Multiple angled screenshots of a UX audit web application showing pages with audit summaries, detailed findings highlighted in color-coded boxes, a dashboard with overall scores, and form inputs to start a new audit, all set against a black background.
01
Opportunity
02
Ideation
03
Prototype
04
Testing
05  Working Tool
06  In Use

Problem to solve

Why an audit tool?

When it follows a pattern, it's a good candidate for automation. It'll get me to a good starting point, faster.

Whether a site needs a full redesign, a partial one or ongoing care, it starts with an audit: what's working, what needs improving and whether the brand and experience are delivering on the metrics that matter — conversion, retention and adoption.

There's a baseline that applies to any site, in any industry.

Outcomes (in progress)

Tested on 3 sites: 50 of 51 findings were right, 1 was partly right and 0 were wrong.

It missed 12 issues, mostly strategic, which is where a designer comes in.

TYPE
Productivity tool
STATUS
Prototype tested, building the working tool
ROLE
Designer and builder, solo
TOOLS
Claude Pro, Claude Design
AI experiment
UX audit
Automation
Prompt wireframing
Process design
Prototyping

Process

How I audit now

Same every time

Different every time

Goals + scope

Business goals, target audience, pages in scope.

15 min

Capture pages

Screenshots at three key sizes.

60 min

Auto

Sort into a file

Name, order, and annotate

60 min

Auto

Audit findings

Message, navigation, trust, page speed, etc.

2 hr

30 min

Strategy

Bigger picture: audience fit, structure, priorities.

45 min+

Share it

Report, plan or email for the client.

45 min

15 min

By hand: ~5¼ hrs

With the tool: ~1¾ hrs

Up next: Ideation

Scoping

Context and guardrails

I wanted to see how well AI can design and build a smart tool with some guardrails, but not too many.

What I gave AI

How I audit: Screenshot the key pages, pull into a workspace, check each against the same criteria, then pull findings into a report or plan.

Key criteria: Message, navigation, trust, next step and conversion, plus "website best practice".

A few style lines: Mostly white, black for actions, soft corners, pastel notes.

The guardrails

I check everything: AI drafts, I decide.

AI designs: See how intuitively AI designs UI/UX on its own.

Claude Pro only: No paid API or extra tools.

Built for a big screen: Desktop, where designers do their work.

Prompt wireframing

Five rounds in 3 hours

Each round started with AI's draft and ended with my feedback, mostly by voice, the way I'd talk through it with a colleague.

Wireframe 1: AI's first draft

Screenshot of a tool interface with a 'Review' tab active, showing a webpage review for the Homepage. The left sidebar lists pages by priority, the center displays a webpage wireframe with numbered issue markers, and the right panel lists review items including high, critical, and working well feedback with options to verify, edit, or dismiss each. The webpage wireframe includes placeholder blocks representing headline, content sections, and client logos with color-coded issue markers.

Prototype 2: After five rounds of feedback

User interface of a UX audit tool showing the Home page review with five findings marked on a webpage mockup. The left sidebar lists pages to review with counts and a progress bar for capturing pages. The central area displays a screenshot placeholder with numbered issue indicators. The right sidebar lists detailed audit comments for each finding, including severity tags like High and Critical, descriptive titles, explanations, and suggested actions with Verify and Ignore buttons. At the top, navigation options toggle device views: Desktop, Tablet, Mobile.

Round 1 + 2

Cut what wasn't adding value. Extra screens and inputs were busying and/or not informing results.

Round 3

Clearer statuses, page-by-page controls and "ignore" instead of "dismiss".

Round 4 + 5

AI defaulted to explaining how things work. People need to know how, not read how.

Prototype 1 + 2

Applied familiar UX and behavioural patterns, with colours only where it matters.

Up next: Prototype

Clickable prototype

Try it out

Prototype cannot display

It was built for desktop. Open this page on a laptop to try it, or scroll through images below.

Where AI was strong

Clear, consistent UI from a few sentences of direction.

A thorough framework from a short prompt, including checks and flow details I hadn't defined.

A few lines on style: Mostly white, black for key actions, soft corners, pastel notes.

