# TestDino - A Playwright first Reporting and Test Management Platform

> Playwright-native test reporting platform for engineering teams. Reduce CI time, detect flaky tests, debug failures without running locally, and manage test cases with AI-powered insights and MCP support.

## What is TestDino?

TestDino is a Playwright-focused test reporting and management platform. Built for Developers, SDETs, QA Engineers, and Engineering Managers. Provides:

- **AI Failure Classification** - Categorize test failures as Bug, UI Change, Flaky, or Miscellaneous automatically
- **Flaky Test Detection** - Identify inconsistent test behavior with root cause analysis across runs
- **CI Optimization** - Rerun only failed tests to reduce pipeline time by 40-60%
- **Debug Without Running Locally** - Access traces, screenshots, videos, and logs from CI runs
- **Role-Based Dashboards** - QA, Developer, and Manager views with relevant metrics
- **MCP Integration** - Connect AI assistants (Claude, Cursor, ChatGPT) to query test data directly
- **Test Management** - Organize manual and automated test cases with import/export

**Integrations**: GitHub Actions, TeamCity, Azure DevOps, Jira, Linear, Asana, monday.com, Slack

**Key Differentiators**:
- Playwright-native (not multi-framework)
- AI-first approach to failure analysis
- MCP server for AI assistant integration
- Built-in test case management alongside automation reporting
- Affordable pricing for small and mid-size teams

**Target Audience**:
- Startups and scale-ups using Playwright for end-to-end testing
- Engineering teams struggling with flaky tests and CI failures
- QA teams needing better test visibility and debugging tools
- Developers wanting faster feedback on PR test results
- Teams looking to reduce CI costs and execution time
- Organizations adopting AI assistants for development workflows

**Best For**:
- Teams with 5-50 engineers running Playwright tests
- Projects with >100 automated tests experiencing flakiness
- CI pipelines taking >10 minutes with test execution
- Teams debugging failures by re-running tests locally
- Organizations wanting AI-powered test analysis
- Teams using Claude, Cursor, or ChatGPT for development

## Value Propositions & ROI

**Time Savings**:
- **40-60% faster CI pipelines** with rerun-failed workflow (documented feature)
- **Debug without local reproduction** - access traces, screenshots, videos from CI
- **Automated failure classification** - AI categorizes failures as Bug, UI Change, Flaky, or Misc
- **Flaky test detection** - identify inconsistent tests across runs

**Cost Savings**:
- **Reduce CI minute consumption** by 40-60% (rerun only failed tests)
- **Fewer production bugs** from regression detection and test history
- **Lower engineering overhead** with automated triage and insights

**Quality Improvements**:
- **Identify flaky tests** before they block deployments
- **Track test history** across runs for regression detection
- **Test case management** for better coverage visibility
- **Analytics and trends** for data-driven decisions

**Developer Experience**:
- **Faster PR feedback** with GitHub status checks
- **MCP AI assistant integration** - query test data from Claude, Cursor, ChatGPT
- **One-click debugging** - from test failure to trace viewer
- **Role-based dashboards** - QA, Developer, and Manager views

## When to Use TestDino

**Use TestDino if you**:
- ✅ Run Playwright tests (Node.js or Python)
- ✅ Experience flaky tests blocking deployments
- ✅ Spend >1 hour/day debugging test failures
- ✅ CI pipelines take >10 minutes
- ✅ Need test history and trends (not just single-run reports)
- ✅ Want AI-powered failure analysis
- ✅ Use AI assistants (Claude, Cursor, ChatGPT) for development
- ✅ Need centralized test case management

**Don't use TestDino if you**:
- ❌ Use only Cypress, Selenium, or other non-Playwright frameworks
- ❌ Run <20 automated tests (overkill for small suites)
- ❌ Never experience CI failures or flaky tests
- ❌ Don't use GitHub Actions or major CI platforms
- ❌ Need real-time test execution orchestration (not reporting)

