Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add artokun/comfyui-mcp --skill model-compatibilitygit clone --depth 1 https://github.com/artokun/comfyui-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/artokun/comfyui-mcp/model-compatibility)<a href="https://agentmods.dev/skills/artokun/comfyui-mcp/model-compatibility"><img src="https://agentmods.dev/badge/skills/artokun/comfyui-mcp/model-compatibility/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/artokun/comfyui-mcp/model-compatibility"><img src="https://agentmods.dev/badge/skills/artokun/comfyui-mcp/model-compatibility.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.04926 |
| Opus 5.5 | $0.00019 | $0.01970 |
| Sonnet 5.5 | $0.00009 | $0.00985 |
| Haiku 4.5 | $0.00005 | $0.00493 |
Grade A, and why
model-compatibility scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- model-compatibility — 94% identical, 28 lines differ
How it starts
The opening of the file, as written. The whole thing — 441 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ComfyUI Model Compatibility Matrix
Stable Diffusion 1.5 (SD 1.5)
Overview
The original widely-adopted Stable Diffusion model. Huge ecosystem of fine-tunes, LoRAs, ControlNets, and embeddings. Still the most compatible and lightweight model family.
Configuration
| Parameter | Value |
|---|---|
| Loader | CheckpointLoaderSimple |
| Native Resolution | 512x512 |
| Supported Resolutions | 512x512, 512x768, 768x512, 768x768 (some fine-tunes) |
| VAE | Built-in or external (vae-ft-mse-840000-ema-pruned.safetensors) |
| CLIP | Single CLIP-L (output index 1 from checkpoint) |
| Text Encoder Node | CLIPTextEncode |
| CFG Range | 7-12 (typical: 7.5) |
| Negative Prompt | Yes — very important for quality |
| Steps | 20-30 (standard samplers) |
| Sampler | All standard samplers: euler, euler_ancestral, dpmpp_2m, dpmpp_sde, ddim |
| Scheduler | normal, karras |
| Denoise | 1.0 (txt2img), 0.5-0.8 (img2img) |
| VRAM (FP16) | ~2-3GB |
Workflow Pattern
CheckpointLoaderSimple → MODEL(0), CLIP(1), VAE(2)
CLIP(1) → CLIPTextEncode (positive) → CONDITIONING
CLIP(1) → CLIPTextEncode (negative) → CONDITIONING
EmptyLatentImage (width=512, height=512) → LATENT
KSampler (cfg=7.5, steps=20, sampler="euler", scheduler="normal") → LATENT
VAEDecode → IMAGE
SaveImage
VAE Notes
- Most SD 1.5 checkpoints have a built-in VAE, but it's often mediocre
- Recommended: Use external
vae-ft-mse-840000-ema-pruned.safetensorsfor better color accuracy - Load via
VAELoadernode and connect toVAEDecode - FP16 VAE can produce NaN on some images. FP32 VAE is more stable
ControlNet Compatibility
SD 1.5 has the largest ControlNet ecosystem:
| ControlNet | Model File Pattern | Notes |
|---|---|---|
| Canny | control_v11p_sd15_canny |
Edge detection |
| Depth | control_v11f1p_sd15_depth |
Depth map |
| OpenPose | control_v11p_sd15_openpose |
Skeleton/pose |
| Scribble | control_v11p_sd15_scribble |
Hand-drawn lines |
| Lineart | control_v11p_sd15_lineart |
Clean lines |
| Softedge | control_v11p_sd15_softedge |
Soft edges (HED) |
| Normal | control_v11p_sd15_normalbae |
Normal maps |
| Seg | control_v11p_sd15_seg |
Semantic segmentation |
| Tile | control_v11f1e_sd15_tile |
Tile/upscale guidance |
| Inpaint | control_v11p_sd15_inpaint |
Inpainting guidance |
| IP-Adapter | ip-adapter_sd15 |
Image prompt |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 441 lines · 47 tokens per session scan A 2b3785acb615
model-compatibility is a skill published in the GitHub repository artokun/comfyui-mcp (829 stars, last pushed 2d ago), licensed MIT. It adds 47 tokens to every session and 4,926 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
dev
One-command dev loop boot. Spins up portless (named HTTPS subdomain), emulate (stateful API mocks), the project's dev server, and an agent-browser session, all keyed to the current git branch. Use when starting a feature branch, switching worktrees, or returning to a project after a break. Skips silently with install…
storybook-mcp-integration
Reference for the Storybook MCP server itself (@storybook/addon-mcp): 6 tools across 3 toolsets (dev, docs, testing), availability detection, and per-agent toolset filtering. Use when setting up the server or calling these tools directly against components that already exist. For the end-to-end pipeline that turns a…
chief-strategy-officer
Owns where the business plays and how it wins over a multi-year horizon — portfolio choices, corporate development, strategic partnerships, and planning under uncertainty. Use this for a decision about which markets or businesses to be in, whether to build, buy, or partner, how to allocate capital across business…
chief-revenue-officer
Owns the revenue engine end to end: sales, monetization, pricing, customer success, retention, and partnerships. Use this for pricing and packaging decisions, sales strategy and coverage, forecast and pipeline health, churn and expansion, partner and channel strategy, or when marketing-sourced demand is not…
personal-guide-render
Instructions for understanding the status of a personal guide that the platform builds automatically from stored user data. The platform creates daily lessons and rebuilds the full guide weekly on its servers.
agent-fault
A command for recording a recurring mistake made by an AI agent in a shared fault-tracking system.