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 hassancs91/claude-image-generation --skill level-1-image-generatorgit clone --depth 1 https://github.com/hassancs91/claude-image-generationWrote 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/hassancs91/claude-image-generation/level-1-image-generator)<a href="https://agentmods.dev/skills/hassancs91/claude-image-generation/level-1-image-generator"><img src="https://agentmods.dev/badge/skills/hassancs91/claude-image-generation/level-1-image-generator/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/hassancs91/claude-image-generation/level-1-image-generator"><img src="https://agentmods.dev/badge/skills/hassancs91/claude-image-generation/level-1-image-generator.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 | $0.00208 | $0.03591 |
| Opus 5.5 | $0.00083 | $0.01436 |
| Sonnet 5.5 | $0.00042 | $0.00718 |
| Haiku 4.5 | $0.00021 | $0.00359 |
Grade C, and why
prompt-to-design scanned grade C with 1 finding 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.
Tells the agent never to refusehighAnti-refusal
Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.
never refuse, never return a blob that ignores the prompt. How it starts
The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
prompt-to-design
Turn a free-form prompt + an aspect ratio into a finished PNG, built entirely from
code. The house style is the level of the four pieces in reference/: posters,
typographic covers, mesh/gradient atmospheres, geometric compositions, soft
product abstractions. Frictionless like an image generator, but bounded to
designed graphics.
What it is (and is not)
Everything is drawn with math and type — no image model. That means:
- Great at: posters & album art, quote / story / reel / carousel covers, wallpapers, gradient & mesh backgrounds, neon / synthwave, Bauhaus / Swiss geometric art, minimalist logos-as-shapes, patterns, soft "product" orbs, anything typographic. Crisp text, perfect alignment, editable, no AI artifacts.
- Cannot do: photorealism, a specific real person's face, detailed representational illustration (a recognizable animal, a fantasy castle), brand logos, or copyrighted characters.
Accept any prompt and always output a designed PNG. Silently route the prompt to the rendering approach that fits (see Style routing). Only if a prompt truly demands a photo (e.g. "photorealistic portrait of my friend") say so in one sentence and deliver the strongest stylized/typographic interpretation anyway — never refuse, never return a blob that ignores the prompt.
Inputs
- Prompt — free text. Extract: subject/scene, mood, any color cues, and any literal words to render (quotes, titles, handles), plus implied style.
- Aspect ratio — a preset or
WxH. If unspecified, default 1:1.
The pipeline (follow in order)
- Read the prompt. Identify subject, mood, palette hints, literal text, ratio.
- Route to a style (one of: typographic, geometric, gradient-atmospheric, soft-minimal, poster-scene) — see below. When ambiguous, pick the one that best serves the words + mood.
- Choose a palette (3–6 colors, deliberate). See Palette.
- Plan the composition in your head first: the ONE focal element, the hierarchy, where the negative space lives. Balance mass with space.
- Assign fonts by role (display / grotesque / geometric / serif / serif_book / mono / pixel / techno). See Typography.
- Write a Python script that imports the engine and composes the piece (pattern below). Prefer the library primitives; drop to numpy only for custom effects.
- Render to a PNG in the outputs directory.
- VERIFY (mandatory gate — see Verify). Fix issues, re-render.
- Present the PNG. (Do not show the user the internal design reasoning or any
.mdnotes — PNG only.)
What ships with it
53 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.
- fonts/BigShoulders-Bold.ttf 92 KB
- fonts/BigShoulders-OFL.txt 4.3 KB
- fonts/BigShoulders-Regular.ttf 92 KB
- fonts/Boldonse-OFL.txt 4.3 KB
- fonts/Boldonse-Regular.ttf 75 KB
- fonts/CrimsonPro-Bold.ttf 105 KB
- fonts/CrimsonPro-Italic.ttf 106 KB
- fonts/CrimsonPro-OFL.txt 4.3 KB
- fonts/CrimsonPro-Regular.ttf 104 KB
- fonts/DMMono-OFL.txt 4.3 KB
- fonts/DMMono-Regular.ttf 48 KB
- fonts/EricaOne-OFL.txt 4.3 KB
- fonts/EricaOne-Regular.ttf 24 KB
- fonts/Gloock-OFL.txt 4.3 KB
- fonts/Gloock-Regular.ttf 93 KB
- fonts/InstrumentSans-Bold.ttf 66 KB
- fonts/InstrumentSans-BoldItalic.ttf 68 KB
- fonts/InstrumentSans-Italic.ttf 68 KB
- fonts/InstrumentSans-OFL.txt 4.3 KB
- fonts/InstrumentSans-Regular.ttf 66 KB
- fonts/JetBrainsMono-Bold.ttf 112 KB
- fonts/JetBrainsMono-OFL.txt 4.3 KB
- fonts/JetBrainsMono-Regular.ttf 112 KB
- fonts/Lora-Bold.ttf 131 KB
- fonts/Lora-BoldItalic.ttf 137 KB
- fonts/Lora-Italic.ttf 136 KB
- fonts/Lora-OFL.txt 4.3 KB
- fonts/Lora-Regular.ttf 131 KB
- fonts/Outfit-Bold.ttf 54 KB
- fonts/Outfit-OFL.txt 4.3 KB
- fonts/Outfit-Regular.ttf 54 KB
- fonts/PixelifySans-Medium.ttf 50 KB
- fonts/PixelifySans-OFL.txt 4.3 KB
- fonts/Silkscreen-OFL.txt 4.3 KB
- fonts/Silkscreen-Regular.ttf 31 KB
- fonts/Tektur-Medium.ttf 74 KB
- fonts/Tektur-OFL.txt 4.3 KB
- fonts/Tektur-Regular.ttf 74 KB
- fonts/WorkSans-Bold.ttf 187 KB
- fonts/WorkSans-BoldItalic.ttf 172 KB
- fonts/WorkSans-Italic.ttf 170 KB
- fonts/WorkSans-OFL.txt 4.3 KB
- fonts/WorkSans-Regular.ttf 184 KB
- fonts/YoungSerif-OFL.txt 4.3 KB
- fonts/YoungSerif-Regular.ttf 103 KB
- lib/fonts.py 3.8 KB runs code
- lib/render.py 25 KB runs code
- outputs/coffee-shop-logo.png 2081 KB
- README.md 2.8 KB
- reference/geometric_bauhaus.py 2.9 KB runs code
- reference/quote_card.py 2.7 KB runs code
- reference/soft_carousel.py 2.2 KB runs code
- reference/synthwave_poster.py 4.6 KB runs code
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 · 251 lines · 208 tokens per session scan C 06979440437b
prompt-to-design is a skill published in the GitHub repository hassancs91/claude-image-generation (109 stars, last pushed 2mo ago), licensed MIT. It adds 208 tokens to every session and 3,591 once invoked, about $0.0008 per session on Opus 5.5. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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