web-qa-bot
AI-powered web application QA automation using accessibility-tree based testing. Smoke tests, test suites, and PDF reports.
What this skill does
# 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: [email protected] }
- 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)
Related in Writing & Docs
jax-development
IncludedUse this skill when the user is writing, debugging, profiling, refactoring, reviewing, benchmarking, parallelising, exporting, or explaining JAX code, or when they mention JAX, jax.numpy, jit, grad, value_and_grad, vmap, scan, lax, random keys, pytrees, jax.Array, sharding, Mesh, PartitionSpec, NamedSharding, pmap, shard_map, Pallas, XLA, StableHLO, checkify, profiler, or the JAX repo. It helps turn NumPy or PyTorch-style code into pure functional JAX, fix tracer/control-flow/shape/PRNG bugs, remove recompiles and host-device syncs, choose transforms and sharding strategies, inspect jaxpr/lowering/IR, and benchmark compiled code correctly.
nature-article-writer
IncludedDrafts, rewrites, diagnostically critiques, and style-calibrates primary research manuscripts for Nature and Nature Portfolio journals. Use when the user wants a Nature-style title, summary paragraph or abstract, introduction, results, discussion, methods, figure legends, presubmission enquiry, cover letter, reviewer response, or when a scientific draft sounds generic, jargon-heavy, structurally weak, or AI-ish and needs precise, broad-reader-friendly prose without inventing data, analyses, or references. Best for primary research articles and letters rather than reviews or press releases unless explicitly adapting one.
deckrd
IncludedDocument-driven framework that derives requirements, specifications, implementation plans, and executable tasks from goals through structured AI dialogue. Use when user says "write requirements", "create spec", "plan implementation", "derive tasks", "structure this feature", "break down into tasks", or "document this module". Also use for reverse engineering existing code into docs (/deckrd rev). Do NOT use for direct code writing — use /deckrd-coder after tasks are generated. Do NOT use when the user only wants to run or fix existing code without planning.
clinical-decision-support
IncludedGenerate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
handling-sf-data
IncludedSalesforce data operations with 130-point scoring. Use this skill to create, update, delete, bulk import/export, generate test data, and clean up org records using sf CLI and anonymous Apex. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, needs data factory patterns for Apex tests, or needs to seed/clean records in a Salesforce org. DO NOT TRIGGER when: SOQL query writing only (use querying-soql), Apex test execution (use running-apex-tests), or metadata deployment (use deploying-metadata).
accelint-ac-to-playwright
IncludedConvert and validate acceptance criteria for Playwright test automation. Use when user asks to (1) review/evaluate/check if AC are ready for automation, (2) assess if AC can be converted as-is, (3) validate AC quality for Playwright, (4) turn AC into tests, (5) generate tests from acceptance criteria, (6) convert .md bullets or .feature Gherkin files to Playwright specs, (7) create test automation from requirements. Handles both bullet-style markdown and Gherkin syntax with JSON test plan generation and validation.