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.
npx agentmods add skills/microsoft/win-dev-skills/winui-ui-testingnpx skills add microsoft/win-dev-skills --skill winui-ui-testinggit clone --depth 1 https://github.com/microsoft/win-dev-skillsWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00122 | $0.06085 |
| Opus 5 | $0.00061 | $0.03043 |
| Sonnet 5 | $0.00024 | $0.01217 |
| Haiku 4.5 | $0.00012 | $0.00609 |
Grade A, and why
winui-ui-testing 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 369 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scope — any Windows app
winapp ui drives Windows UI Automation (UIA), the accessibility layer every Windows UI framework exposes, so the AutomationId-based approach in this skill works on any Windows desktop app: Win32, WPF, WinForms, and WinUI 3, packaged or unpackaged. The file-picker tests below already drive the OS's Win32 file dialog through the same verbs. For a non-WinUI app, use the same verbs and script template and skip the WinUI-specific gotchas (x:Bind LostFocus commit, ContentDialog selectors, MSIX relaunch).
Approach
The goal of this skill is to validate UI and app functionality automatically, without manual interaction, by exercising the app's UI elements, verifying their state, and asserting that the app behaves as expected under test conditions.
There are two main approaches:
- Interactive exploration — manually run the app, use
winapp ui <command>to explore the UI tree, find AutomationIds, verify element properties, and test functionality interactively. This is useful for discovery, but slow and expensive if repeated for every test iteration. - Scripted batch testing — generate a
ui-tests.ps1script that exercises all UI elements and asserts expected behavior in one pass. This allows you to run the tests automatically, capture results, and iterate quickly without manually interacting with the app each time.
Unless the user asked for interactive exploration, or you are unfamiliar with the code/app or need to explore the UI tree to discover AutomationIds for hidden or dynamically generated elements (flyouts, dialogs, lazy-loaded content), prefer scripted batch testing — it is faster, repeatable, and produces a record of pass/fail results that can be reviewed and acted on.
winapp ui Verbs
- Query:
status,list-windows,inspect,search,get-property,get-value,get-focused,wait-for - Interact:
invoke,click,set-value,focus,scroll,scroll-into-view - Advanced input:
send-keys(synthetic keyboard + accelerators),hover(tooltips/flyouts),drag(drag-drop, reorder, sliders),touch(tap/swipe/pinch/stretch),pen(stylus ink, pressure/tilt/eraser) - Capture:
screenshot,record(H.264 MP4 video)
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.
- 3d ago First seen · 369 lines · 122 tokens per session scan A 1b6164a6b6cd
winui-ui-testing is a skill published in the GitHub repository microsoft/win-dev-skills (406 stars, last pushed 6d ago), licensed MIT. It adds 122 tokens to every session and 6,085 once invoked, about $0.0006 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.
Other skills, from other repositories
playwright-testing
Generer og kjør Playwright E2E-tester for webapplikasjoner med page objects, auth fixtures og tilgjengelighetstester.
technical-design-doc-creator
Creates comprehensive Technical Design Documents (TDD) with mandatory and optional sections through interactive discovery. Use when user asks to "write a design doc", "create a TDD", "technical spec", "architecture document", "RFC", "design proposal", or needs to document a technical decision before implementation. Do…
spec-driven-eval
Scores how completely an implementation fulfills a PRD/spec, case by case, and produces a single comparable final grade. Invoke only when explicitly named (e.g. run spec-driven-eval); do not auto-trigger. Use when benchmarking spec-driven implementations, grading acceptance criteria, evaluating whether a feature was…
content-to-pipeline
When the user wants to turn content into revenue, build a content-led GTM motion, reverse engineer distribution, or repurpose content across platforms. Also use when the user mentions 'content marketing,' 'content-led growth,' 'content to pipeline,' 'distribution,' 'content repurposing,' 'content strategy,' 'thought…
domain-identification-grouping
Groups existing components into logical business domains to plan service-based architecture. Use when asking "which components belong together?", "group these into services", "organize by domain", "component-to-domain mapping", or planning service extraction from an existing codebase. Do NOT use for identifying new…
frontend-blueprint
AI frontend specialist and design consultant that guides users through a structured discovery process before generating any code. Collects visual references, design tokens, typography, icons, layout preferences, and brand guidelines to ensure the final output matches the user's vision with high fidelity. Use when the…