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 Vallykrie/swarmGPT --skill codex-imagegengit clone --depth 1 https://github.com/Vallykrie/swarmGPTWrote 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/vallykrie/swarmgpt/codex-imagegen)<a href="https://agentmods.dev/skills/vallykrie/swarmgpt/codex-imagegen"><img src="https://agentmods.dev/badge/skills/vallykrie/swarmgpt/codex-imagegen.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 | $0.00112 | $0.01143 |
| Opus 5 | $0.00056 | $0.00571 |
| Sonnet 5 | $0.00022 | $0.00229 |
| Haiku 4.5 | $0.00011 | $0.00114 |
Grade A, and why
codex-imagegen 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 6d 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
codex-imagegen
You cannot produce raster images. codex exec sessions can: the Codex CLI
exposes a built-in image_gen.imagegen tool that generates and edits images
using the user's existing ChatGPT authentication. No API key is required
and no OPENAI_API_KEY is used — this runs on the plan the user already
signed into with codex login.
Your job: turn the request into a precise image prompt, dispatch it, verify the file that comes back, and deliver it.
Step 0 — Preflight
command -v codex— if missing, stop and tell the user to install the Codex CLI (npm install -g @openai/codex) and runcodex login.- Locate
dispatch.shas in codex-swarm Step 0. You can also callcodex execdirectly for a single image; the dispatcher is for batches.
Step 1 — Build the manifest
For each requested image, record as separate fields:
- purpose — what it is for (icon, hero, texture, OG card…)
- prompt — the detailed description you will send
- new or edit — edits need exact input paths
- destination — an absolute output path
- format — png, jpg, webp
Treat a user-specified path and format as immutable. Do not rename the file,
change its extension, or pick a different directory without asking. If the
user gave no path, choose a sensible project location (assets/, public/,
docs/images/) and say which one you picked. If the exact path already exists
and replacement was not requested, ask before overwriting.
Step 2 — Write the image prompt
Codex generates what you describe, so describe it fully. Cover: subject, composition and framing, style (flat vector, 3D render, photo, watercolor…), palette, lighting, background (state explicitly if it must be transparent), aspect ratio, and any text that must appear verbatim. Name what must not be there too — stray text, watermarks, borders.
For an edit, pass the exact absolute path of every input file and state what must stay unchanged.
Step 3 — Dispatch
One job per image. Images are independent, so a batch goes out in parallel.
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.
- 6d ago First seen · 104 lines · 112 tokens per session scan A 3af28044b187
codex-imagegen is a skill published in the GitHub repository Vallykrie/swarmGPT (2 stars, last pushed 1mo ago), licensed MIT. It adds 112 tokens to every session and 1,143 once invoked, about $0.0006 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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