Where it still needed me

The first draft worked but using it didn't feel that way. AI missed some basic interaction and usability deails that make a tool feel easy: panels that didn't scroll independently, pins that didn't open their finding, a shifting header, and filters that hid when they should focus.

Learnings

Solidified ideas

Looking right is quick, being right still takes a designer: AI gets to polished fast but we need to know what's wrong with it.

I don't always know what I'm missing: AI won't flag costs, limits or build needs unprompted. Domain knowledge i.e. dev is still very important.

A wireframe in minutes sharpens decisions: Seeing it quickly makes the calls easier.

Next steps

A prototype = clearer thinking

Having something working makes it easier to define and refine an MVP. It surfaces missed use cases and other problems worth solving.

The review works: The flow feels right. The big open question is whether AI can capture a real site and audit it well.

The report needs the most work: It's detailed, but I have no insight into how the score is calculated and it doesn't feel easy to follow for someone who wasn't part of the auditing experience.

It also needs a plan: When the audit is the first step of a redesign, the next step is a plan — quick wins first, then the deeper work.

Up next: Testing

Objectives

Test before building

The prototype shows how a review works but the findings are made up. Before building the working tool, I wanted to know two things: can it capture a site properly and are AI's findings good enough to build around?

Capture

Each page at desktop, tablet and mobile widths, using only what I already had: Claude Pro and the browser built into the Claude app.

Findings

AI runs my framework over each page and writes findings in the tool's format. I mark right, partly right or wrong and note anything missed.

Process

How it ran

Sample capture at three sizes, shown on my own site.

Website homepage shown in three screen sizes labeled Desktop 1440px, Tablet 768px, and Mobile 375px, displaying a blurred gradient background with the text 'Your designer, on demand.' above a subheading about helping startups design digital products and an email entry field with a 'Let's chat' button, plus a 'Spots available' badge.

Three site, different goals

A services business I'd redesigned, so I knew its issues (book an appointment), an online store (buy), and a small maker business (get a quote).

Three inputs per page

Screenshots at each width, the page text, and quick checks run inside the page: headings, labels, link targets and button sizes.

A review sheet

I mark every finding against its screenshot, so the score comes from my judgement, not AI's.

Results

What capture showed

It works, with limits: Mobile and tablet were clear. Desktop depended on the window size and full pages had to be captured one screen at a time. The working tool needs a proper capture library (Playwright was suggested).

Screenshots and page checks need each other: Pop-ups made headings look cut off when they weren't and text alone flagged a working embed as broken. Together, they caught both.

Speed needs its own tool: Load times from the browser weren't reliable, so performance will come from PageSpeed Insights.

Results

What capture showed

Broken links and buttons, missing key details, typos, accessibility gaps. The findings proved useful.

51

Findings scored

50

Right

1

Partly right

0

Wrong

12

Missed

What it missed told me more. Most fell into three groups:

Strategy: It looked at pages one at a time. It didn't step back and ask who the site is for, whether the structure suits them or whether what was listed as the core services made sense for the target audience. That was the heart of my own audit for the same site.

Depth and feel: Pages that are technically fine but thin, text-heavy or overwhelming next to good sites in the same category.

Key pages it never saw: Some issues were on important pages, like cart, search and a contact form, that weren't in the small set AI picked to capture.

It also didn't know about constraints: a booking system that couldn't deep link, a template that only allows a carousel, rules about showing reviews for health services. Several of its suggested fixes were right but not possible on the platform.

Learnings

Key insights

It's a strong first pass, not an audit

It covers the baseline across every page faster than I could, and it's accurate. The strategic layer is still mine, and that's the part clients pay for.

Context makes fixes useful

Knowing the platform, the template and any known constraints upfront turns a correct finding into a doable one.

Evidence has to match the finding

Two screenshots didn't clearly show what the finding described. If I can't see it, I can't verify it quickly.

Next steps

Revisions before the build

Ask for platform and known constraints when setting up the audit.

Capture every page, not a sample AI picks, plus key states like cart, search and forms.

Pin screenshots to the exact element each finding talks about.

Strategy as my layer: audiences, structure and direction sit above the findings, in my words.

Coming soon: Working tool

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