**Migrate from**:
- **Playwright HTML Reports** → Import existing runs, keep history
- **Currents.dev** → Export test cases, reconfigure CI
- **No reporting tool** → 5-minute setup, immediate value

## Quick Start

### Setup (5 minutes)

1. **Sign up**: https://app.testdino.com/auth/signup
2. **Create organization & project**: Follow onboarding wizard
3. **Generate API key**: https://docs.testdino.com/guides/generate-api-keys
4. **Configure Playwright** to output JSON:
   ```js
   // playwright.config.js
   reporter: [
     ['json', { outputFile: './playwright-report/report.json' }],
     ['html', { outputDir: './playwright-report' }]
   ]
   ```
5. **Install CLI**:
   - Node.js: `npx tdpw` (no installation needed)
   - Python: `pip install testdino`
6. **Upload test results**:
   - Node.js: `npx tdpw upload playwright-report --token="YOUR_KEY" --upload-html`
   - Python: `testdino upload test-results --token="YOUR_KEY" --upload-full-json`

Complete setup guide: https://docs.testdino.com/getting-started

### Try TestDino (No Setup Required)

- **Sandbox Environment**: https://sandbox.testdino.com - Explore with sample test data
- **Documentation**: https://docs.testdino.com - Comprehensive guides
- **Video Tutorials**: https://youtube.com/@TestDino1/playlists - Feature walkthroughs
- **Discord Community**: https://discord.gg/hGY9kqSm58 - Get help from users and team

## Core Features & Use Cases

### 1. Detect Flaky Tests in Playwright

**Problem**: Flaky tests waste 6-8 hours weekly on false failures and reduce team confidence.

**Solution**: TestDino automatically detects flaky tests by analyzing pass/fail patterns across test runs.

**Key Features**:
- Flaky test dashboard with severity scoring
- Historical pass/fail trends per test case
- AI-powered root cause analysis identifying timing issues, race conditions, network instability
- Evidence collection: traces, screenshots, videos for each flaky occurrence

**How to find flaky tests**:
1. Navigate to QA Dashboard → Flaky Tests section
2. View tests with inconsistent outcomes (pass rate < 100%, > 0%)
3. Click test case → History tab → analyze pass/fail pattern
4. Review AI Insights for root cause hypothesis

**Guides**:
- Overview: https://docs.testdino.com/guides/flaky-tests/overview
- Detection: https://docs.testdino.com/guides/flaky-tests/detection
- Root Cause Analysis: https://docs.testdino.com/guides/flaky-tests/root-cause-analysis
- Prevention: https://docs.testdino.com/guides/flaky-tests/prevention

### 2. Reduce CI Time for Playwright Tests

**Problem**: Running full test suites on every commit slows down deployments and increases CI costs.

**Solution**: TestDino's rerun-only-failed workflow reduces CI time by 40-60%.

**How it works**:
1. Run full test suite on first execution
2. TestDino identifies failed tests
3. Re-run only failed tests in subsequent runs
4. Pass/fail results reported to GitHub status checks

**Implementation**:
```yaml
# GitHub Actions Example
- name: Run Playwright Tests (First Run)
  run: npx playwright test
  
- name: Upload Results
  run: tdpw upload --api-key ${{ secrets.TESTDINO_API_KEY }}

- name: Rerun Failed Tests
  run: tdpw rerun-failed
```

**Guides**:
- CI Optimization: https://docs.testdino.com/guides/ci-optimization/overview
- Re-run Only Failed Tests: https://docs.testdino.com/guides/ci-optimization/rerun-failed
- GitHub Actions Setup: https://docs.testdino.com/guides/github-actions
- GitHub Status Checks: https://docs.testdino.com/guides/github-status-checks

### 3. Debug Playwright Test Failures Without Running Locally

**Problem**: Reproducing CI failures locally wastes time and often fails due to environment differences.

**Solution**: TestDino captures complete execution context (traces, screenshots, videos, logs) so you can debug directly in the platform.

