Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add int2t05/engineering-skills/plugin install engineering-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/int2t05/engineering-skills/imagegen)<a href="https://agentmods.dev/skills/int2t05/engineering-skills/imagegen"><img src="https://agentmods.dev/badge/skills/int2t05/engineering-skills/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 | $0.00120 | $0.01224 |
| Opus 5 | $0.00060 | $0.00612 |
| Sonnet 5 | $0.00024 | $0.00245 |
| Haiku 4.5 | $0.00012 | $0.00122 |
Grade A, and why
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 yesterday.
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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Imagegen
Generate premium design reference images across three modes — brand identity, web sections, mobile screens — that feel art-directed and implementation-friendly, not generic AI slop. Output is images only, never code.
When to use
- Brand identity boards, logo concepts, identity systems → brand mode
- Website section reference images (one horizontal image per section) → web mode
- Mobile app screen concepts and multi-screen flows → mobile mode
- Triggers on "brand kit", "logo 设计", "品牌系统", "web design image", "landing page image", "网站设计图", "mobile design image", "app screen image", "移动端设计图", "手机界面图"
Not for: frontend code (use frontend-design); image-to-code pipeline (use image-to-code).
Tool note: use an available image-generation tool — do not bind to a specific product.
Steps
1. Pick the mode and load its workflow
Infer from the brief which mode fits, then load that mode's reference for the full workflow. Each mode has its own section-count rule, composition logic, and anti-slop list.
- brand — brand-kit overview boards, logo concepting, identity systems → references/brand-mode.md
- web — one horizontal section image per section, premium art direction → references/web-mode.md
- mobile — phone-mockup-framed app screens and multi-screen flows → references/mobile-mode.md
If the brief spans modes (e.g. a brand system plus web mockups), lead with the primary mode and note the secondary. Do not mash modes into one frame.
2. Hold one art direction across the set
Whatever the mode, lock one visual direction — palette, typography, imagery treatment, corner radius, density — and keep it consistent across every image in the set. Screen 3 must not drift into a different product world than screen 1. The mode reference defines the mode-specific bible; this step is the shared consistency spine across the whole set.
3. Ban AI slop (all modes)
What ships with it
4 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.
- yesterday Changed · +1 lines 119f4eca2d7a
- 5d ago First seen · 79 lines · 120 tokens per session scan A 6c9602c98771
imagegen is a skill published in the GitHub repository int2t05/engineering-skills (3 stars, last pushed 4d ago), licensed MIT. It adds 120 tokens to every session and 1,224 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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