diff --git a/comfy_extras/nodes_mahiro.py b/comfy_extras/nodes_mahiro.py
new file mode 100644
index 00000000..8fcdfba7
--- /dev/null
+++ b/comfy_extras/nodes_mahiro.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn.functional as F
+
+class Mahiro:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {"model": ("MODEL",),
+                            }}
+    RETURN_TYPES = ("MODEL",)
+    RETURN_NAMES = ("patched_model",)
+    FUNCTION = "patch"
+    CATEGORY = "_for_testing"
+    DESCRIPTION = "Modify the guidance to scale more on the 'direction' of the positive prompt rather than the difference between the negative prompt."
+    def patch(self, model):
+        m = model.clone()
+        def mahiro_normd(args):
+            scale: float = args['cond_scale']
+            cond_p: torch.Tensor = args['cond_denoised']
+            uncond_p: torch.Tensor = args['uncond_denoised']
+            #naive leap
+            leap = cond_p * scale
+            #sim with uncond leap
+            u_leap = uncond_p * scale
+            cfg = args["denoised"]
+            merge = (leap + cfg) / 2
+            normu = torch.sqrt(u_leap.abs()) * u_leap.sign()
+            normm = torch.sqrt(merge.abs()) * merge.sign()
+            sim = F.cosine_similarity(normu, normm).mean()
+            simsc = 2 * (sim+1)
+            wm = (simsc*cfg + (4-simsc)*leap) / 4
+            return wm
+        m.set_model_sampler_post_cfg_function(mahiro_normd)
+        return (m, )
+
+NODE_CLASS_MAPPINGS = {
+    "Mahiro": Mahiro
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "Mahiro": "Mahiro is so cute that she deserves a better guidance function!! (。・ω・。)",
+}
diff --git a/nodes.py b/nodes.py
index b6e2465f..df412454 100644
--- a/nodes.py
+++ b/nodes.py
@@ -2147,6 +2147,7 @@ def init_builtin_extra_nodes():
         "nodes_torch_compile.py",
         "nodes_mochi.py",
         "nodes_slg.py",
+        "nodes_mahiro.py",
         "nodes_lt.py",
         "nodes_hooks.py",
     ]