diff --git a/datasets/mlab-real/cifar10/environment/Dockerfile b/datasets/mlab-real/cifar10/environment/Dockerfile
new file mode 100644
index 0000000000000000000000000000000000000000..24c5bf2d83029b6f132fe0558bc3bc7c10a7da48
--- /dev/null
+++ b/datasets/mlab-real/cifar10/environment/Dockerfile
@@ -0,0 +1,5 @@
+FROM autods-mlab-vision:latest
+COPY prepare.py /opt/mlab/prepare.py
+COPY data /opt/mlab/data
+RUN /opt/venvs/vision/bin/python /opt/mlab/prepare.py || python /opt/mlab/prepare.py
+WORKDIR /workspace
diff --git a/datasets/mlab-real/cifar10/environment/data/answer.csv b/datasets/mlab-real/cifar10/environment/data/answer.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bf265fef4aecd1c6e8efd2b88d1f065cbc2c150f
--- /dev/null
+++ b/datasets/mlab-real/cifar10/environment/data/answer.csv
@@ -0,0 +1,2001 @@
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diff --git a/datasets/mlab-real/cifar10/environment/data/test.csv b/datasets/mlab-real/cifar10/environment/data/test.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4e1064a821c070a005d4970993c525d7087af0fd
--- /dev/null
+++ b/datasets/mlab-real/cifar10/environment/data/test.csv
@@ -0,0 +1,2001 @@
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diff --git a/datasets/mlab-real/cifar10/environment/data/train.csv b/datasets/mlab-real/cifar10/environment/data/train.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7661abfc2a73554ef4d8adad007a2381506de469
--- /dev/null
+++ b/datasets/mlab-real/cifar10/environment/data/train.csv
@@ -0,0 +1,8001 @@
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diff --git a/datasets/mlab-real/cifar10/environment/prepare.py b/datasets/mlab-real/cifar10/environment/prepare.py
new file mode 100644
index 0000000000000000000000000000000000000000..96432772456910b308dae68a27937f9e0a783e1e
--- /dev/null
+++ b/datasets/mlab-real/cifar10/environment/prepare.py
@@ -0,0 +1,11 @@
+"""Stage REAL MLAB data (bundled by the mlab-real adapter) at build time."""
+import os, shutil
+from pathlib import Path
+WS=Path(os.environ.get("MLAB_WORKSPACE","/workspace")); ANS=Path(os.environ.get("MLAB_ANSWER_DIR","/opt/mlab"))
+SRC=Path("/opt/mlab/data"); WS.mkdir(parents=True,exist_ok=True); ANS.mkdir(parents=True,exist_ok=True)
+for f in ("train.csv","test.csv"):
+    shutil.copy(SRC/f, WS/f)
+for f in ("train_images.npy","test_images.npy","node_features.npy","edges.npy"):
+    if (SRC/f).exists(): shutil.copy(SRC/f, WS/f)
+shutil.copy(SRC/"answer.csv", ANS/"answer.csv")
+print("[prepare] REAL mlab cifar10 (image 10-class, real split): staged", os.listdir(WS))
diff --git a/datasets/mlab-real/cifar10/instruction.md b/datasets/mlab-real/cifar10/instruction.md
new file mode 100644
index 0000000000000000000000000000000000000000..4a97b0073e88678b1c1d293222731d6fe9257b89
--- /dev/null
+++ b/datasets/mlab-real/cifar10/instruction.md
@@ -0,0 +1,30 @@
+# CIFAR-10 (small) — image classification
+
+Dataset Description
+The CIFAR-10 dataset: 32x32 colour images in 10 mutually exclusive classes
+(airplane, automobile, bird, cat, deer, dog, frog, horse, ship, truck).
+
+File and Data Field Descriptions
+train_images.npy / test_images.npy - uint8 arrays of shape (N, 32, 32, 3).
+train.csv - labels for the training images.
+  id    - row index into train_images.npy.
+  label - class index 0-9 (the column to predict).
+test.csv  - ids for the test images (predict `label`).
+sample_submission.csv - a submission file in the correct format.
+
+## Data (already staged in `/workspace`)
+- `train_images.npy` — uint8 array, shape `(N, 32, 32, 3)`, row-aligned with `train.csv`.
+- `train.csv` — `id`, target **`label`** (0–9).
+- `test_images.npy` — uint8 array, row-aligned with `test.csv`.
+- `test.csv` — `id` only.
+
+## Approach
+Choose your own approach, libraries and tools. Explore the data, train a real model (not a constant/trivial baseline), validate sensibly, and write the submission below.
