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 aa-on-ai/agentic-design-system --skill agent-friendly-designgit clone --depth 1 https://github.com/aa-on-ai/agentic-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/aa-on-ai/agentic-design-system/agent-friendly-design)<a href="https://agentmods.dev/skills/aa-on-ai/agentic-design-system/agent-friendly-design"><img src="https://agentmods.dev/badge/skills/aa-on-ai/agentic-design-system/agent-friendly-design/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/aa-on-ai/agentic-design-system/agent-friendly-design"><img src="https://agentmods.dev/badge/skills/aa-on-ai/agentic-design-system/agent-friendly-design.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 | $0.00154 | $0.02206 |
| Opus 5 | $0.00077 | $0.01103 |
| Sonnet 5 | $0.00031 | $0.00441 |
| Haiku 4.5 | $0.00015 | $0.00221 |
Grade A, and why
agent-friendly-design 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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
agent-friendly design
how to build sites and apps that AI agents can actually use.
why this exists
most design guidance is about agents building UI. this skill is about agents consuming UI. the audience for your site is no longer just humans — automated traffic surpassed human traffic in 2024 (51% of all web interactions). agents browse, compare, purchase, research, and interact on behalf of users.
if your site is invisible to agents, you're invisible to a growing majority of the web.
the core insight
the accessibility tree — originally built for screen readers — is becoming the primary interface between AI agents and your website. OpenAI's Atlas explicitly uses ARIA tags to interpret page structure. Microsoft's Playwright MCP provides accessibility snapshots, not screenshots. even vision-first agents (Anthropic Computer Use, Google Mariner) are incorporating accessibility data for reliability.
building for agents and building for accessibility are the same work. every improvement you make for one benefits the other.
the checklist
1. semantic HTML (non-negotiable)
agents can't "see" your layout. they read structure. div soup is invisible.
- use native elements:
<button>,<nav>,<main>,<article>,<section>,<header>,<footer>,<aside> - proper heading hierarchy:
<h1>through<h6>, no skipped levels <label>elements explicitly associated with form inputs (useforattribute)<table>for tabular data with<thead>,<th>, andscopeattributes- links are
<a>elements, buttons are<button>elements. never<div onclick> - use
<form>for forms, with<fieldset>and<legend>for groups - meaningful
<img alt>text (not "image1.png")
test: disable CSS. can you still understand the page? if yes, agents can too.
2. ARIA: useful, not magic
ARIA supplements semantic HTML — it doesn't replace it. use it when native elements can't express the interaction.
aria-labelon buttons and links that lack visible text (icon buttons, close buttons)aria-expandedon toggles, dropdowns, accordionsaria-liveregions for dynamic content agents need to notice (status messages, notifications)roleattributes only when there's no native element (e.g.,role="tablist",role="dialog")aria-describedbyfor complex form fields that need additional contextaria-hidden="true"on decorative elements agents should ignore
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 · 184 lines · 154 tokens per session scan A 4d03ef014984
agent-friendly-design is a skill published in the GitHub repository aa-on-ai/agentic-design-system (5 stars, last pushed 19d ago), licensed MIT. It adds 154 tokens to every session and 2,206 once invoked, about $0.0008 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.
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