audit-design

audit-design is a command for Claude Code from tan-yong-sheng/ai-vision-mcp. It costs 22 tokens per session (346 once invoked), scanned A, original, MIT.

A command that audits a design from an image, such as a screenshot or website image. It checks usability conventions, accessibility, visual consistency, and design-system rules.

In plain words
What is it for?
Use it to review screenshots or image URLs, check mobile accessibility, assess WCAG requirements, and compare findings with an optional DESIGN.md file.
Why use it?
It helps find problems in an interface without relying on an informal visual review. You can choose a quick, standard, or deep analysis and supply extra focus areas.

Command for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions subagents.

Part of the design-eval plugin — 5 skills, 5 commands, 4 agents shipped together

Good fit Use it to review screenshots or image URLs, check mobile accessibility, assess WCAG requirements, and compare findings with an optional DESIGN.md file.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/tan-yong-sheng/ai-vision-mcp/audit-design
Install

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.

Clone the repo
git clone --depth 1 https://github.com/tan-yong-sheng/ai-vision-mcp

Made for: Claude Code.

Or install design-eval, the plugin that ships this one along with the rest of its 5 skills, 5 commands, 4 agents.

Wrote 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.

agentmods badge for audit-design

README.md
[![agentmods](https://agentmods.dev/badge/commands/tan-yong-sheng/ai-vision-mcp/audit-design/github.svg)](https://agentmods.dev/commands/tan-yong-sheng/ai-vision-mcp/audit-design)
Your own site
<a href="https://agentmods.dev/commands/tan-yong-sheng/ai-vision-mcp/audit-design"><img src="https://agentmods.dev/badge/commands/tan-yong-sheng/ai-vision-mcp/audit-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.

agentmods 80×15 button for audit-design

Your own site · 80×15
<a href="https://agentmods.dev/commands/tan-yong-sheng/ai-vision-mcp/audit-design"><img src="https://agentmods.dev/badge/commands/tan-yong-sheng/ai-vision-mcp/audit-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 346 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.00346
Opus 5 $0.00011 $0.00173
Sonnet 5 $0.00004 $0.00069
Haiku 4.5 $0.00002 $0.00035

Measured 12d ago against content hash 51b9fa4216d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

audit-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 12d 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.

plugins/design-eval/commands/audit-design.md · 36 lines

What it actually says

/design-eval:audit-design

Comprehensive design audit analyzing heuristics, accessibility, visual consistency, and design system governance.

Arguments

Argument Description Example
--imageSource URL, file path, or base64 image to audit https://example.com/screenshot.png
--depth Analysis depth: quick (30min), standard (1hr), deep (2hr) --depth standard
--design-system Path to DESIGN.md file for design-aware remediation (optional) --design-system ./DESIGN.md
--userPrompt Additional focus areas or custom instructions --userPrompt "focus on mobile accessibility"

Examples

/design-eval:audit-design --imageSource https://example.com/hero.jpg --depth standard
/design-eval:audit-design --imageSource ./screenshot.png --depth deep --userPrompt "check WCAG AAA compliance"
/design-eval:audit-design --imageSource https://example.com/hero.jpg --depth standard --design-system ./DESIGN.md

Execution Instructions

Route this request to the design-eval:design-auditor subagent. The final user-visible response must be the subagent's output verbatim.

Raw slash-command arguments: $ARGUMENTS

Changes

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.

  1. 12d ago First seen · 36 lines · 22 tokens per session scan A 51b9fa4216d8

Subscribe to this mod's changes

audit-design is a command published in the GitHub repository tan-yong-sheng/ai-vision-mcp (78 stars, last pushed 5mo ago), licensed MIT. It adds 22 tokens to every session and 346 once invoked, about $0.0001 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 2026-08-30.