jtydhr88/comfyui-custom-node-skills101 installs
comfyui-node-migration
ComfyUI V1 to V3 node migration - converting legacy nodes to the V3 API. Use when migrating existing custom nodes from V1 to V3, understanding differences between API versions, or modernizing node code.
How do I install this agent skill?
npx skills add https://github.com/jtydhr88/comfyui-custom-node-skills --skill comfyui-node-migrationIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill provides a migration guide and code examples for converting ComfyUI custom nodes from V1 to V3. No security issues were detected.
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No alerts
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Risk: LOW · No issues
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1 file scanned · No issues
What does this agent skill do?
ComfyUI V1 → V3 Migration Guide
Migrate existing V1 nodes to the modern V3 API. V3 uses classmethods, typed inputs/outputs, and ComfyExtension registration.
Migration Checklist
- Change base class to
io.ComfyNode - Replace
INPUT_TYPES()withdefine_schema()returningio.Schema - Rename execution function to
executeand make it a@classmethod - Replace return tuples with
io.NodeOutput(...) - Replace
IS_CHANGEDwithfingerprint_inputs - Replace
VALIDATE_INPUTSwithvalidate_inputs - Convert
check_lazy_statusto@classmethod - Replace
NODE_CLASS_MAPPINGSwithComfyExtension+comfy_entrypoint() - Access hidden inputs via
cls.hiddeninstead of kwargs - Remove
__init__methods (no instance state in V3)
Side-by-Side Comparison
V1 (Before)
import torch
class ImageInvertV1:
CATEGORY = "image"
FUNCTION = "invert"
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("image",)
OUTPUT_TOOLTIPS = ("The inverted image",)
DESCRIPTION = "Inverts image colors"
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"image": ("IMAGE",),
"strength": ("FLOAT", {
"default": 1.0,
"min": 0.0,
"max": 1.0,
"step": 0.01,
}),
},
"optional": {
"mask": ("MASK",),
},
"hidden": {
"unique_id": "UNIQUE_ID",
},
}
@classmethod
def IS_CHANGED(s, image, strength, mask=None, unique_id=None):
return strength
@classmethod
def VALIDATE_INPUTS(s, image, strength, mask=None, unique_id=None):
if strength < 0:
return "Strength must be non-negative"
return True
def invert(self, image, strength, mask=None, unique_id=None):
inverted = 1.0 - image
result = image * (1 - strength) + inverted * strength
if mask is not None:
result = image * (1 - mask.unsqueeze(-1)) + result * mask.unsqueeze(-1)
return (result,)
NODE_CLASS_MAPPINGS = {"ImageInvertV1": ImageInvertV1}
NODE_DISPLAY_NAME_MAPPINGS = {"ImageInvertV1": "Invert Image"}
V3 (After)
import torch
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io
class ImageInvertV3(io.ComfyNode):
@classmethod
def define_schema(cls):
return io.Schema(
node_id="ImageInvertV3",
display_name="Invert Image",
description="Inverts image colors",
category="image",
inputs=[
io.Image.Input("image"),
io.Float.Input("strength", default=1.0, min=0.0, max=1.0, step=0.01),
io.Mask.Input("mask", optional=True),
],
outputs=[
io.Image.Output("IMAGE", tooltip="The inverted image"),
],
hidden=[io.Hidden.unique_id],
)
@classmethod
def fingerprint_inputs(cls, image, strength, mask=None):
return strength
@classmethod
def validate_inputs(cls, image, strength, mask=None):
if strength < 0:
return "Strength must be non-negative"
return True
@classmethod
def execute(cls, image, strength, mask=None):
node_id = cls.hidden.unique_id # access hidden via cls.hidden
inverted = 1.0 - image
result = image * (1 - strength) + inverted * strength
if mask is not None:
result = image * (1 - mask.unsqueeze(-1)) + result * mask.unsqueeze(-1)
return io.NodeOutput(result)
class MyExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [ImageInvertV3]
async def comfy_entrypoint() -> MyExtension:
return MyExtension()
Property Mapping
