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 jgkme/img-gen-mcp --skill image-modelsgit clone --depth 1 https://github.com/jgkme/img-gen-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/jgkme/img-gen-mcp/image-models)<a href="https://agentmods.dev/skills/jgkme/img-gen-mcp/image-models"><img src="https://agentmods.dev/badge/skills/jgkme/img-gen-mcp/image-models/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/jgkme/img-gen-mcp/image-models"><img src="https://agentmods.dev/badge/skills/jgkme/img-gen-mcp/image-models.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00032 | $0.00868 |
| Opus 5 | $0.00016 | $0.00434 |
| Sonnet 5 | $0.00006 | $0.00174 |
| Haiku 4.5 | $0.00003 | $0.00087 |
Grade A, and why
image-models 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Models And Backends
Use this skill when selecting or validating image generation models, local provider backends, and background-removal backends for img-gen-mcp.
Supported OpenRouter image models
Prefer these slugs when prompting OpenRouter image generation:
microsoft/mai-image-2.5openai/gpt-image-1openai/gpt-5-image-miniopenai/gpt-5.4-image-2google/gemini-2.5-flash-imagegoogle/gemini-2.5-flash-image-previewgoogle/gemini-3-pro-image-previewx-ai/grok-imagine-image-qualitybytedance-seed/seedream-4.5sourceful/riverflow-v2.5-fast:freesourceful/riverflow-v2.5-fastsourceful/riverflow-v2.5-prosourceful/riverflow-v2-fastsourceful/riverflow-v2-prorecraft/recraft-v4.1-utilityrecraft/recraft-v4.1-vectorrecraft/recraft-v4.1-utility-prorecraft/recraft-v4.1-pro-vectorrecraft/recraft-v3black-forest-labs/flux.2-problack-forest-labs/flux.2-flex
Model notes
microsoft/mai-image-2.5is a strong default for polished photorealistic output.x-ai/grok-imagine-image-qualityis image-only and is good for realistic, prompt-faithful results.openai/gpt-5-image-miniis useful when lower latency is preferred.sourceful/riverflow-*models are often useful for stylized or prompt-following generation.recraft/*models are useful for logo/vector-style work.provider=autocan infer the backend from the model slug for common OpenAI, Gemini, OpenRouter, and local wrapper families.
Discovery tools
- Use
list_image_modelsto inspect provider families, defaults, and output directories. - Use
get_provider_statusto check which providers are configured, the active defaults, and local bootstrap hints. - Use
get_model_capabilitiesto see which providers can generate, edit, batch, or use local endpoints.
Workflow helpers
- Use
submit_taskandget_taskwhen a client prefers polling instead of waiting synchronously. - Use
batch_generate_imagewhen you want multiple variants from a single 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.
- 10d ago First seen · 82 lines · 32 tokens per session scan A b4758d76aa2a
image-models is a skill published in the GitHub repository jgkme/img-gen-mcp (2 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 868 once invoked, about $0.0002 per session on Opus 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 2026-08-31.
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