+
+## Submission — REQUIRED
+Write predictions to **`/workspace/submission.csv`** with EXACTLY two columns:
+- `id` — from `test.csv`
+- `label` — predicted class (0–9)
+
+Scoring: **accuracy** against the held-out labels (higher is better). Validate on
+a held-out split of the training images first.
diff --git a/datasets/mlab-real/cifar10/solution/solve.sh b/datasets/mlab-real/cifar10/solution/solve.sh
new file mode 100644
index 0000000000000000000000000000000000000000..035d6779f6bad578641403d564bf1772aafd5761
--- /dev/null
+++ b/datasets/mlab-real/cifar10/solution/solve.sh
@@ -0,0 +1,37 @@
+#!/bin/bash
+# Oracle: torchvision.models CNN (resnet18 adapted to 32x32) — the specialized
+# library this task names.
+set -euo pipefail
+/opt/venvs/vision/bin/python - <<'PY'
+import numpy as np, pandas as pd, torch, torch.nn as nn
+from torchvision import models
+
+torch.manual_seed(0)
+tr = pd.read_csv("/workspace/train.csv"); te = pd.read_csv("/workspace/test.csv")
+Xtr = np.load("/workspace/train_images.npy").astype("float32") / 255.0
+Xte = np.load("/workspace/test_images.npy").astype("float32") / 255.0
+mean, std = Xtr.mean((0, 1, 2)), Xtr.std((0, 1, 2)) + 1e-6
+t = lambda X: torch.from_numpy(((X - mean) / std).transpose(0, 3, 1, 2).copy())
+Xtr_t, Xte_t, ytr = t(Xtr), t(Xte), torch.tensor(tr["label"].values)
+
+model = models.resnet18(weights=None, num_classes=5)
+model.conv1 = nn.Conv2d(3, 64, 3, 1, 1, bias=False)   # 32x32-friendly stem
+model.maxpool = nn.Identity()
+opt = torch.optim.Adam(model.parameters(), lr=1e-3)
+lossf = nn.CrossEntropyLoss()
+model.train()
+for epoch in range(5):
+    perm = torch.randperm(len(Xtr_t))
+    for i in range(0, len(perm), 128):
+        idx = perm[i:i + 128]
+        opt.zero_grad(); loss = lossf(model(Xtr_t[idx]), ytr[idx])
+        loss.backward(); opt.step()
+    print(f"[oracle] epoch {epoch} loss {loss.item():.3f}")
+model.eval()
+with torch.no_grad():
+    pred = torch.cat([model(Xte_t[i:i + 256]).argmax(1)
+                      for i in range(0, len(Xte_t), 256)])
+pd.DataFrame({"id": te["id"], "label": pred.numpy()}).to_csv(
+    "/workspace/submission.csv", index=False)
+print("[oracle] torchvision resnet18 wrote submission.csv")
+PY
diff --git a/datasets/mlab-real/cifar10/task.toml b/datasets/mlab-real/cifar10/task.toml
new file mode 100644
index 0000000000000000000000000000000000000000..f94acd8e4fa645f9746a667009cef89f3ecbc969
--- /dev/null
+++ b/datasets/mlab-real/cifar10/task.toml
@@ -0,0 +1,25 @@
+schema_version = "1.3"
+artifacts = ["/workspace/submission.csv"]
+[task]
+name = "autods-mlab/cifar10"
+description = "MLAgentBench CIFAR-10 (small) — image classification (timm / torchvision)"
+keywords = ["mlab", "mlagentbench", "image", "vision", "timm", "torchvision", "autods"]
+[[task.authors]]
+name = "AutoDS"
+[metadata]
+family = "vision"
+metric = "accuracy"
+specialized_libraries = ["timm", "torchvision", "albumentations"]
+[verifier]
+timeout_sec = 1200.0
+collect = []
+[verifier.env]
+[agent]
+timeout_sec = 3600.0
+[environment]
+network_mode = "public"
+build_timeout_sec = 1800.0
+os = "linux"
+mcp_servers = []
+[environment.env]
+[solution.env]
diff --git a/datasets/mlab-real/cifar10/tests/score.py b/datasets/mlab-real/cifar10/tests/score.py
new file mode 100644
index 0000000000000000000000000000000000000000..1ea732ce81c1bffb03c618d18f04d3dc06819f3f
--- /dev/null
+++ b/datasets/mlab-real/cifar10/tests/score.py
@@ -0,0 +1,24 @@
+"""Score CIFAR-10 (accuracy). Always writes a reward (0.0 on failure)."""
