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 Lrinvl1203/world-class-web-design-os --skill design-discoverygit clone --depth 1 https://github.com/Lrinvl1203/world-class-web-design-osWrote 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/lrinvl1203/world-class-web-design-os/design-discovery)<a href="https://agentmods.dev/skills/lrinvl1203/world-class-web-design-os/design-discovery"><img src="https://agentmods.dev/badge/skills/lrinvl1203/world-class-web-design-os/design-discovery/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/lrinvl1203/world-class-web-design-os/design-discovery"><img src="https://agentmods.dev/badge/skills/lrinvl1203/world-class-web-design-os/design-discovery.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 | $0.00036 | $0.00364 |
| Opus 5 | $0.00018 | $0.00182 |
| Sonnet 5 | $0.00007 | $0.00073 |
| Haiku 4.5 | $0.00004 | $0.00036 |
Grade A, and why
design-discovery 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 11d 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.
What it actually says
Design Discovery
Convert the request into a decision brief
Capture only information that changes the design:
- business/product and desired outcome;
- primary users and context of use;
- top job-to-be-done and secondary jobs;
- primary CTA/conversion and failure modes;
- content inventory and trust evidence;
- required pages, states, locales and devices;
- brand attributes and explicit anti-attributes;
- technical/deployment constraints;
- measurable CTQs.
CTQ examples
Translate adjectives into observable requirements.
- “premium” → deliberate art direction, controlled type hierarchy, authored imagery, restrained motion, no template residue.
- “fast to use” → core answer/action discoverable in one scan and short navigation path.
- “mobile-first” → content priority and interaction model are designed for touch before desktop decoration is added.
Ambiguity policy
Do not stall on low-risk gaps. Infer reasonable defaults, label them as assumptions, and continue. Ask only when a missing decision would materially change business logic, brand, legal requirements or architecture.
Output
Produce a concise design brief with: Goal, Audience, Primary Job, Primary Action, Content Priority, Brand, Anti-Direction, Constraints, CTQs.
When imagery, logos, footage, 3D models, fonts, or external references affect the direction, read references/asset-protocol.md and record ownership, rights, fidelity, fallback, and delivery status before treating an asset as available.
What ships with it
2 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.
- 11d ago First seen · 41 lines · 36 tokens per session scan A 4f478739bd69
design-discovery is a skill published in the GitHub repository Lrinvl1203/world-class-web-design-os (8 stars, last pushed 14d ago), licensed MIT. It adds 36 tokens to every session and 364 once invoked, about $0.0002 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
design-md
Author/validate/export Google's DESIGN.md token spec files.
component-family-consistency
Buttons, inputs, pills, badges, calendars, and other interactive components form a visual family — they share the same border-radius, colour logic, shadow scale, border style, and spacing rhythm. Inconsistency between them breaks the sense of a coherent product. Use when building or reviewing a component library…
modular-scale-typography
Typography feels cohesive and intentional when font sizes follow a modular scale — a ratio-based sequence where every size is mathematically related to the others. Use when defining type scales, setting up design tokens, reviewing font size choices, or when typography feels inconsistent or arbitrary.
extract-design
Extract a complete design system — colors, typography, spacing, components, shadows, and W3C design tokens — from any live website using Dembrandt. Runs a headless browser against the URL and returns real computed values from the DOM. Use when you need a site's actual design tokens, want to reverse-engineer a visual…
algorithmic-color-palette
Derive a full UI colour palette algorithmically from one or two brand colours. Darker and lighter variants for interactive states, desaturated greys from the brand hue for borders and backgrounds, and semantic colours that feel coherent with the brand rather than generic. Use when building a colour system from scratch…
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…