Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/slogsdon/skills-designnpx agentmods add skills/slogsdon/skills-design/design-systemWrote 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/slogsdon/skills-design/design-system)<a href="https://agentmods.dev/skills/slogsdon/skills-design/design-system"><img src="https://agentmods.dev/badge/skills/slogsdon/skills-design/design-system/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/slogsdon/skills-design/design-system"><img src="https://agentmods.dev/badge/skills/slogsdon/skills-design/design-system.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 | $0.00087 | $0.03750 |
| Opus 5 | $0.00044 | $0.01875 |
| Sonnet 5 | $0.00017 | $0.00750 |
| Haiku 4.5 | $0.00009 | $0.00375 |
Grade A, and why
design-system 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.
How it starts
The opening of the file, as written. The whole thing — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: design-system
Generates three artifacts that together define a brand's visual system:
DESIGN.md— portable spec following the Google design.md format. YAML frontmatter (machine-readable tokens) + 8 markdown sections (human rationale).tokens.css— CSS custom properties exported from the YAML, consumed bydesign-ui-componentsand every platform skill.showcase.html— single self-contained HTML page that renders every token in context. The visual proof that the system holds together.
When to use
- After
/design-planhas producedDESIGN-PLAN.md - Before any platform artifact skill (LinkedIn, Twitter, YouTube, etc.) — they all read
DESIGN.mdandtokens.css - When iterating on brand: re-run to regenerate downstream files when the plan changes
Inputs
- Required: brand slug (e.g.
shane-personal) - Preferred: existing
./design/<brand-slug>/DESIGN-PLAN.md(read with Read tool) - Fallback: if no plan exists, ask the user for a 3-question inline brief (visual direction, voice adjectives, hard NOs)
Outputs
./design/<brand-slug>/
DESIGN.md # Google spec format
tokens.css # CSS custom properties
showcase.html # visual proof
Steps
1. Locate and read the plan
test -f ./design/<brand-slug>/DESIGN-PLAN.md
If present, read it. If absent, ask the user 3 quick questions (visual direction, voice adjectives, hard NOs) and proceed with those answers as the de-facto plan.
2. Derive concrete tokens from the plan
Translate the plan's strategic decisions into specific token values. Use these heuristics by visual direction:
editorial → display serif (Fraunces, Playfair Display, Crimson Pro, Newsreader), restrained sans body (Söhne, Public Sans, IBM Plex Sans), mono accents (JetBrains Mono, Berkeley Mono); warm neutral surface (#fbfaf9-ish, not pure white); single ink color near-black; one accent used sparingly; generous letter-spacing on small uppercase labels (0.18em+); hairline rules over heavy borders; small radius (0–4px).
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 · 318 lines · 87 tokens per session scan A 3c5ccc657253
design-system is a skill published in the GitHub repository slogsdon/skills-design (3 stars, last pushed 25d ago), licensed MIT. It adds 87 tokens to every session and 3,750 once invoked, about $0.0004 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.
Other skills, from other repositories
brand-visual-language
A brand's visual tone — playful or serious, rounded or angular — should be consistent across all UI elements. Shape language in typography, border-radius, and iconography communicates personality before a single word is read. Use when establishing a design system, choosing icon libraries, setting border-radius tokens…
loading-states-and-perceived-performance
Manage user expectations during wait times with appropriate loading states — from simple spinners to complex skeleton screens and staggered animations. Perceived performance is often more important than actual load time. Use when designing data-heavy components, handling API calls, building hero sections, or improving…
micro-interactions
Micro-interactions are small, purposeful animations and responses that reward the user and make the interface feel alive — an animated icon, a satisfying toggle, a subtle reveal. Borrowed from the natural world, they add delight without distraction. Use when designing interactive components, success states, toggles…
motion-and-storytelling
Disney's 12 animation principles, cinematic storytelling techniques, and comic book conventions apply to web UI — used subtly, they make interfaces feel alive, intentional, and emotionally resonant. Use when designing transitions, micro-interactions, onboarding flows, scroll animations, or any motion in the UI.
elevation-and-depth
Elevation — subtle shadows and layering — communicates visual hierarchy by lifting elements above the surface. Combined with border-radius, it creates the tactile quality of cards, modals, and interactive surfaces. Use when designing cards, dropdowns, modals, tooltips, or any floating UI element.
responsive-paradigms
Mobile, tablet, and desktop are different interaction paradigms — not the same layout scaled up or down. Sections can be hidden, repositioned, or made sticky on mobile. Navigation and primary actions move. Use when designing responsive layouts, adapting desktop UI for mobile, or deciding what to show on each…