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 veryCoolTimo/imagegen-skills --skill image-promptgit clone --depth 1 https://github.com/veryCoolTimo/imagegen-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/verycooltimo/imagegen-skills/image-prompt)<a href="https://agentmods.dev/skills/verycooltimo/imagegen-skills/image-prompt"><img src="https://agentmods.dev/badge/skills/verycooltimo/imagegen-skills/image-prompt/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/verycooltimo/imagegen-skills/image-prompt"><img src="https://agentmods.dev/badge/skills/verycooltimo/imagegen-skills/image-prompt.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 | $0.00148 | $0.03339 |
| Opus 5.5 | $0.00059 | $0.01336 |
| Sonnet 5.5 | $0.00030 | $0.00668 |
| Haiku 4.5 | $0.00015 | $0.00334 |
Grade A, and why
image-prompt 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
image-prompt
Turn a one-line idea into a single, gold-quality image-generation prompt. Auto-first: infer everything sensible, output the prompt, let the user redirect in one line.
Workflow
-
Read the idea. Extract: subject/brand, any style hints, aspect/format, target model. Invent a fictional placeholder brand name if branding is implied but none given. If the user names a saved style ("in the style", "use preset ") or asks to save one ("save this style as "), handle it via Style presets below. If the user wants help choosing a look ("help me with the style", "what styles can you do", "в каких стилях можешь"), present the Style menu below. If the user supplies an existing image to transform, composite, restyle, localize, or place someone/something into — or wants a poster/ad built around a supplied person or product — that is an EDIT: use Edit / remix mode below.
-
Pick the archetype using
references/archetypes.md(poster / landing-hero / product-ad / ui-mockup / photoreal-scene / game-screenshot / infographic / logo / illustration). Use the routing table. If ambiguous, choose the richest layout and note it. -
Set defaults from the archetype: aspect →
size,quality. (See the model adapter.) -
Expand into the 9-block skeleton using
references/anatomy.md. Skim the matching gold example(s) inreferences/gold-examples.mdto calibrate depth and phrasing. Pull fonts + a cohesive hex palette fromreferences/fonts-palettes.md. Fill every block: named zones with position/size%/tilt, literal copy in quotes, named fonts, hex palette, mood cluster, finish + quality tag. Photoreal/game ideas use the labeled-block variant. -
Format for the target model. Default
gpt-image-2→ followreferences/models/gpt-image-2.md(labeled sections, text-in-quotes, CONSTRAINTS block, size/quality). If the user names another model and its file doesn't exist yet, say so and fall back to the rich natural-language style, then proceed.
What ships with it
15 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.
- references/anatomy.md 7.5 KB
- references/archetypes.md 8.3 KB
- references/edit-remix.md 5.1 KB
- references/fonts-palettes.md 3.9 KB
- references/generation.md 3.0 KB
- references/gold-examples.md 23 KB
- references/models/flux.md 3.8 KB
- references/models/gemini.md 4.4 KB
- references/models/gpt-image-2.md 6.4 KB
- references/models/ideogram.md 3.3 KB
- references/models/midjourney.md 3.7 KB
- references/models/recraft.md 4.7 KB
- references/models/reve.md 3.9 KB
- references/models/universal.md 2.0 KB
- references/styles.md 5.2 KB
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 · 225 lines · 148 tokens per session scan A bbbf887d6d65
image-prompt is a skill published in the GitHub repository veryCoolTimo/imagegen-skills (6 stars, last pushed 3mo ago), licensed MIT. It adds 148 tokens to every session and 3,339 once invoked, about $0.0006 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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