---
name: web-qa-bot
description: AI-powered web application QA automation using accessibility-tree based testing. Smoke tests, test suites, and PDF reports.
version: 0.1.0
---
# web-qa-bot
AI-powered web application QA automation using accessibility-tree based testing.
## Overview
This skill provides tools for automated QA testing of web applications. It uses browser accessibility trees for reliable element detection instead of fragile CSS selectors.
## Installation
```bash
npm install -g web-qa-bot agent-browser
agent-browser install
```
## Commands
### Quick Smoke Test
```bash
web-qa-bot smoke https://example.com
```
Runs basic health checks:
- Page loads successfully
- No console errors
- Navigation elements present
- Images have alt text
### Run Test Suite
```bash
web-qa-bot run ./tests/suite.yaml --output report.md
```
### Generate PDF Report
```bash
web-qa-bot report ./results.json -o report.pdf -f pdf
```
## Use Cases
### 1. Quick Site Health Check
```bash
# Smoke test a production URL
web-qa-bot smoke https://app.example.com --checks pageLoad,consoleErrors,navigation
```
### 2. Pre-deployment QA
Create a test suite and run before each deployment:
```yaml
# tests/critical-paths.yaml
name: Critical Paths
baseUrl: https://staging.example.com
tests:
- name: Login flow
steps:
- goto: /login
- type: { ref: Email, text: test@example.com }
- type: { ref: Password, text: testpass }
- click: Sign In
- expectVisible: Dashboard
- expectNoErrors: true
```
```bash
web-qa-bot run ./tests/critical-paths.yaml --output qa-report.pdf -f pdf
```
### 3. Monitor for Regressions
```bash
# Run tests and fail CI if issues found
web-qa-bot run ./tests/smoke.yaml || exit 1
```
### 4. Programmatic Testing
```typescript
import { QABot } from 'web-qa-bot'
const qa = new QABot({
baseUrl: 'https://example.com',
headless: true
})
await qa.goto('/')
await qa.click('Get Started')
await qa.snapshot()
qa.expectVisible('Sign Up')
await qa.close()
```
## Integration with agent-browser
This tool wraps agent-browser CLI for browser automation:
```bash
# Connect to existing browser session
web-qa-bot smoke https://example.com --cdp 18800
# Run headed for debugging
web-qa-bot run ./tests/suite.yaml --no-headless
```
## Test Results Format
Results are returned as structured JSON:
```json
{
"name": "Smoke Test",
"url": "https://example.com",
"summary": {
"total": 4,
"passed": 3,
"failed": 0,
"warnings": 1
},
"tests": [
{
"name": "Page Load",
"status": "pass",
"duration": 1234
}
]
}
```
## Tips
1. **Use role-based selectors** - More reliable than CSS classes
2. **Check console errors** - Often reveals hidden issues
3. **Test both navigation methods** - Direct URL and in-app routing
4. **Screenshot on failure** - Automatic in test suites
5. **Monitor for modals** - Can block interactions
## Report Formats
- **Markdown** - Default, human-readable
- **PDF** - Professional reports via ai-pdf-builder
- **JSON** - Machine-readable for CI/CD
## Troubleshooting
### "agent-browser not found"
```bash
npm install -g agent-browser
agent-browser install
```
### "Element not found"
Take a snapshot first to see available refs:
```bash
agent-browser snapshot
```
### "Timeout waiting for element"
Increase timeout or check if element is behind a loading state:
```yaml
steps:
- waitMs: 2000
- waitFor: "Loading" # Wait for loading to appear
- waitFor: "Content" # Then wait for content
```
## Links
- [GitHub](https://github.com/NextFrontierBuilds/web-qa-bot)
- [npm](https://www.npmjs.com/package/web-qa-bot)AI advertising agents that automates ad campaigns across Google Ads, Meta Ads, LinkedIn Ads, and TikTok Ads. Creates campaigns, reads live performance data, researches keywords with real CPC data, optimizes budgets, and manages ads through natural language via the Adspirer MCP server. 103 tools across 4 ad platforms.
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