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 dark-blue-contrasting-cleangit 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/dark-blue-contrasting-clean)<a href="https://agentmods.dev/skills/devinilabs/pro-skill/dark-blue-contrasting-clean"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/dark-blue-contrasting-clean/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/dark-blue-contrasting-clean"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/dark-blue-contrasting-clean.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 | $0.00032 | $0.00839 |
| Opus 5 | $0.00016 | $0.00419 |
| Sonnet 5 | $0.00006 | $0.00168 |
| Haiku 4.5 | $0.00003 | $0.00084 |
Grade A, and why
dark-blue-contrasting-clean 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 6d 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 dark-blue-contrasting-clean — 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dark Blue Contrasting Clean Skill
Use When
- Create a dark-blue clean design system with strong contrast, cobalt gradient feature blocks, crisp framed structure, and restrained premium glow.
Workflow
Scope
- Apply this as a full design-system direction across page background, framing rails, hero or CTA bands, cards, link groups, navigation, and motion.
- Use it when the interface should feel premium, dark, crisp, and blue-led, with strong contrast between deep navy surfaces and brighter cobalt focal regions.
- This is not an airy cloud-blue system and not loud neon sci-fi. It should stay clean, architectural, and high-contrast.
Visual target
- Build the page on a near-black navy base, using dark blue-black backgrounds with subtle tonal variation rather than flat pure black.
- Introduce one or more prominent cobalt or royal-blue feature blocks as contrast moments, such as hero banners, CTA bands, spotlight cards, or product sections.
- Use white typography and pale-blue support text over the dark system so the contrast feels sharp, readable, and premium.
- Add thin outer rails, border-x container lines, small corner squares, and quiet framing detail so the layout feels disciplined and engineered.
- Let blue glow stay soft and localized, appearing in background blooms, button emphasis, or tiny live indicators instead of flooding the whole page.
Implementation guidance
- Prefer a framed max-width shell or inner container with vertical boundary lines and subtle corner markers holding the composition together.
- Use border-gradient wrappers for premium blue feature blocks and dark cards, then place cleaner inner fills inside them so the edge treatment stays crisp.
- Organize the layout in clean stacked zones: a high-impact contrast block, then quieter index or navigation areas, followed by a restrained legal or footer zone.
- Buttons and CTA cards should feel firm and premium, using dark translucent fills, blue-tinted borders, pale-blue copy, and hover states that brighten slightly.
- Typography should remain light and elegant: thin to regular sans-serif weights, generous spacing, and small uppercase utility lines for section numbering or metadata.
- Use subtle abstract blue light fields, large blurred glows, circular traces, or soft overlay washes to add atmosphere without weakening the clean structure.
- Motion should stay calm and premium: masked word reveals, fade-up sections, quiet icon drift, and gentle hover translation are appropriate.
What ships with it
3 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.
- 6d ago First seen · 55 lines · 32 tokens per session scan A d92603c74fc0
dark-blue-contrasting-clean is a skill published in the GitHub repository devinilabs/pro-skill (24 stars, last pushed 27d ago), licensed MIT. It adds 32 tokens to every session and 839 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to dark-blue-contrasting-clean, differing in 0 lines, and is treated as a copy.
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