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 bnet47/codexicon --skill design-experiencegit clone --depth 1 https://github.com/bnet47/codexiconWrote 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/bnet47/codexicon/design-experience)<a href="https://agentmods.dev/skills/bnet47/codexicon/design-experience"><img src="https://agentmods.dev/badge/skills/bnet47/codexicon/design-experience/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/bnet47/codexicon/design-experience"><img src="https://agentmods.dev/badge/skills/bnet47/codexicon/design-experience.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 | $0.00034 | $0.01141 |
| Opus 5.5 | $0.00014 | $0.00456 |
| Sonnet 5.5 | $0.00007 | $0.00228 |
| Haiku 4.5 | $0.00003 | $0.00114 |
Grade A, and why
design-experience 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 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.
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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design experience
Create a coherent customer experience, not a decorated wireframe. Make every visual choice serve the product, audience, setting, and task.
1. Establish context
Read the approved charter or feature brief, existing interface, design system, brand assets, content, and relevant conventions. Read agent_docs/design.md when it exists. Do not create durable design context unless the user requests it or the approved workflow requires it.
Resolve the target surface before applying visual guidance. In a monorepo:
- Identify the app or package that owns the route or component, then inspect its nearest applicable instructions, design brief, design-system files, and incumbent interface.
- Treat root-level
agent_docs/design.mdand shared tokens as repository-wide constraints or fallback context. Do not import another app's surface direction, assets, or conventions. - Prefer the closest applicable owner guidance when scopes differ, unless a higher-level constraint explicitly governs the choice.
- If ownership or scope is unclear, state the uncertainty and use the target's existing implementation as evidence rather than inventing a shared design system.
- Keep resulting design context app- or surface-scoped. Create durable files only when requested or required by the approved workflow.
Define before implementation:
- user, primary task, setting, and observable success;
- surface register: brand when design carries identity and persuasion, or product when design primarily serves repeated work;
- product personality, emotional tone, and anti-references;
- one memorable, context-specific design idea;
- brand, platform, accessibility, performance, content, and licensing constraints;
- required viewports, states, and interaction paths.
Write one physical-scene sentence: who uses this, where, in what conditions, and with what level of urgency or attention. Use it to choose light versus dark, density, contrast, target sizes, motion, and information hierarchy.
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.
- 1mo ago Changed · +8 lines bc7765e29617
- 1mo ago First seen · 77 lines · 34 tokens per session scan A b8231e9b63e0
design-experience is a skill published in the GitHub repository bnet47/codexicon (5 stars, last pushed 3d ago), licensed MIT. It adds 34 tokens to every session and 1,141 once invoked, about $0.0001 per session on Opus 5.5. 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
visual-asset-design
A guide for turning character, scene, and prop ideas into prompts for generating consistent reference images. It covers layouts, camera views, visual identity, and continuity across image variations.
ui-mockup
Create UI mockups at three fidelity levels — ASCII wireframes for quick iteration, standalone HTML mockups for delivery with requirements, and live prototypes for interaction testing.
oma-design
Define or review a visual system, DESIGN.md, or redesign direction. Use for typography, layout, color, motion, and interaction design decisions.
conversion-review
Review a landing page or form to find why visitors do not sign up or buy: unclear message, friction, missing proof, weak call to action. Looks at the real page on desktop and phone and ranks the fixes.
frontend-design
Give a web page or app its own look instead of a generic AI-made one: choose colors, type and layout on purpose before building, then critique the result. Use when building a new interface or reshaping an existing one.
brand-assets
Make images, covers and transparent cutouts that look like one family: a pinned style sheet, fixed formats, every file checked against it, and cutouts confirmed truly transparent.