How do I install the Comfy Nodes skill?

Run npx skillmds@latest add tomevault-io/comfy-nodes-2 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Comfy Nodes safe to use?

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Which AI agents work with Comfy Nodes?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Comfy Nodes free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Comfy Nodes?

tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Comfy Nodes by tomevault-io — Agent Skill

Name: Comfy Nodes
Author: tomevault-io

File contents

ComfyUI Custom Node Development

This skill helps you create custom ComfyUI nodes from Python code.

Quick Template

class MyNode:
    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "image": ("IMAGE",),
                "value": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0}),
            },
            "optional": {
                "mask": ("MASK",),
            }
        }

    RETURN_TYPES = ("IMAGE",)
    RETURN_NAMES = ("output",)
    FUNCTION = "execute"
    CATEGORY = "Custom/MyNodes"

    def execute(self, image, value, mask=None):
        result = image * value
        return (result,)

NODE_CLASS_MAPPINGS = {"MyNode": MyNode}
NODE_DISPLAY_NAME_MAPPINGS = {"MyNode": "My Node"}

Converting Python to Node

When you have Python code to wrap:

Step 1: Identify inputs and outputs

# Original function
def apply_blur(image, radius=5):
    from PIL import ImageFilter
    return image.filter(ImageFilter.GaussianBlur(radius))

Step 2: Map types

Python Type	ComfyUI Type	Conversion
PIL Image	IMAGE	`torch.from_numpy(np.array(pil) / 255.0)`
numpy array	IMAGE	`torch.from_numpy(arr.astype(np.float32))`
cv2 BGR	IMAGE	`torch.from_numpy(cv2.cvtColor(img, cv2.COLOR_BGR2RGB) / 255.0)`
float 0-255	IMAGE	Divide by 255.0
Single image	Batch	`tensor.unsqueeze(0)`

Step 3: Handle batch dimension

ComfyUI images are [B,H,W,C] - always process all batch items:

def execute(self, image, radius):
    batch_results = []
    for i in range(image.shape[0]):
        # Convert to PIL
        img_np = (image[i].cpu().numpy() * 255).astype(np.uint8)
        pil_img = Image.fromarray(img_np)

        # Your processing
        result = pil_img.filter(ImageFilter.GaussianBlur(radius))

        # Convert back
        result_np = np.array(result).astype(np.float32) / 255.0
        batch_results.append(torch.from_numpy(result_np))

    return (torch.stack(batch_results),)

Common Input Types

Type	Shape/Format	Widget Options
IMAGE	[B,H,W,C] float 0-1	-
MASK	[H,W] or [B,H,W] float 0-1	-
LATENT	{"samples": [B,C,H,W]}	-
MODEL	ModelPatcher	-
CLIP	CLIP encoder	-
VAE	VAE model	-
CONDITIONING	[(cond, pooled), ...]	-
INT	integer	default, min, max, step
FLOAT	float	default, min, max, step, display
STRING	str	default, multiline
BOOLEAN	bool	default
COMBO	str	List of options as type

Checklist

INPUT_TYPES is a @classmethod
Return value is a tuple: return (result,)
Handle batch dimension [B,H,W,C]
Add to NODE_CLASS_MAPPINGS
Category uses / for submenus

References

NODE_TEMPLATE.md - Full template with V3 schema
OFFICIAL_DOCS.md - Official ComfyUI documentation
PURZ_EXAMPLES.md - Example nodes and workflows

Finding Similar Nodes

Use the MCP tools to find existing nodes for reference:

comfy_search("blur")        → Find blur implementations
comfy_spec("GaussianBlur")  → See how inputs are defined

Source: ConstantineB6/Comfy-Pilot — distributed by TomeVault.

---name: comfy-nodes-2description: Use when the user wants to create a ComfyUI custom node, convert Python code to a node, make a node from a script, or needs help with ComfyUI node development, INPUT_TYPES, RETURN_TYPES, or node class structure.---# ComfyUI Custom Node DevelopmentThis skill helps you create custom ComfyUI nodes from Python code.## Quick Template```pythonclass MyNode: @classmethod def INPUT_TYPES(cls): return { "required": { "image": ("IMAGE",), "value": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0}), }, "optional": { "mask": ("MASK",), } } RETURN_TYPES = ("IMAGE",) RETURN_NAMES = ("output",) FUNCTION = "execute" CATEGORY = "Custom/MyNodes" def execute(self, image, value, mask=None): result = image * value return (result,)NODE_CLASS_MAPPINGS = {"MyNode": MyNode}NODE_DISPLAY_NAME_MAPPINGS = {"MyNode": "My Node"}```## Converting Python to NodeWhen you have Python code to wrap:### Step 1: Identify inputs and outputs```python# Original functiondef apply_blur(image, radius=5): from PIL import ImageFilter return image.filter(ImageFilter.GaussianBlur(radius))```### Step 2: Map types| Python Type | ComfyUI Type | Conversion ||-------------|--------------|------------|| PIL Image | IMAGE | `torch.from_numpy(np.array(pil) / 255.0)` || numpy array | IMAGE | `torch.from_numpy(arr.astype(np.float32))` || cv2 BGR | IMAGE | `torch.from_numpy(cv2.cvtColor(img, cv2.COLOR_BGR2RGB) / 255.0)` || float 0-255 | IMAGE | Divide by 255.0 || Single image | Batch | `tensor.unsqueeze(0)` |### Step 3: Handle batch dimensionComfyUI images are `[B,H,W,C]` - always process all batch items:```pythondef execute(self, image, radius): batch_results = [] for i in range(image.shape[0]): # Convert to PIL img_np = (image[i].cpu().numpy() * 255).astype(np.uint8) pil_img = Image.fromarray(img_np) # Your processing result = pil_img.filter(ImageFilter.GaussianBlur(radius)) # Convert back result_np = np.array(result).astype(np.float32) / 255.0 batch_results.append(torch.from_numpy(result_np)) return (torch.stack(batch_results),)```## Common Input Types| Type | Shape/Format | Widget Options ||------|--------------|----------------|| IMAGE | [B,H,W,C] float 0-1 | - || MASK | [H,W] or [B,H,W] float 0-1 | - || LATENT | {"samples": [B,C,H,W]} | - || MODEL | ModelPatcher | - || CLIP | CLIP encoder | - || VAE | VAE model | - || CONDITIONING | [(cond, pooled), ...] | - || INT | integer | default, min, max, step || FLOAT | float | default, min, max, step, display || STRING | str | default, multiline || BOOLEAN | bool | default || COMBO | str | List of options as type |## Checklist- [ ] `INPUT_TYPES` is a `@classmethod`- [ ] Return value is a tuple: `return (result,)`- [ ] Handle batch dimension `[B,H,W,C]`- [ ] Add to `NODE_CLASS_MAPPINGS`- [ ] Category uses `/` for submenus## References- [NODE_TEMPLATE.md](references/NODE_TEMPLATE.md) - Full template with V3 schema- [OFFICIAL_DOCS.md](references/OFFICIAL_DOCS.md) - Official ComfyUI documentation- [PURZ_EXAMPLES.md](references/PURZ_EXAMPLES.md) - Example nodes and workflows## Finding Similar NodesUse the MCP tools to find existing nodes for reference:```comfy_search("blur") → Find blur implementationscomfy_spec("GaussianBlur") → See how inputs are defined```---> Source: [ConstantineB6/Comfy-Pilot](https://github.com/ConstantineB6/Comfy-Pilot) — distributed by [TomeVault](https://tomevault.io).

Frequently asked questions

Comfy Nodes