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Verifying Ui

Community
Innei
verifying-ui

Use when work changes what your human partner sees in a running app — a spec with UI has just been built, or a visible bug (layout, style, wrong state on screen) is about to be fixed — and before telling them it is done or ready

Overview

PublisherInnei
Repositoryryugi
Skill nameverifying-ui
Stars
321
Forks
14
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Innei on GitHub. Read the source before you install it.

Installation

Install the Verifying Ui AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Innei/ryugi/tree/main/skills/verifying-ui
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Innei/ryugi.git /tmp/ryugi
mkdir -p .claude/skills
cp -r /tmp/ryugi/skills/verifying-ui .claude/skills/verifying-ui
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Verifying Ui in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Verifying Ui on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Verifying Ui is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Verifying UI

Your human partner decides whether UI work is right, by looking at what the running app actually shows next to what they approved. Your own check — a browser measurement, a passing test, a glance at a screenshot, the project's own app-checking skill — is not the verdict. The work is done when every verify group on the page is passed.

REQUIRED BACKGROUND: ryugi:artifacts — its artboard.md covers image and video boards, verify groups and reading verdicts.

Work with no visible change skips this skill: logic already proven by tests, CLI or terminal output, a tweak your human partner watched you make live.

Before fixing a visible bug

Capture the broken state from the running app now, while you reproduce it. After the fix there is no honest "before".

The verify page

  1. Where. The artboard that holds the approved design gets a page verify (name "Verify"). No such artboard (a bug, work that skipped brainstorming, or a design approved on a claude.ai canvas): a new artboard verify-<topic>, with the canvas link in each group's sticky.
  2. One group per module or per bug, "verify": true, titled with the module or bug:
    • Built from a spec: the approved board (a board with the same file) on the left, a screenshot of the real app on the right. A module with interaction also gets a short recording of it. No approved board: the screenshot alone, titled with the spec's requirement.
    • A bug: before on the left, after on the right; add a recording when the bug is about behaviour.
  3. Evidence is real. Screenshots and recordings come from the running app, with whatever tool this environment has — a project skill that drives the app is a fine source. Never an HTML board standing in for "actual". Copy evidence under pages/verify/; keep each video under 8MB and the artboard under 20MB. Over 20MB the cloud copy stops updating: say so and shrink or drop the largest recordings.
  4. Set focus to the first group, check that warnings and pending are empty, give the link (the cloud link when there is one), say what each group shows, and ask them to tell you here when they have decided. End your turn; don't poll.

Running the checks

Before the first run, read how the project says to verify (its agent instructions, acceptance or verification docs) and follow its commands and output conventions over your own habits.

Each check has one output location. A retry or rerun writes over the previous result; never create numbered copies (-1, -2, -final) of the same check. Keep two runs side by side only when the point is comparing two builds, and name them for the builds. Delete scratch output you created once the evidence you need is copied to the verify page.

Prepare each recording

Add the original recording normally; Artifacts prepares Verify videos automatically. Replay the video on the Verify page: every action, loading or error state, and final result must remain visible. When original timing or narration is itself evidence (performance, timeouts), set "trim": false on that video board.

When verdicts come back

On their next message, run comment list and read groups.

  • pass: done for that group. Leave its files alone.
  • reject: read the reason and any pins on its boards, and fix it inside that group:
    • Behaviour or state (wrong content, a disabled control, a broken flow): under ryugi:test-driven-development.
    • Look only (layout, spacing, color, type): the rejected screenshot is the failing reproduction and the new screenshot is the check.
    • One commit per fix; exploratory work stays uncommitted, as ryugi:executing-specs says.
    • Replace the evidence (same file, or add a board to the group), reply on the reject thread with what changed and the commit, and leave the thread open.
    • The fix changes what a passed group shows: replace that group's evidence too — it goes back to pending — and say so in your reply.
  • pending: waiting on your human partner. Say so; don't call it done.

Your final message is "done" only when every verify group has passed. Until then it carries the link and what is waiting on whom.

A new round is for new work on the same page — a later spec, another bug — not for a reject. Put it below the last round with new groups. Passed groups of earlier rounds drop "verify": true; groups that have not passed keep it.

Red Flags

ThoughtReality
"I measured it in the browser; it's aligned"Measurements show what you measured. Put the screenshots up.
"Tests pass, so the UI matches"Tests don't see font size, spacing or color. Compare against the approved board.
"Screenshots were scratch; delete them"They are the evidence. They go on the verify page.
"No project verify skill, so I verified it myself"This skill is the verification.
"The project's verify skill already checked it"It made evidence. Put it on the verify page; the verdict is theirs.
"They're in a hurry; I'll just say it's fixed"Before/after takes a minute and is what they show the room.
"I'll mock the result in HTML"A mockup isn't evidence. Capture the real app or say you can't.
"Pending means fine"Pending means nobody has looked.

Frequently asked questions

What does the Verifying Ui AI skill do?

Use when work changes what your human partner sees in a running app — a spec with UI has just been built, or a visible bug (layout, style, wrong state on screen) is about to be fixed — and before telling them it is done or ready

Why use Verifying Ui on TypingMind?

Because you install it once and use it with any model. Verifying Ui is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Verifying Ui in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Innei/ryugi/tree/main/skills/verifying-ui. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Verifying Ui?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Verifying Ui?

As many as you like. As long as a model supports skills, you can use Verifying Ui with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Verifying Ui AI skill free?

It is published on GitHub by Innei. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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