nano-banana-pro: respect explicit --resolution when editing images (#36880)

* nano-banana-pro: respect explicit --resolution when editing images

* Changelog: note nano banana resolution fix

* Update CHANGELOG.md

---------

Co-authored-by: Vincent Koc <vincentkoc@ieee.org>

CHANGELOG.md

@@ -196,6 +196,7 @@ Docs: https://docs.openclaw.ai
 - Agents/gateway config guidance: stop exposing `config.schema` through the agent `gateway` tool, remove prompt/docs guidance that told agents to call it, and keep agents on `config.get` plus `config.patch`/`config.apply` for config changes. (#7382) thanks @kakuteki.
 - Agents/failover: classify periodic provider limit exhaustion text (for example `Weekly/Monthly Limit Exhausted`) as `rate_limit` while keeping explicit `402 Payment Required` variants in billing, so failover continues without misclassifying billing-wrapped quota errors. (#33813) thanks @zhouhe-xydt.
 - Mattermost/interactive button callbacks: allow external callback base URLs and stop requiring loopback-origin requests so button clicks work when Mattermost reaches the gateway over Tailscale, LAN, or a reverse proxy. (#37543) thanks @mukhtharcm.
+- Skills/nano-banana-pro resolution override: respect explicit `--resolution` values during image editing and only auto-detect output size from input images when the flag is omitted. (#36880) Thanks @shuofengzhang and @vincentkoc.
 
 ## 2026.3.2
 

skills/nano-banana-pro/scripts/generate_image.py

@@ -42,6 +42,33 @@ def get_api_key(provided_key: str | None) -> str | None:
     return os.environ.get("GEMINI_API_KEY")
 
 
+def auto_detect_resolution(max_input_dim: int) -> str:
+    """Infer output resolution from the largest input image dimension."""
+    if max_input_dim >= 3000:
+        return "4K"
+    if max_input_dim >= 1500:
+        return "2K"
+    return "1K"
+
+
+def choose_output_resolution(
+    requested_resolution: str | None,
+    max_input_dim: int,
+    has_input_images: bool,
+) -> tuple[str, bool]:
+    """Choose final resolution and whether it was auto-detected.
+
+    Auto-detection is only applied when the user did not pass --resolution.
+    """
+    if requested_resolution is not None:
+        return requested_resolution, False
+
+    if has_input_images and max_input_dim > 0:
+        return auto_detect_resolution(max_input_dim), True
+
+    return "1K", False
+
+
 def main():
     parser = argparse.ArgumentParser(
         description="Generate images using Nano Banana Pro (Gemini 3 Pro Image)"
@@ -66,8 +93,8 @@ def main():
     parser.add_argument(
         "--resolution", "-r",
         choices=["1K", "2K", "4K"],
-        default="1K",
-        help="Output resolution: 1K (default), 2K, or 4K"
+        default=None,
+        help="Output resolution: 1K, 2K, or 4K. If omitted with input images, auto-detect from largest image dimension."
     )
     parser.add_argument(
         "--aspect-ratio", "-a",
@@ -105,13 +132,12 @@ def main():
 
     # Load input images if provided (up to 14 supported by Nano Banana Pro)
     input_images = []
-    output_resolution = args.resolution
+    max_input_dim = 0
     if args.input_images:
         if len(args.input_images) > 14:
             print(f"Error: Too many input images ({len(args.input_images)}). Maximum is 14.", file=sys.stderr)
             sys.exit(1)
 
-        max_input_dim = 0
         for img_path in args.input_images:
             try:
                 with PILImage.open(img_path) as img:
@@ -126,15 +152,16 @@ def main():
                 print(f"Error loading input image '{img_path}': {e}", file=sys.stderr)
                 sys.exit(1)
 
-        # Auto-detect resolution from largest input if not explicitly set
-        if args.resolution == "1K" and max_input_dim > 0:  # Default value
-            if max_input_dim >= 3000:
-                output_resolution = "4K"
-            elif max_input_dim >= 1500:
-                output_resolution = "2K"
-            else:
-                output_resolution = "1K"
-            print(f"Auto-detected resolution: {output_resolution} (from max input dimension {max_input_dim})")
+    output_resolution, auto_detected = choose_output_resolution(
+        requested_resolution=args.resolution,
+        max_input_dim=max_input_dim,
+        has_input_images=bool(input_images),
+    )
+    if auto_detected:
+        print(
+            f"Auto-detected resolution: {output_resolution} "
+            f"(from max input dimension {max_input_dim})"
+        )
 
     # Build contents (images first if editing, prompt only if generating)
     if input_images:

skills/nano-banana-pro/scripts/test_generate_image.py

@@ -0,0 +1,36 @@
+import importlib.util
+from pathlib import Path
+
+import pytest
+
+MODULE_PATH = Path(__file__).with_name("generate_image.py")
+SPEC = importlib.util.spec_from_file_location("generate_image", MODULE_PATH)
+assert SPEC and SPEC.loader
+MODULE = importlib.util.module_from_spec(SPEC)
+SPEC.loader.exec_module(MODULE)
+
+
+@pytest.mark.parametrize(
+    ("max_input_dim", "expected"),
+    [
+        (0, "1K"),
+        (1499, "1K"),
+        (1500, "2K"),
+        (2999, "2K"),
+        (3000, "4K"),
+    ],
+)
+def test_auto_detect_resolution_thresholds(max_input_dim, expected):
+    assert MODULE.auto_detect_resolution(max_input_dim) == expected
+
+
+def test_choose_output_resolution_auto_detects_when_resolution_omitted():
+    assert MODULE.choose_output_resolution(None, 2200, True) == ("2K", True)
+
+
+def test_choose_output_resolution_defaults_to_1k_without_inputs():
+    assert MODULE.choose_output_resolution(None, 0, False) == ("1K", False)
+
+
+def test_choose_output_resolution_respects_explicit_1k_with_large_input():
+    assert MODULE.choose_output_resolution("1K", 3500, True) == ("1K", False)