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 devinilabs/pro-skill --skill generate-reference-inspired-brand-worldsgit clone --depth 1 https://github.com/devinilabs/pro-skillWrote 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/devinilabs/pro-skill/generate-reference-inspired-brand-worlds)<a href="https://agentmods.dev/skills/devinilabs/pro-skill/generate-reference-inspired-brand-worlds"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/generate-reference-inspired-brand-worlds/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/devinilabs/pro-skill/generate-reference-inspired-brand-worlds"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/generate-reference-inspired-brand-worlds.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 | $0.00089 | $0.01593 |
| Opus 5 | $0.00044 | $0.00796 |
| Sonnet 5 | $0.00018 | $0.00319 |
| Haiku 4.5 | $0.00009 | $0.00159 |
Grade A, and why
generate-reference-inspired-brand-worlds 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 9d 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.
This is a copy
100% identical to generate-reference-inspired-brand-worlds — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Reference-Inspired Brand Worlds
Create brand concepts that feel intentionally related to a reference while changing the identity, meaning, subjects, and signature composition. Treat this as an art-direction layer over the available image-generation workflow.
Start correctly
- Load and inspect every supplied image before prompting.
- Label each input explicitly:
Image 1: primary visual-language referenceImage 2: current concept/content anchorwhen revising an existing result
- Use the available image-generation tool. When the built-in
imagegenskill is available, load it and follow its save, reference, iteration, and validation rules. - Treat a style reference as guidance, not an edit target, unless the user asks to preserve specific pixels.
- Keep the reference image out of reusable skill assets unless the user owns it and explicitly authorizes redistribution.
Set the similarity dial
Use the user's language to choose a target. The numbers communicate intent; they are not measurable similarity scores.
- 30% — distant inspiration: keep only abstract principles such as mood, density, or contrast.
- 50% — recognizable influence: share medium and emotional tone; change palette, composition, subjects, and type system.
- 70% — adjacent brand family: share the reference's composition logic, texture, palette relationships, human presence, and wordmark scale while creating new subjects, actions, arrangement, and letterforms. Default here for “not too different from the inspiration.”
- 85% — close art-direction neighbor: preserve most high-level visual grammar but change at least four signature elements. Do not recreate an exact commercial identity.
If the user says “inspired, not copying,” preserve originality even when they request the 70–85% range.
Extract visual DNA
Write two short lists before generating.
Reusable visual grammar
Capture high-level relationships:
- scene density and depth layers
- palette relationships rather than exact swatches
- print, photographic, painterly, woven, or halftone surface
- lighting and emotional temperature
- type scale, weight, contrast, and placement logic
- amount and role of human presence
- rhythm of organic and architectural forms
What ships with it
7 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.
- 9d ago First seen · 156 lines · 89 tokens per session scan A ac378caa7a20
generate-reference-inspired-brand-worlds is a skill published in the GitHub repository devinilabs/pro-skill (24 stars, last pushed 26d ago), licensed MIT. It adds 89 tokens to every session and 1,593 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to generate-reference-inspired-brand-worlds, differing in 0 lines, and is treated as a copy.
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