| V1 Property | V3 Equivalent |
|---|---|
CATEGORY = "image" | io.Schema(category="image") |
FUNCTION = "my_func" | Always execute (fixed name) |
RETURN_TYPES = ("IMAGE",) | outputs=[io.Image.Output()] |
RETURN_NAMES = ("image",) | outputs=[io.Image.Output(display_name="image")] |
OUTPUT_TOOLTIPS = ("tip",) | outputs=[io.Image.Output(tooltip="tip")] |
OUTPUT_NODE = True | io.Schema(is_output_node=True) |
DEPRECATED = True | io.Schema(is_deprecated=True) |
EXPERIMENTAL = True | io.Schema(is_experimental=True) |
API_NODE = True | io.Schema(is_api_node=True) |
NOT_IDEMPOTENT = True | io.Schema(not_idempotent=True) |
DESCRIPTION = "..." | io.Schema(description="...") |
SEARCH_ALIASES = [...] | io.Schema(search_aliases=[...]) |
INPUT_IS_LIST = True | io.Schema(is_input_list=True) |
OUTPUT_IS_LIST = (True,) | io.Image.Output(is_output_list=True) |
DEV_ONLY = True | io.Schema(is_dev_only=True) |
ESSENTIALS_CATEGORY = "Basic" | io.Schema(essentials_category="Basic") |
Input Type Mapping
| V1 Input | V3 Input |
|---|---|
("IMAGE",) | io.Image.Input("id") |
("MASK",) | io.Mask.Input("id") |
("LATENT",) | io.Latent.Input("id") |
("MODEL",) | io.Model.Input("id") |
("CLIP",) | io.Clip.Input("id") |
("VAE",) | io.Vae.Input("id") |
("CONDITIONING",) | io.Conditioning.Input("id") |
("INT", {"default": 0, ...}) | io.Int.Input("id", default=0, ...) |
("FLOAT", {"default": 1.0, ...}) | io.Float.Input("id", default=1.0, ...) |
("STRING", {"multiline": True}) | io.String.Input("id", multiline=True) |
("BOOLEAN", {"default": True}) | io.Boolean.Input("id", default=True) |
(["opt1", "opt2"],) | io.Combo.Input("id", options=["opt1", "opt2"]) |
("CONTROL_NET",) | io.ControlNet.Input("id") |
("CLIP_VISION",) | io.ClipVision.Input("id") |
("CLIP_VISION_OUTPUT",) | io.ClipVisionOutput.Input("id") |
("STYLE_MODEL",) | io.StyleModel.Input("id") |
("GLIGEN",) | io.Gligen.Input("id") |
("UPSCALE_MODEL",) | io.UpscaleModel.Input("id") |
("AUDIO",) | io.Audio.Input("id") |
("VIDEO",) | io.Video.Input("id") |
("SAMPLER",) | io.Sampler.Input("id") |
("SIGMAS",) | io.Sigmas.Input("id") |
("NOISE",) | io.Noise.Input("id") |
("GUIDER",) | io.Guider.Input("id") |
("HOOKS",) | io.Hooks.Input("id") |
("LORA_MODEL",) | io.LoraModel.Input("id") |
("MESH",) | io.Mesh.Input("id") |
("VOXEL",) | io.Voxel.Input("id") |
("FILE_3D",) | io.File3DAny.Input("id") |
("FILE_3D_GLB",) | io.File3DGLB.Input("id") |
("SVG",) | io.SVG.Input("id") |
("COLOR",) | io.Color.Input("id") |
("BOUNDING_BOX",) | io.BoundingBox.Input("id") |
("CURVE",) | io.Curve.Input("id") |
("LATENT_UPSCALE_MODEL",) | io.LatentUpscaleModel.Input("id") |
("MODEL_PATCH",) | io.ModelPatch.Input("id") |
("HOOK_KEYFRAMES",) | io.HookKeyframes.Input("id") |
("AUDIO_ENCODER",) | io.AudioEncoder.Input("id") |
("AUDIO_ENCODER_OUTPUT",) | io.AudioEncoderOutput.Input("id") |
("TRACKS",) | io.Tracks.Input("id") |
("LOSS_MAP",) | io.LossMap.Input("id") |
("TIMESTEPS_RANGE",) | io.TimestepsRange.Input("id") |
("LATENT_OPERATION",) | io.LatentOperation.Input("id") |
("WEBCAM",) | io.Webcam.Input("id") |
("PHOTOMAKER",) | io.Photomaker.Input("id") |
("WAN_CAMERA_EMBEDDING",) | io.WanCameraEmbedding.Input("id") |
("LOAD_3D",) | io.Load3D.Input("id") |
("LOAD_3D_ANIMATION",) | io.Load3DAnimation.Input("id") |
("LOAD3D_CAMERA",) | io.Load3DCamera.Input("id") |
("FILE_3D_GLTF",) | io.File3DGLTF.Input("id") |
("FILE_3D_FBX",) | io.File3DFBX.Input("id") |
("FILE_3D_OBJ",) | io.File3DOBJ.Input("id") |
("FILE_3D_STL",) | io.File3DSTL.Input("id") |
("FILE_3D_USDZ",) | io.File3DUSDZ.Input("id") |
("FILE_3D_PLY",) | io.File3DPLY.Input("id") |
("FILE_3D_SPLAT",) | io.File3DSPLAT.Input("id") |
("FILE_3D_SPZ",) | io.File3DSPZ.Input("id") |
("FILE_3D_KSPLAT",) | io.File3DKSPLAT.Input("id") |
("FILE_3D_SPLAT_ANY",) | io.File3DSplatAny.Input("id") |
("FILE_3D_POINT_CLOUD_ANY",) | io.File3DPointCloudAny.Input("id") |
