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 andrewii23/ii23-skills --skill image-gen-routergit clone --depth 1 https://github.com/andrewii23/ii23-skillsWrote 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/andrewii23/ii23-skills/image-gen-router)<a href="https://agentmods.dev/skills/andrewii23/ii23-skills/image-gen-router"><img src="https://agentmods.dev/badge/skills/andrewii23/ii23-skills/image-gen-router/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/andrewii23/ii23-skills/image-gen-router"><img src="https://agentmods.dev/badge/skills/andrewii23/ii23-skills/image-gen-router.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 | $0.00239 | $0.02092 |
| Opus 5.5 | $0.00096 | $0.00837 |
| Sonnet 5.5 | $0.00048 | $0.00418 |
| Haiku 4.5 | $0.00024 | $0.00209 |
Grade A, and why
image-gen-router scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Gen Router
Claude cannot generate a raster image, but the user's ChatGPT and Google accounts can. This skill generates a raster image by driving one of two official CLIs, headless, under the account the user is already signed into: no API key, no per-image API bill, exactly as if the user typed the prompt into that tool themselves.
- GPT — the OpenAI Codex CLI (
codex execwith its built-in$imagegenskill, modelgpt-image-2), under the user's ChatGPT login. It counts toward the Codex plan's usage limits. - Gemini — the Google Antigravity CLI (
agy -p, headless mode, its built-in image tool), under the user's Google login. It uses the plan's Antigravity quota.
The whole point of this skill is letting the user pick the model. Everything else (subject, style, aspect, palette, mood) flows straight from the prompt into the chosen backend.
The one decision that matters: which backend
Before generating, you must know which backend to use. There are exactly two cases:
1. The user already named a backend → use it, don't ask. Honor whatever they said and skip straight to generation. Map their words like this:
- GPT, OpenAI, ChatGPT, codex, "the gpt one", DALL·E (as a model family, not the API) → gpt
- Gemini, Google, agy, Antigravity, "nano banana", "the google one" → gemini
Asking again when they've already told you is annoying and wastes a turn — the user was explicit for a reason.
2. The user did NOT name a backend → ask, with no default. Use the
AskUserQuestion tool with a single question and exactly two options, presented
as equals (neither marked "recommended" — the user didn't express a preference,
so don't manufacture one). For example:
AskUserQuestion(questions=[{
"question": "Which model should generate this image?",
"header": "Image model",
"multiSelect": false,
"options": [
{"label": "GPT (codex)", "description": "OpenAI image model via Codex CLI, under your ChatGPT login."},
{"label": "Gemini (agy)", "description": "Google image model via Antigravity CLI, under your Google login."}
]
}])
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.
- 2d ago Changed · +18 lines 2bb46d889ddd
- 2mo ago First seen · 160 lines · 239 tokens per session scan A b00472d6aeea
image-gen-router is a skill published in the GitHub repository andrewii23/ii23-skills (11 stars, last pushed 3d ago), licensed MIT. It adds 239 tokens to every session and 2,092 once invoked, about $0.0010 per session on Opus 5.5. 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.
image-gen-router compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| image-gen-routerandrewii23/ii23-skills | Skill | 11 | 3d ago | MIT | A | 239 | Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |