Install
$ agentstack add skill-billy-enrizky-openbrowser-ai-e2e-testing Open-source listing, not yet scanned by AgentStack. Follow the source repository for install instructions.
Security review
⚠ Flagged1 finding(s); flagged for manual review. · v0.1.0 How review works →
- • Prompt-injection patterns
- • Secret / credential exfiltration
- • Dangerous shell & filesystem operations
- • Untrusted network calls
- • Known-malicious package signatures
- high Pipes remote content directly into a shell (remote code execution).
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
End-to-End Testing
Simulate real user interactions and verify web application behavior using Python code execution. Covers navigation, form interaction, content assertions, and multi-page flows.
All code runs via openbrowser-ai -c. The daemon starts automatically and persists variables across calls. All browser functions are async -- use await.
The CLI daemon also persists cookies and login state in ~/.config/openbrowser/profiles/daemon/storage_state.json, so authenticated sessions can be reused across later runs.
Setup
Before running, verify openbrowser-ai is installed:
openbrowser-ai --help
If not found, install:
# macOS/Linux
curl -fsSL https://raw.githubusercontent.com/billy-enrizky/openbrowser-ai/main/install.sh | sh
# Windows (PowerShell)
irm https://raw.githubusercontent.com/billy-enrizky/openbrowser-ai/main/install.ps1 | iex
Workflow
Step 1 -- Navigate and verify page load
openbrowser-ai -c - type={etype} placeholder=\"{placeholder}\"")
# Fill and submit
await input_text(index=3, text="test@example.com")
await input_text(index=4, text="test-password")
await click(index=5) # Login button
await wait(2)
# Assert logged in
state = await browser.get_browser_state_summary()
assert "dashboard" in state.url.lower() or "welcome" in state.title.lower(), \
f"Login may have failed. URL: {state.url}, Title: {state.title}"
print("Login test passed")
EOF
Step 4 -- Test navigation flows
openbrowser-ai -c - e.textContent.trim());
})()
""")
assert len(errors) > 0, "Expected validation errors but found none"
print(f"Validation errors shown: {errors}")
# Assert page did not navigate
path = await evaluate("window.location.pathname")
print(f"Still on: {path}")
EOF
Step 6 -- Test responsive behavior
openbrowser-ai -c - 0, "detail": f"{cart_count} items"})
# Print results
import json
passed = sum(1 for t in test_results if t["passed"])
total = len(test_results)
print(f"\nResults: {passed}/{total} passed")
print(json.dumps(test_results, indent=2))
EOF
Tips
- Code is piped via stdin using heredoc (`-c - /dev/null 2>&1 || true' EXIT
... openbrowser-ai -c calls here ...
Do not rely on the idle timeout. Do not call `done()` as a substitute, `done()` only marks the task complete inside the agent loop, it does not close the browser.
## Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- **Author:** [billy-enrizky](https://github.com/billy-enrizky)
- **Source:** [billy-enrizky/openbrowser-ai](https://github.com/billy-enrizky/openbrowser-ai)
- **License:** MIT
- **Homepage:** https://docs.openbrowser.me/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.