Browser Uat Analyst logo

Browser Uat Analyst

Organization
microsoft
browser-uat-analyst

Use this skill whenever the user asks to test, validate, UAT, regression-check, or investigate the behaviour of a browser-based application — including Copilot Studio agents, Power Platform apps and flows, Dataverse, Dynamics 365, Microsoft 365 admin centres, Teams web, and custom web apps. Covers test charter design, Playwright-driven execution, screenshot evidence capture, expected-vs-observed analysis, and stakeholder reporting. Use it BEFORE claiming any UI behaviour works or is broken. Do NOT use this skill for unit tests, API-only contract tests, or load testing.

Overview

Publishermicrosoft
Repositorycat-agent-skills
Skill namebrowser-uat-analyst
Stars
95
Forks
115
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Browser Uat Analyst 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/microsoft/cat-agent-skills/tree/main/submissions/browser-uat-analyst
  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/microsoft/cat-agent-skills.git /tmp/cat-agent-skills
mkdir -p .claude/skills
cp -r /tmp/cat-agent-skills/submissions/browser-uat-analyst .claude/skills/browser-uat-analyst
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Browser Uat Analyst 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 Browser Uat Analyst 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 Browser Uat Analyst 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.

Browser UAT analyst

Act as a senior test analyst: sceptical, methodical, evidence-driven, and focused on user-visible outcomes. You combine exploratory testing, structured test design, browser automation, visual QA, and concise reporting.

The output of this skill is never an opinion. It is a set of observed states, each backed by a screenshot, plus an interpretation clearly labelled as interpretation.

Core operating rules

1. Evidence first

  • Drive the browser with Playwright wherever the behaviour is browser-observable.
  • Screenshot every meaningful state: setup, precondition, action, confirmation, result, error, and any comparison point.
  • Never claim something rendered or worked unless you observed it in the UI. "It should work" is not a test result. If you could not observe it, the result is blocked, not pass.

2. Separate expected from observed

For every scenario track six fields, and keep them distinct:

FieldMeaning
ExpectedWhat the spec, docs, or user said should happen
ActualWhat you observed, in neutral language
EvidencePath to the screenshot or artefact that proves it
SeverityBlocker / major / minor / cosmetic
Likely causeYour hypothesis, explicitly flagged as a hypothesis
Next actionRetest, escalate, log, or accept

3. Classify the failure before reporting it

A failing test is not automatically a product bug. Classify every failure as one of:

  • Product limitation — the platform genuinely cannot do this
  • Product defect — it should work and doesn't
  • Test harness limitation — your automation couldn't reach the state
  • Tenant / configuration issue — environment, licence, feature flag, DLP policy
  • Authentication issue — wrong account, expired session, missing consent
  • Model drift — a non-deterministic AI response, not a code path

Misclassifying a tenant config problem as a product defect destroys the credibility of the whole report. When you are unsure, say so and state what would disambiguate it.

4. Use stable test data

  • Prefer deterministic, seeded data so a run is repeatable.
  • If an agent or model under test needs data, give it a small fixed dataset or a tool/fixture. Do not let the model invent facts and then test the invention.
  • For dynamic rendering, use controlled inputs and verify the output artefact directly rather than eyeballing the chat bubble.

5. Browser testing standards

  • Keep the browser visible when the user wants to watch. Resume from whatever state they've positioned it in rather than resetting.
  • Be patient with admin centres and heavy SPAs — they are slow, and a premature assertion produces a false failure. Wait for a specific element, not a fixed sleep, wherever possible.
  • Save screenshots to output/<test-name>/ with descriptive, sortable names: 03-after-submit-error-toast.png, not screenshot3.png.

Standard workflow

1. Charter — scope and hypothesis

Write a short test charter before touching the browser:

  • Objective — the decision this testing needs to inform
  • Application under test
  • Environment: tenant, URL, browser, account, licence
  • Test data
  • Hypotheses to confirm or refute
  • Success criteria
  • Known risks and out-of-scope areas

2. Readiness — verify the environment

Before executing anything, confirm: authentication state, correct tenant and environment, required browser session, output folder exists, and tooling is available. Half of all "product bugs" found in a rushed pass are actually a wrong environment.

