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Ui Testing

Community
RealTask
ui-testing

Build practical UI verification plans for interactions, responsive layouts, accessibility, visual regression, and real-world edge cases.

Overview

PublisherRealTask
RepositoryMAX-DESIGN
Skill nameui-testing
Stars
4
Forks
0
Bundled files
Instructions only
LicenseMIT
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 RealTask on GitHub. Read the source before you install it.

Installation

Install the Ui Testing 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/RealTask/MAX-DESIGN/tree/main/skills/ui-testing
  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/RealTask/MAX-DESIGN.git /tmp/MAX-DESIGN
mkdir -p .claude/skills
cp -r /tmp/MAX-DESIGN/skills/ui-testing .claude/skills/ui-testing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ui Testing 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 Ui Testing 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 Ui Testing 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.

UI testing

When to use

Use when delivering a new interface, changing shared components or tokens, fixing UI bugs, reviewing a pull request, or deciding whether a screen is ready to ship.

Workflow

1. Define risk and acceptance criteria

Translate the user goal into observable outcomes. Prioritize the primary path, destructive or irreversible actions, authentication and permissions, data loss, accessibility barriers, high-traffic components, and common failure modes. Avoid trying to test every pixel equally.

2. Inspect available tools first

Read project scripts and existing test conventions. Prefer the project's current tools for unit, component, browser, accessibility, and screenshot tests. Do not add a dependency before confirming the need and the project's package policy.

3. Cover behavior, not only rendering

Test the primary user journey and the most valuable alternate paths. Check navigation, form validation, success and error feedback, disabled controls, menus and dialogs, keyboard input, loading interruption, empty data, and retry behavior. Use deterministic fixtures for tests; do not rely on unstable production data.

4. Cover responsive and content extremes

Use named target viewports based on actual support rather than arbitrary devices alone. Test narrow, medium, and wide layouts; text zoom where possible; long translations; long names; large numbers; missing images; empty lists; and dense tables. Look for overflow, overlap, hidden actions, clipped focus rings, and unexpected shifts.

5. Combine automated and manual methods

Use unit and integration tests for logic and state transitions, end-to-end tests for critical journeys, automated accessibility checks for detectable violations, and visual regression for meaningful visual changes. Manually inspect keyboard flow, reading order, focus behavior, copy clarity, and the rendered page when tools allow. Automated tests are evidence, not proof of usability or full accessibility conformance.

6. Keep visual tests stable

Control fonts, viewport, color scheme, data, animations, and timing where possible. Mask or stabilize genuinely dynamic content without hiding product defects. Review screenshot differences rather than blindly updating baselines. Prefer assertions about user-visible behavior to brittle selectors tied to incidental markup.

7. Report results with scope

Record command or tool, pass/fail result, relevant environment, and what was not tested. Separate source inspection from browser execution, automated accessibility scans from manual assistive-technology testing, and screenshot review from actual interaction testing.

Verification matrix

LayerUseful evidence
Static/buildlint, type check, build, token validation
Componentstates, validation logic, keyboard and event behavior
End-to-endcritical user journeys and error recovery
Accessibilityautomated scan plus manual keyboard and semantic review
Visualviewport screenshots, realistic content, reviewed diffs
Performancemeasured metrics or profiling when available

Quality gates

  • The highest-risk user journeys have explicit acceptance checks.
  • Critical success and failure paths are covered.
  • Responsive layout and realistic content extremes are checked.
  • Visual diffs are reviewed; baselines are not updated blindly.
  • Accessibility methods and remaining gaps are stated honestly.
  • Only checks actually run are reported as passed.

Frequently asked questions

What does the Ui Testing AI skill do?

Build practical UI verification plans for interactions, responsive layouts, accessibility, visual regression, and real-world edge cases.

Why use Ui Testing on TypingMind?

Because you install it once and use it with any model. Ui Testing 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 Ui Testing in TypingMind?

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

Which AI models can use Ui Testing?

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 Ui Testing?

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

Is the Ui Testing AI skill free?

Yes. It is published on GitHub by RealTask under the MIT license. 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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