
+    if episodes_dir.exists():
+        for parquet_file in tqdm(sorted(episodes_dir.rglob("*.parquet")), desc="Processing episodes"):
+            df = pd.read_parquet(parquet_file)
+            df["tasks"] = [[UNIFIED_TASK]] * len(df)  # All episodes get the unified task
+            df.to_parquet(parquet_file)
+    else:
+        logging.warning(f"No episodes directory found at {episodes_dir}, skipping")
 
-    for src_parquet in tqdm(sorted(src_episodes_dir.rglob("*.parquet")), desc="Processing episodes"):
-        rel_path = src_parquet.relative_to(src_episodes_dir)
-        dst_parquet = dst_episodes_dir / rel_path
-        dst_parquet.parent.mkdir(parents=True, exist_ok=True)
-
-        df = pd.read_parquet(src_parquet)
-        df["tasks"] = [[UNIFIED_TASK]] * len(df)  # All episodes get the unified task
-        df.to_parquet(dst_parquet)
-
-    # Create new tasks.parquet with single task
+    # Update tasks.parquet with single task
     logging.info(f"Creating single task: {UNIFIED_TASK}")
     new_tasks = pd.DataFrame({"task_index": [0]}, index=[UNIFIED_TASK])
-    write_tasks(new_tasks, output_root)
+    write_tasks(new_tasks, input_root)
 
     # Update info.json
     new_info = src_meta.info.copy()
     new_info["total_tasks"] = 1
-    write_info(new_info, output_root)
+    write_info(new_info, input_root)
 
-    # Copy stats.json (unchanged)
-    if src_meta.stats:
-        write_stats(src_meta.stats, output_root)
-
-    logging.info(f"Dataset saved to {output_root}")
+    logging.info(f"Dataset modified in-place at {input_root}")
     logging.info(f"Task: {UNIFIED_TASK}")
 
     if push_to_hub:
         from lerobot.datasets.lerobot_dataset import LeRobotDataset
 
-        logging.info(f"Pushing {output_repo_id} to hub")
-        dataset = LeRobotDataset(output_repo_id, root=output_root)
+        logging.info(f"Pushing {input_repo_id} to hub")
+        dataset = LeRobotDataset(input_repo_id, root=input_root)
         dataset.push_to_hub(private=True)
         logging.info("Push complete!")