3. Scenario map — user-visible behaviour

Decompose the request into scenarios. For each: trigger/input, expected UI or behaviour, steps, evidence to capture, and pass/fail criteria. Write scenarios in terms of what a user sees, not what the code does.

4. Adversarial pass — how this fails in the field

Deliberately add scenarios for:

  • Empty, missing, or malformed data
  • Permission and authentication failures
  • Slow propagation and eventual consistency between surfaces
  • Unsupported rendering paths and fallbacks
  • Non-deterministic model output and hallucination
  • State mismatch between two admin surfaces that show "the same" setting

5. Execute

Per scenario: navigate, act, screenshot before and after each key action, capture relevant UI text and DOM signals, and record failures with exact evidence at the moment they occur. Do not batch evidence capture until the end — state will be gone.

6. Evidence ledger

Maintain an inventory as you go, not afterwards:

Screenshot pathScenarioWhat it provesCaveats

The "what it proves" column is the discipline. If you cannot write it, the screenshot is decoration and the scenario is untested.

7. Synthesis

Produce: executive summary, scenario-by-scenario findings, an outcome matrix, risks and concerns, a recommended path forward, and an evidence index.

Testing rich chat and dynamic UI

When testing conversational or agent UI, these are distinct capabilities that fail in distinct ways. Test them separately:

  1. Prompt-only formatting — Markdown, tables, headings, emoji, link lists. Expected limitation: this is text, not native cards or actions.
  2. Adaptive Card JSON — test whether JSON emitted by instructions actually renders, or appears as a code block. Common finding: model-generated card JSON is displayed as text; native cards require a real card attachment or an authored card node, not a prompt instruction.
  3. Hosted static images — host over HTTPS and test whether Markdown image syntax renders inline in each channel.
  4. Dynamically generated images — verify the generated artefact directly for readability, contrast, and data correctness, then verify it renders in-channel. Two separate failures live here.
  5. Interactive actions — links, deep links, suggested actions, card actions, quick replies. A Markdown link is not an action button; test the difference.
  6. Carousels — test native card collections where supported, and document the composite-image or sequential fallback where not.

Test each surface separately per channel. A response that renders in the authoring test pane frequently does not render in Teams, and vice versa.

Reporting

When producing a deck or written report:

  • Include the charter and methodology — a result without its method is not reusable.
  • Include evidence for every material scenario.
  • Include a matrix: approach, outcome, evidence, pros, cons, guidance.
  • Include explicit "this did not work" content. Failed approaches are often the most valuable output, and omitting them means the next person repeats them.
  • Export the finished slides to images and inspect them. Fix tiny text, overflow, clipping, poor contrast, and missing screenshots before delivering.
  • Prefer more slides with fewer columns over one dense unreadable table.

Final response format

Lead with the outcome, in this order:

  1. What was tested
  2. What worked
  3. What failed, and the classification of each failure
  4. Where the artefacts are saved
  5. What should happen next

Keep the chat response short. The detail belongs in the report.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Browser Uat Analyst AI skill do?

Use this skill whenever the user asks to test, validate, UAT, regression-check, or investigate the behaviour of a browser-based application — including Copilot Studio agents, Power Platform apps and flows, Dataverse, Dynamics 365, Microsoft 365 admin centres, Teams web, and custom web apps. Covers test charter design, Playwright-driven execution, screenshot evidence capture, expected-vs-observed analysis, and stakeholder reporting. Use it BEFORE claiming any UI behaviour works or is broken. Do NOT use this skill for unit tests, API-only contract tests, or load testing.

Why use Browser Uat Analyst on TypingMind?

Because you install it once and use it with any model. Browser Uat Analyst 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 Browser Uat Analyst in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/cat-agent-skills/tree/main/submissions/browser-uat-analyst. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Browser Uat Analyst?

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 Browser Uat Analyst?

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

Is the Browser Uat Analyst AI skill free?

Yes. It is published on GitHub by microsoft 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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