+from __future__ import annotations
+import argparse, json
+from pathlib import Path
+import pandas as pd
+ID, TARGET = "id", "label"
+def main() -> int:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--submission", required=True); ap.add_argument("--answer", required=True); ap.add_argument("--reward-json", required=True)
+    a = ap.parse_args(); rp = Path(a.reward_json); rp.parent.mkdir(parents=True, exist_ok=True)
+    def emit(r, **x):
+        rp.write_text(json.dumps({"reward": float(r), **x})); print(json.dumps({"reward": float(r), **x})); return 0
+    try:
+        ans = pd.read_csv(a.answer); sub = pd.read_csv(a.submission)
+    except Exception as e:  # noqa: BLE001
+        return emit(0.0, error=f"read failed: {e}")
+    if ID not in sub.columns or TARGET not in sub.columns:
+        return emit(0.0, error="submission needs columns [id, label]")
+    m = ans.merge(sub, on=ID, suffixes=("_true","_pred"))
+    if m.empty: return emit(0.0, error="no id overlap")
+    acc = float((pd.to_numeric(m["label_true"],errors="coerce")==pd.to_numeric(m["label_pred"],errors="coerce")).mean())
+    return emit(acc, accuracy=acc, n=int(len(m)))
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/datasets/mlab-real/cifar10/tests/test.sh b/datasets/mlab-real/cifar10/tests/test.sh
new file mode 100644
index 0000000000000000000000000000000000000000..df8eb169d51c7efe90034ceabadcaf8134b85d38
--- /dev/null
+++ b/datasets/mlab-real/cifar10/tests/test.sh
@@ -0,0 +1,6 @@
+#!/bin/bash
+set -uo pipefail
+mkdir -p /logs/verifier
+PY=/opt/venvs/vision/bin/python; [ -x "$PY" ] || PY=python
+"$PY" /tests/score.py --submission /workspace/submission.csv --answer /opt/mlab/answer.csv --reward-json /logs/verifier/reward.json
+exit 0
diff --git a/datasets/mlab-real/fathomnet/environment/data/images/02394855-3ecf-4096-9f69-9a3a7a88e55d.jpg b/datasets/mlab-real/fathomnet/environment/data/images/02394855-3ecf-4096-9f69-9a3a7a88e55d.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..273f9df8c155137645d53a5b99e59ae0484ab4fa
--- /dev/null
+++ b/datasets/mlab-real/fathomnet/environment/data/images/02394855-3ecf-4096-9f69-9a3a7a88e55d.jpg
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f4bf53cd8ba6f309bdea12e3b7bb15a3a9c62a9316fdb0cba79c9633db14b54b
+size 2979859
diff --git a/datasets/mlab-real/fathomnet/environment/data/images/0442ba67-4bb4-42de-b345-2ff7d42b14f0.jpg b/datasets/mlab-real/fathomnet/environment/data/images/0442ba67-4bb4-42de-b345-2ff7d42b14f0.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..9d2444899c40d3adefce959caf9fe0e0ef5571f6
--- /dev/null
+++ b/datasets/mlab-real/fathomnet/environment/data/images/0442ba67-4bb4-42de-b345-2ff7d42b14f0.jpg
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ab9bd515c289c0f4a59c85e6100d759f720ea5fe29a11e57d5b58ff7b92238a8
+size 2413437
diff --git a/datasets/mlab-real/fathomnet/environment/data/images/0463d802-5e43-45cb-8114-e5b9301ed7bd.jpg b/datasets/mlab-real/fathomnet/environment/data/images/0463d802-5e43-45cb-8114-e5b9301ed7bd.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..ba9b8cee0ee91ca045628d783be660e5675ec1f4
--- /dev/null
+++ b/datasets/mlab-real/fathomnet/environment/data/images/0463d802-5e43-45cb-8114-e5b9301ed7bd.jpg
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4f0e3f92fead11e359cf5f9ec739482fb9dc42788d0d885389992a1f56818f1f
+size 384988
diff --git a/datasets/mlab-real/fathomnet/environment/data/images/0495d30b-490c-479b-8387-4554e21bb763.jpg b/datasets/mlab-real/fathomnet/environment/data/images/0495d30b-490c-479b-8387-4554e21bb763.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..979bb74232d815cf0ef495ef01c61ed20363bcf8
--- /dev/null
+++ b/datasets/mlab-real/fathomnet/environment/data/images/0495d30b-490c-479b-8387-4554e21bb763.jpg
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