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 RaphLorr/claude-skill-image-gen --skill claude-skill-image-gengit clone --depth 1 https://github.com/RaphLorr/claude-skill-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/raphlorr/claude-skill-image-gen/claude-skill-image-gen)<a href="https://agentmods.dev/skills/raphlorr/claude-skill-image-gen/claude-skill-image-gen"><img src="https://agentmods.dev/badge/skills/raphlorr/claude-skill-image-gen/claude-skill-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/raphlorr/claude-skill-image-gen/claude-skill-image-gen"><img src="https://agentmods.dev/badge/skills/raphlorr/claude-skill-image-gen/claude-skill-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 | $0.00076 | $0.01294 |
| Opus 5.5 | $0.00030 | $0.00518 |
| Sonnet 5.5 | $0.00015 | $0.00259 |
| Haiku 4.5 | $0.00008 | $0.00129 |
Grade A, and why
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 2mo 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image generation (gpt-image-2 via codex CLI)
Generate a real AI image by running the wrapper, which shells out to the
official codex binary (it already holds the ChatGPT auth) and saves a PNG:
python3 ~/.claude/skills/image-gen/scripts/generate.py "<detailed prompt>" \
--out <path/to/image.png> [--quality <q>] [--size <s>] [--ref <image>] [--effort <e>]
The script prints the saved file path on stdout. Show or embed it in your reply
(e.g. ) so the user can view it.
Writing the prompt
Always expand the user's request into a rich, specific prompt: subject, style, composition, lighting, colours, mood. gpt-image-2 rewards specificity.
Choosing --out
Always pass a descriptive path under the current project (e.g.
assets/hero-banner.png) so successive images don't overwrite each other.
Choosing --quality (default: auto)
high— user asks for "detailed", "photorealistic", "high-res", "print", "polished", a hero image, or final artwork.low— user asks for a "quick", "draft", "rough", or "placeholder" image.medium— explicitly asked for medium, or a balance of speed and detail.- omit (auto) — no quality signal in the request.
Higher quality costs more quota and time; don't default to high.
Choosing --effort (default: low)
Reasoning effort of the orchestrating model before it calls the image tool —
how hard it plans the prompt, not the pixel render quality. low is fastest
and cheapest and is right for most requests. Raise it only when planning helps:
medium/high— complex multi-subject scenes, accurate text inside the image, infographics/diagrams, or careful identity-preserving--refedits.xhigh— rarely; only whenhighstill misreads an intricate prompt.
low is the floor for image generation (minimal is rejected by the API for the
image tool). Higher effort is slower and uses more quota, so don't default to it.
Choosing --size (default: auto)
Pick from the user's intent; pass an aspect keyword, a ratio, or exact pixels:
landscape/16:9/wide— banners, headers, scenery, desktop wallpaper.portrait/2:3/tall— posters, phone wallpaper, full-body subjects.square/1:1— avatars, icons, app art, social posts.WIDTHxHEIGHT(e.g.1024x1024) — when the user gives exact dimensions.- omit (auto) — let the model choose.
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.
- 2mo ago First seen · 95 lines · 76 tokens per session scan A e8b593f24de1
image-gen is a skill published in the GitHub repository RaphLorr/claude-skill-image-gen (1 stars, last pushed 4mo ago), licensed MIT. It adds 76 tokens to every session and 1,294 once invoked, about $0.0003 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 compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| image-genRaphLorr/claude-skill-image-gen | Skill | 1 | 4mo ago | MIT | A | 76 | Claude Code, Codex |
| codex-auth-setupndycode/codex-multi-auth | Skill | 566 | 4d ago | MIT | A | 32 | Claude Code, Codex |
| examplendycode/codex-multi-auth | Skill | 566 | 4d ago | MIT | A | 10 | Claude Code, Codex |
| dynamic-workflowsccbud/CCBuddy | Skill | 8 | 25d ago | Apache-2.0 | A | 100 | Claude Code |
| visualizeccbud/CCBuddy | Skill | 8 | 25d ago | Apache-2.0 | A | 63 | Claude Code, Codex |
| explain-codebasesuryast/free-ai-agent-skills | Skill | 2 | 15d ago | MIT | A | 58 | Claude Code, Codex |
| context-canvas-checkpointphenomenoner/Chatgpt-Codex-App-Plus | Skill | 2 | 13d ago | MIT | A | 88 | Claude Code, Codex |