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 ideogram-ultragit 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/ideogram-ultra)<a href="https://agentmods.dev/skills/artokun/comfyui-mcp/ideogram-ultra"><img src="https://agentmods.dev/badge/skills/artokun/comfyui-mcp/ideogram-ultra/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/ideogram-ultra"><img src="https://agentmods.dev/badge/skills/artokun/comfyui-mcp/ideogram-ultra.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 | $0.00068 | $0.06135 |
| Opus 5.5 | $0.00027 | $0.02454 |
| Sonnet 5.5 | $0.00014 | $0.01227 |
| Haiku 4.5 | $0.00007 | $0.00613 |
Grade A, and why
ideogram-ultra 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:
- ideogram-ultra — 91% identical, 66 lines differ
How it starts
The opening of the file, as written. The whole thing — 359 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ideogram 4 (Ideogram Ultra) Workflows
Overview
This is a LOCAL open-weights pipeline, NOT the hosted Ideogram API. There is no API key, no IdeogramGenerate API node, and no network call at generation time. Comfy-Org released the Ideogram 4 weights on Hugging Face and they run entirely on your GPU via standard UNETLoader / CLIPLoader / VAELoader nodes. (Note: ComfyUI also ships separate API/"partner" nodes that call the paid hosted Ideogram service. That is a different thing and is not what this workflow uses.)
Ideogram 4 is best known for text rendering / typography, poster and graphic-design layouts, and prompt adherence. The hallmark of this workflow is a structured JSON prompt (a "compositional deconstruction" caption with bounding boxes) instead of a plain text prompt. This is what gives precise control over where text and objects land in the frame.
Source workflow this skill is derived from: IDEOGRAM_ULTRA_WORKFLOW-V2.json (UI format, 66 nodes, 4 subgraphs), by Aitrepreneur. It provides both a TEXT TO IMAGE path and an IMAGE TO IMAGE path.
Two unusual things to know up front
- Dual models. Two UNETs are loaded: a conditional model (
ideogram4_fp8_scaled) and an..._unconditional_fp8_scaledmodel. ADualModelGuidernode uses both to perform asymmetric classifier-free guidance; the unconditional model provides the CFG baseline. There is no negative text prompt; negative conditioning isConditioningZeroOut. - Two text models, different jobs.
qwen3vl_8b_fp8_scaledis the actual diffusion text encoder (loaded withCLIPLoader, typeideogram4).gemma4_e4b_it_fp8_scaledis used only inside an optional prompt-builder subgraph (aTextGeneratenode) that auto-writes the structured JSON from a plain idea. It is not the diffusion encoder.
Installation
Custom nodes
The workflow needs these four custom node packs (clone into ComfyUI/custom_nodes/). Exact repos from the installer scripts:
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 · 359 lines · 68 tokens per session scan A f98342c119a4
ideogram-ultra is a skill published in the GitHub repository artokun/comfyui-mcp (863 stars, last pushed yesterday), licensed MIT. It adds 68 tokens to every session and 6,135 once invoked, about $0.0003 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.
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