("SPLAT",) | io.Splat.Input("id") |
("LOAD3D_MODEL_INFO",) | io.Load3DModelInfo.Input("id") |
("BACKGROUND_REMOVAL",) | io.BackgroundRemoval.Input("id") |
("DICT",) | io.Dict.Input("id") |
("ARRAY",) | io.Array.Input("id") |
("COLORS",) | io.Colors.Input("id") |
("BOUNDING_BOXES",) | io.BoundingBoxes.Input("id") |
("RANGE",) | io.Range.Input("id") |
("HISTOGRAM",) | io.Histogram.Input("id") |
("POINT",) | io.Point.Input("id") |
("FACE_ANALYSIS",) | io.FaceAnalysis.Input("id") |
("BBOX",) | io.BBOX.Input("id") |
("SEGS",) | io.SEGS.Input("id") |
("IMAGECOMPARE",) | io.ImageCompare.Input("id") |
("*",) | io.AnyType.Input("id") or io.MultiType.Input("id", types=[...]) |
Method Migration
Execute Method
# V1: instance method with custom name
class V1Node:
FUNCTION = "process"
def process(self, image, value):
return (result,)
# V3: classmethod named "execute", returns NodeOutput
class V3Node(io.ComfyNode):
@classmethod
def execute(cls, image, value):
return io.NodeOutput(result)
IS_CHANGED → fingerprint_inputs
# V1
@classmethod
def IS_CHANGED(s, **kwargs):
return float("NaN") # always re-execute
# V3
@classmethod
def fingerprint_inputs(cls, **kwargs):
import time
return time.time() # always re-execute
VALIDATE_INPUTS → validate_inputs
# V1
@classmethod
def VALIDATE_INPUTS(s, input_types=None, **kwargs):
return True
# V3
@classmethod
def validate_inputs(cls, input_types=None, **kwargs):
return True
check_lazy_status
# V1: instance method
def check_lazy_status(self, **kwargs):
return ["input_name"]
# V3: classmethod
@classmethod
def check_lazy_status(cls, **kwargs):
return ["input_name"]
Hidden Inputs
# V1: received as kwargs
def execute(self, image, unique_id=None, prompt=None):
node_id = unique_id
# V3: accessed via cls.hidden
@classmethod
def execute(cls, image):
node_id = cls.hidden.unique_id
prompt = cls.hidden.prompt
Registration Migration
# V1
NODE_CLASS_MAPPINGS = {
"Node1": Node1Class,
"Node2": Node2Class,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"Node1": "Node One",
"Node2": "Node Two",
}
WEB_DIRECTORY = "./js"
# V3
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io
class MyExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [Node1Class, Node2Class]
@override
async def on_load(self):
# Optional: initialization logic
pass
async def comfy_entrypoint() -> MyExtension:
return MyExtension()
# WEB_DIRECTORY still works the same way for JS extensions
WEB_DIRECTORY = "./js"
Output Node Migration
# V1
class V1SaveNode:
RETURN_TYPES = ()
OUTPUT_NODE = True
FUNCTION = "save"
def save(self, images, prefix):
# ... save logic ...
return {"ui": {"images": results}}
# V3
from comfy_api.latest import io, ui
class V3SaveNode(io.ComfyNode):
@classmethod
def define_schema(cls):
return io.Schema(
node_id="V3SaveNode",
display_name="Save",
category="image",
is_output_node=True,
inputs=[
io.Image.Input("images"),
io.String.Input("prefix", default="output"),
],
outputs=[],
hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo],
)
@classmethod
def execute(cls, images, prefix):
saved = ui.ImageSaveHelper.get_save_images_ui(images, prefix, cls=cls)
return io.NodeOutput(ui=saved)
Key Gotchas
- No instance state: V3 execute is a classmethod. Don't store state on
self. Use external storage if needed. - Fixed method name: Always
execute, never custom names. - Hidden access changed: Use
cls.hidden.promptnot function parameters. - Return type changed:
io.NodeOutput(val)not(val,). - Optional inputs: Use
=Nonedefault in execute params, not separate"optional"dict. - Async support: V3 execute can be
async def execute(cls, ...).
See Also
comfyui-node-basics- V3 node fundamentalscomfyui-node-packaging- Project structurecomfyui-node-lifecycle- Execution lifecycle differences
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/jtydhr88/comfyui-custom-node-skills/comfyui-node-migration">View comfyui-node-migration on skillZs</a>