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Use when translating natural language eval instructions into playwright-cli commands during AI agent evaluation — clicking, typing, waiting, scrolling, screenshot capture
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Interact with Langfuse and access its documentation. Use when needing to (1) query or modify Langfuse data programmatically via the CLI — traces, prompts, datasets, scores, sessions, and any other API resource, (2) look up Langfuse documentation, concepts, integration guides, or SDK usage, or (3) understand how any Langfuse feature works. This skill covers CLI-based API access (via npx) and multiple documentation retrieval methods.
Use when generating HTML evaluation reports for AI agent test suites — self-contained HTML with embedded screenshots, pass/fail results grouped by functional and compliance
Use when probing AI agents — reads eval config YAML, orchestrates browser interaction, verification, and report generation for web-based AI agent evaluation
Use when verifying AI agent responses during evaluation — content matching, behavioral assertions, AI-judged quality, and compliance checks with optional multi-step verification flows
Basierend auf der SOC-Berufsklassifikation
| name | agent-eval-browser-interact |
| description | Use when translating natural language eval instructions into playwright-cli commands during AI agent evaluation — clicking, typing, waiting, scrolling, screenshot capture |
Translates natural language instructions into playwright-cli commands. Built on top of the playwright-cli skill — uses snapshots to find element refs, then acts on them.
For every natural language instruction:
playwright-cli snapshot — get current page state with element refse15)playwright-cli commandplaywright-cli screenshot --filename=<path> — capture result| Natural Language | playwright-cli Command |
|---|---|
| "Click on X" / "Click the X button" | playwright-cli click <ref> |
| "Type 'text' in X" / "Enter 'text' in X" | playwright-cli fill <ref> "text" or playwright-cli type "text" |
| "Wait for the page to load" | playwright-cli run-code "async page => await page.waitForLoadState('networkidle')" |
| "Wait for X to appear" | playwright-cli snapshot and check for element, retry |
| "Wait for the agent to respond" | See below |
| "Scroll down" | playwright-cli run-code "async page => window.scrollBy(0, 500)" |
| "Press Enter" | playwright-cli press Enter |
| "Go to URL" | playwright-cli goto URL |
# Take snapshot to see all interactive elements
playwright-cli snapshot
# Output shows refs like:
# e1 [textbox "Email"]
# e2 [textbox "Password"]
# e3 [button "Sign In"]
# e4 [link "Forgot password?"]
# Now use the ref that matches the natural language target
# "Click on the Sign In button" → playwright-cli click e3
# "Type 'admin@test.com' in the email field" → playwright-cli fill e1 "admin@test.com"
If the target element isn't obvious from the snapshot, use:
# Get more detail on a specific element
playwright-cli eval "el => el.textContent" e5
# Or take a deeper snapshot
playwright-cli snapshot --depth=6
This is the trickiest action. Strategy:
# 1. Capture current page text length
playwright-cli --raw eval "document.body.innerText.length"
# 2. (send message action happens)
# 3. Poll for new content — use run-code to wait
playwright-cli run-code "async page => {
const before = await page.locator('body').innerText();
await page.waitForFunction(
prevLen => document.body.innerText.length > prevLen,
before.length,
{ timeout: 30000 }
);
await page.waitForTimeout(2000);
}"
Also check for loading indicators:
playwright-cli snapshot
# Look for spinners, "typing..." indicators, loading states
# Wait until they disappear
After every action:
playwright-cli screenshot --filename=screenshots/step-01-click.png
If a command fails:
playwright-cli screenshot --filename=screenshots/step-N-error.pngplaywright-cli snapshot