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 tamtom/image-generation-skills --skill gpt-image-1-5git clone --depth 1 https://github.com/tamtom/image-generation-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/tamtom/image-generation-skills/gpt-image-1-5)<a href="https://agentmods.dev/skills/tamtom/image-generation-skills/gpt-image-1-5"><img src="https://agentmods.dev/badge/skills/tamtom/image-generation-skills/gpt-image-1-5/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/tamtom/image-generation-skills/gpt-image-1-5"><img src="https://agentmods.dev/badge/skills/tamtom/image-generation-skills/gpt-image-1-5.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 | $0.00123 | $0.02618 |
| Opus 5.5 | $0.00049 | $0.01047 |
| Sonnet 5.5 | $0.00025 | $0.00524 |
| Haiku 4.5 | $0.00012 | $0.00262 |
Grade A, and why
gpt-image-1-5 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 1mo 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 — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GPT Image 1.5 - Image Generation & Editing
Generate new images or edit existing ones using OpenAI's GPT Image 1.5 model via the Images API.
Usage
Run the script using absolute path (do NOT cd to skill directory first):
Generate new image:
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "your image description" --filename "output.png" [--quality low|medium|high] [--size 1024x1024|1024x1536|1536x1024|auto] [--background transparent|opaque|auto] [--output-format png|webp|jpeg] [--output-compression 0-100] [--n 1-4] [--api-key KEY]
Generate multiple variations:
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "your image description" --filename "output.png" --n 4 --quality high
Edit existing image (without mask - full image edit):
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "editing instructions" --filename "output.png" --input-image "path/to/input.png" [--quality low|medium|high] [--input-fidelity high|low] [--output-format png|webp|jpeg] [--api-key KEY]
Edit with multiple reference images (compositing/style transfer):
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "combine the subject from first image with the style of second image" --filename "output.png" --input-image "subject.png" --input-image "style-ref.png" [--input-fidelity high] [--api-key KEY]
Edit existing image (with mask - precise inpainting):
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "what to put in masked area" --filename "output.png" --input-image "path/to/input.png" --mask "path/to/mask.png" [--api-key KEY]
Important: Always run from the user's current working directory so images are saved where the user is working, not in the skill directory.
Parameters
Quality Options
- low - Fastest generation, lower quality
- medium (default) - Balanced quality and speed
- high - Best quality, slower generation. Use for dense text, detailed layouts, and high-fidelity output
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.
- 1mo ago First seen · 210 lines · 123 tokens per session scan A f53759197c47
gpt-image-1-5 is a skill published in the GitHub repository tamtom/image-generation-skills (9 stars, last pushed 7mo ago), licensed MIT. It adds 123 tokens to every session and 2,618 once invoked, about $0.0005 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.
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