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/deepgram/dglabs-deepclawnpx agentmods add skills/deepgram/dglabs-deepclaw/openai-image-genWrote 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/deepgram/dglabs-deepclaw/openai-image-gen)<a href="https://agentmods.dev/skills/deepgram/dglabs-deepclaw/openai-image-gen"><img src="https://agentmods.dev/badge/skills/deepgram/dglabs-deepclaw/openai-image-gen/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/deepgram/dglabs-deepclaw/openai-image-gen"><img src="https://agentmods.dev/badge/skills/deepgram/dglabs-deepclaw/openai-image-gen.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 | $0.00025 | $0.00907 |
| Opus 5 | $0.00013 | $0.00453 |
| Sonnet 5 | $0.00005 | $0.00181 |
| Haiku 4.5 | $0.00003 | $0.00091 |
Grade A, and why
openai-image-gen 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 9d 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
98% identical to openai-image-gen — 4 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenAI Image Gen
Generate a handful of “random but structured” prompts and render them via the OpenAI Images API.
Run
python3 {baseDir}/scripts/gen.py
open ~/Projects/tmp/openai-image-gen-*/index.html # if ~/Projects/tmp exists; else ./tmp/...
Useful flags:
# GPT image models with various options
python3 {baseDir}/scripts/gen.py --count 16 --model gpt-image-1
python3 {baseDir}/scripts/gen.py --prompt "ultra-detailed studio photo of a lobster astronaut" --count 4
python3 {baseDir}/scripts/gen.py --size 1536x1024 --quality high --out-dir ./out/images
python3 {baseDir}/scripts/gen.py --model gpt-image-1.5 --background transparent --output-format webp
# DALL-E 3 (note: count is automatically limited to 1)
python3 {baseDir}/scripts/gen.py --model dall-e-3 --quality hd --size 1792x1024 --style vivid
python3 {baseDir}/scripts/gen.py --model dall-e-3 --style natural --prompt "serene mountain landscape"
# DALL-E 2
python3 {baseDir}/scripts/gen.py --model dall-e-2 --size 512x512 --count 4
Model-Specific Parameters
Different models support different parameter values. The script automatically selects appropriate defaults based on the model.
Size
- GPT image models (
gpt-image-1,gpt-image-1-mini,gpt-image-1.5):1024x1024,1536x1024(landscape),1024x1536(portrait), orauto- Default:
1024x1024
- Default:
- dall-e-3:
1024x1024,1792x1024, or1024x1792- Default:
1024x1024
- Default:
- dall-e-2:
256x256,512x512, or1024x1024- Default:
1024x1024
- Default:
Quality
- GPT image models:
auto,high,medium, orlow- Default:
high
- Default:
- dall-e-3:
hdorstandard- Default:
standard
- Default:
- dall-e-2:
standardonly- Default:
standard
- Default:
Other Notable Differences
- dall-e-3 only supports generating 1 image at a time (
n=1). The script automatically limits count to 1 when using this model. - GPT image models support additional parameters:
--background:transparent,opaque, orauto(default)--output-format:png(default),jpeg, orwebp- Note:
streamandmoderationare available via API but not yet implemented in this script
- dall-e-3 has a
--styleparameter:vivid(hyper-real, dramatic) ornatural(more natural looking)
What ships with it
1 file 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.
- 9d ago First seen · 90 lines · 25 tokens per session scan A af85649d8857
openai-image-gen is a skill published in the GitHub repository deepgram/dglabs-deepclaw (23 stars, last pushed 4mo ago), licensed MIT. It adds 25 tokens to every session and 907 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to openai-image-gen, differing in 4 lines, and is treated as a copy.
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.