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 first-fluke/fullstack-starter --skill oma-imagegit clone --depth 1 https://github.com/first-fluke/fullstack-starterWrote 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/first-fluke/fullstack-starter/oma-image)<a href="https://agentmods.dev/skills/first-fluke/fullstack-starter/oma-image"><img src="https://agentmods.dev/badge/skills/first-fluke/fullstack-starter/oma-image/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/first-fluke/fullstack-starter/oma-image"><img src="https://agentmods.dev/badge/skills/first-fluke/fullstack-starter/oma-image.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 | $0.00033 | $0.01701 |
| Opus 5.5 | $0.00013 | $0.00680 |
| Sonnet 5.5 | $0.00007 | $0.00340 |
| Haiku 4.5 | $0.00003 | $0.00170 |
Grade A, and why
oma-image 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 14d 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.
This is a copy
100% identical to oma-image — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Agent - Multi-Vendor Image Router
Scheduling
Goal
Generate images and visual assets through authenticated multi-vendor routing while preserving prompt clarity, reference-guided regeneration, cost controls, and reproducible output manifests.
Intent signature
- User asks to generate images, visual assets, illustrations, product photos, concept art, mockups, or AI art.
- Another skill needs shared image-generation infrastructure.
- User provides reference images for a new generated variation or asks for vendor comparison.
When to use
- Generating images, visual assets, illustrations, product photos, concept art
- Comparing output between multiple image models for the same prompt
- Producing images from prompts within editor workflows (Claude Code, Codex, Gemini CLI)
- Other skills needing image generation infrastructure (shared invocation)
- Regenerating a new image that follows a supplied reference's subject, style, lighting, or composition
When NOT to use
- Pixel-level editing, masking, inpainting, object removal, compositing, cropping, resizing, or format conversion -> out of scope; use an image editor or a tool that explicitly supports that operation.
- Generating videos or audio -> out of scope
- Inline vector art / SVG composition from structured data -> use a templating skill
- Simple asset resizing or format conversion -> use a dedicated image library
Expected inputs
- Image prompt or creative brief
- Optional vendor, size, quality, count, output directory, and reference images
- Authentication/environment state for Codex, Pollinations, or Gemini
Expected outputs
- Generated image files under
.agents/results/images/or requested output directory manifest.jsonwith prompt, vendor, model, and reproducibility metadata- Vendor comparison outputs when
--vendor allis used
Dependencies
oma image generateCLI and vendor authentication- Codex image generation, Pollinations API, or Gemini API/CLI strategy
resources/vendor-matrix.md,resources/prompt-tips.md, and theimage:section of.agents/oma-config.yaml
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 14d ago Changed 04a953e23f52
- 1mo ago Changed · -143 lines · -57 tokens per session 3ed9a3c26f5b
- 1mo ago Changed 5239ab60860d
- 1mo ago First seen · 283 lines · 90 tokens per session scan A 0b84bbd69121
oma-image is a skill published in the GitHub repository first-fluke/fullstack-starter (224 stars, last pushed yesterday), licensed MIT. It adds 33 tokens to every session and 1,701 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to oma-image, differing in 0 lines, and is treated as a copy.
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