From power-platform
AI-powered visual QA testing that walks through an app in the browser, records every action with annotated captions (what was done, what should happen), captures screenshots/GIFs, and sends the evidence to Gemini for automated review. Catches UX misalignments, broken flows, missing states, and edge cases that traditional tests miss. Can use Agent Teams for parallel test coverage. Triggers on: "visual test", "visual qa", "test the app", "qa review", "check the ui", "record a test", "walk through the app", "e2e test", "end to end test", "catch edge cases", "gemini review", "screen test", "ux test", "visual regression".
How this skill is triggered — by the user, by Claude, or both
Slash command
/power-platform:visual-qaThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You perform visual quality assurance by walking through a web app in the browser,
You perform visual quality assurance by walking through a web app in the browser, recording every action with structured captions, and sending the evidence to Gemini for automated review. You catch what traditional unit/integration tests miss: misaligned layouts, confusing UX, broken visual states, and edge cases.
resources/caption-format.md.resources/edge-cases.md.flowchart LR
plan["<b>1. Plan the test run</b><br/>What to test<br/>and expect"]
walk["<b>2. Walk the app</b><br/>Click, type,<br/>scroll, wait"]
collect["<b>3. Collect evidence</b><br/>Screenshots,<br/>GIF, captions"]
gemini["<b>4. Send to Gemini</b><br/>AI reviews<br/>actual vs expected"]
plan --> walk --> collect --> gemini
classDef step fill:#0f766e,stroke:#5eead4,color:#ecfeff
class plan,walk,collect,gemini step
Before touching the browser, define the test plan:
Write the test plan as a caption script. Read resources/caption-format.md for the format.
Use Claude in Chrome tools to walk through the app:
1. Navigate to the app URL (mcp__claude-in-chrome__navigate)
2. Start GIF recording (mcp__claude-in-chrome__gif_creator: start_recording)
3. Take initial screenshot (mcp__claude-in-chrome__computer: screenshot)
4. For each test step:
a. Log the caption (ACTION, INTENT, EXPECT)
b. Take a "before" screenshot
c. Perform the action (click, type, scroll)
d. Wait for the page to settle
e. Take an "after" screenshot
f. Note any discrepancies from expected behavior
5. Stop GIF recording (mcp__claude-in-chrome__gif_creator: stop_recording)
6. Export GIF (mcp__claude-in-chrome__gif_creator: export)
After the happy path, run through the edge case checklist in resources/edge-cases.md.
For each applicable edge case:
Gather all evidence into a structured report:
If the user has a Gemini API key, send the evidence for AI review.
Read resources/gemini-review.md for the integration approach.
Gemini analyzes:
Present findings in this format:
## Visual QA Report — [App Name]
Date: [date]
Flows Tested: [count]
Edge Cases Checked: [count]
### Results Summary
PASS: [count] FAIL: [count] PARTIAL: [count]
### Findings
FINDING #1 [SEVERITY: Critical]
STEP: [which step in the flow]
EXPECTED: [what should have happened]
ACTUAL: [what actually happened]
SCREENSHOT: [reference to screenshot]
RECOMMENDATION: [how to fix]
For large apps, spawn a team for parallel test coverage:
| Role | Agent Name | Tests |
|---|---|---|
| Happy Path Tester | happy-path | Core user flows, CRUD operations |
| Edge Case Hunter | edge-hunter | Empty states, long text, permissions, error handling |
| Visual Inspector | visual-inspector | Layout, alignment, responsive, accessibility |
Each agent walks the app independently and produces their own findings. The Lead merges results into a single report.
Read resources/team-testing.md for agent team test orchestration.
If the Chrome extension isn't available, the skill can still generate:
The user would then record their own screen and send the video + captions to Gemini.
npx claudepluginhub mcorbett51090/ravenclaude --plugin power-platformProvides behavioral guidelines to reduce common LLM coding mistakes, focusing on simplicity, surgical changes, assumption surfacing, and verifiable success criteria.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.