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Core ComfyUI knowledge — workflow format, node types, pipeline patterns, and MCP tool usage
Passed 17 of 20 test cases with the skill, and 12 of 20 without it.
and 3 more in the full report
6 fixed13 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
I enqueued a batch of 5 image generation jobs in ComfyUI. Should I poll status in a loop using queue status API calls, or run a background monitor script?
| Checked | Without skill | With skill |
|---|---|---|
| Recommends running a background monitoring script rather than polling queue status in a loop. | Missed | Passed |
The instructions your model reads when the skill loads.
ComfyUI workflows are JSON objects mapping string node IDs to node definitions:
{
"1": {
"class_type": "CheckpointLoaderSimple",
"inputs": { "ckpt_name": "sd_xl_base_1.0.safetensors" },
"_meta": { "title": "Load Checkpoint" }
},
"2": {
"class_type": "CLIPTextEncode",
"inputs": { "text": "a cat", "clip": ["1", 1] },
"_meta": { "title": "Positive Prompt" }
}
}
"1", "2", etc.)class_type is the exact Python class name of the nodeinputs contains both widget values (scalars) and connections (arrays)["sourceNodeId", outputIndex], a 2-element array where:
output list (0-based)_meta is optional and used for display titles only"model": ["1", 0] // Connect to node 1's first output (MODEL)
"clip": ["1", 1] // Connect to node 1's second output (CLIP)
"vae": ["1", 2] // Connect to node 1's third output (VAE)
"positive": ["2", 0] // Connect to node 2's first output (CONDITIONING)
"samples": ["5", 0] // Connect to node 5's first output (LATENT)
"images": ["6", 0] // Connect to node 6's first output (IMAGE)
test cases passed, vs 12 / 20 without
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