Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/mkdev-me/agent-skillsnpx agentmods add skills/mkdev-me/agent-skills/openai-image-generatorWrote 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/mkdev-me/agent-skills/openai-image-generator)<a href="https://agentmods.dev/skills/mkdev-me/agent-skills/openai-image-generator"><img src="https://agentmods.dev/badge/skills/mkdev-me/agent-skills/openai-image-generator.svg" alt="Measured on agentmods" 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 | $0.00018 | $0.00581 |
| Opus 5 | $0.00009 | $0.00291 |
| Sonnet 5 | $0.00004 | $0.00116 |
| Haiku 4.5 | $0.00002 | $0.00058 |
Grade A, and why
openai-image-generator 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 8d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
openai-image-generator
Instructions
Use this skill to generate images using OpenAI's gpt-image-2 model. The skill supports:
- Text-to-image generation from prompts (
images.generate) - Image editing / composition with one or more reference images (
images.edit) - Size presets (square, landscape, portrait, 2K) or a raw
WxHstring - Quality levels (low / medium / high / auto)
- Custom output paths
The API key should be set via the OPENAI_API_KEY environment variable.
Parameters
--prompt(required): The text prompt describing the image to generate--output(required): Output file path for the generated image--reference: Optional reference image path. Can be specified multiple times. When provided, the edits endpoint is used.--size: Output size. Accepts a preset (square,landscape,portrait,2K) or a rawWxHstring (e.g.1920x1080). Default:square(1024x1024).--quality:low,medium,high, orauto(default:auto)
Size constraints for gpt-image-2: max edge 3840px, both edges multiples of 16, aspect ratio ≤ 3:1, total pixels between 655,360 and 8,294,400.
Examples
Basic text-to-image generation
./scripts/generate.py --prompt "A serene mountain landscape at sunset" --output images/landscape.png
With reference image(s) for editing / composition
./scripts/generate.py --prompt "Same character but wearing a party hat" --reference images/character.png --output images/party.png
./scripts/generate.py --prompt "Gift basket containing items from reference images" --reference a.png --reference b.png --output basket.png
Landscape, high quality
./scripts/generate.py --prompt "Cinematic cyberpunk skyline" --size landscape --quality high --output skyline.png
Custom raw size
./scripts/generate.py --prompt "Abstract banner" --size 1920x1088 --output banner.png
Setup
Before first use, set up the virtual environment:
cd scripts && python3 -m venv venv && ./venv/bin/pip install -r requirements.txt
What ships with it
2 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.
- 8d ago First seen · 66 lines · 18 tokens per session scan A b92b2f98b46d
openai-image-generator is a skill published in the GitHub repository mkdev-me/agent-skills (37 stars, last pushed 4mo ago), licensed MIT. It adds 18 tokens to every session and 581 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
webgl-holographic-foil
A self-contained WebGL2 hero: thin-film interference over a crushed-foil surface whose palette shifts with the viewing angle; move the cursor to tilt the film.
general-video
Author or edit a custom HyperFrames composition when no specialized workflow fits, or when BRIEF.md sets flow: companion. Use for longer or multi-scene pieces, brand and sizzle reels, montages, static loops, static title cards, footage remixes, and freeform builds. Use motion-graphics instead for a short unnarrated…
html-ppt-hermes-cyber-terminal
OpenDesign + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.
html-ppt-taste-brutalist
16:9 HTML deck in tactical-telemetry / CRT-terminal taste. Deactivated-CRT charcoal slides, white-phosphor monospace, hazard-red accent, scanline overlay, ASCII syntax, density over decoration. Distilled from Leonxlnx/taste-skill brutalist-skill (Tactical Telemetry mode).
diagnostic-stem-delivery
Audio production with diagnostic analysis, timecode parsing from documents, and verified export workflow.
chengfeng-check-updates
An environment manager for a video-editing system. It checks whether its skills and runtime—the software needed to run them—are installed and compatible.