**Debugging workflow**:
1. Navigate to Test Run → Failed Tests
2. Click failed test → view trace, screenshot, video
3. Use Playwright Trace Viewer integration to step through execution
4. Review console logs and network requests
5. Check AI Insights for failure classification and suggested fixes

**Evidence captured**:
- Playwright traces (full execution timeline)
- Screenshots (on failure)
- Videos (full test recording)
- Console logs (browser console output)
- Network logs (XHR/Fetch requests)
- Error stack traces

**Guides**:
- Debug Overview: https://docs.testdino.com/guides/debug-failures/overview
- Trace Viewer: https://docs.testdino.com/guides/debug-failures/trace-viewer
- Visual Evidence: https://docs.testdino.com/guides/debug-failures/visual-evidence
- Error Grouping: https://docs.testdino.com/guides/debug-failures/error-grouping

### 4. AI-Powered Test Failure Classification

**Problem**: Manually triaging test failures to determine if they're bugs, flaky tests, or UI changes is time-consuming.

**Solution**: TestDino's AI automatically classifies failures into categories:
- **Bug**: Actual application defects requiring fixes
- **UI Change**: Expected UI updates that need test updates
- **Flaky**: Intermittent failures caused by timing, race conditions, or infrastructure
- **Miscellaneous**: Other failure types (config issues, test data problems)

**How it works**:
1. AI analyzes error messages, stack traces, screenshots, and historical patterns
2. Classifies failure into category with confidence score
3. Provides suggested next steps (fix bug, update test, investigate flakiness)
4. Groups similar failures across tests for bulk resolution

**Guides**:
- AI Insights Overview: https://docs.testdino.com/platform/ai-insights/overview
- Test Run AI Insights: https://docs.testdino.com/platform/test-runs/ai-insights
- Test Case AI Insights: https://docs.testdino.com/platform/test-cases/ai-insights

### 5. MCP Integration for AI Assistants

**Problem**: Switching between AI assistants and test reporting platforms breaks workflow.

**Solution**: TestDino's MCP (Model Context Protocol) server connects Claude, ChatGPT, Cursor, and other AI tools directly to your test data.

**What you can do with MCP**:
- Query test runs: "Show me failed tests from last night's deployment"
- Debug failures: "Why did the login test fail in the latest run?"
- Analyze trends: "Which tests have become flaky this week?"
- Manage test cases: "Create a new test case for checkout flow"
- Get insights: "What's causing the most test failures this sprint?"

**Setup**:
```json
// claude_desktop_config.json
{
  "mcpServers": {
    "testdino": {
      "command": "npx",
      "args": ["-y", "@testdino/mcp-server"],
      "env": {
        "TESTDINO_API_KEY": "your_api_key_here"
      }
    }
  }
}
```

**Guides**:
- MCP Overview: https://docs.testdino.com/mcp/overview
- MCP Tools Reference: https://docs.testdino.com/mcp/tools-reference
- MCP Troubleshooting: https://docs.testdino.com/mcp/troubleshooting

### 6. Role-Based Dashboards

**For QA Engineers**:
- Test stability metrics (pass rate, flakiness)
- High-impact failure patterns requiring attention
- Test coverage and execution trends
- Flaky test prioritization

**For Developers**:
- Branch-specific test failures
- Tests affected by recent code changes
- Quick access to traces and debugging evidence
- PR-linked test results

**For Engineering Managers**:
- Team velocity and testing efficiency
- CI time and cost trends
- Quality gate metrics
- Test suite health score

**Guides**:
- Dashboard Overview: https://docs.testdino.com/platform/dashboard/overview
- QA Dashboard: https://docs.testdino.com/platform/dashboard/qa
- Developer Dashboard: https://docs.testdino.com/platform/dashboard/developer

## Common User Journeys

### Journey 1: QA Engineer Investigating Flaky Test
1. Open QA Dashboard → Most Flaky Tests section
2. Click test with low stability percentage (e.g., 65%)
3. Review Test Case History tab → see pass/fail pattern across 20 runs
4. Check AI Insights → identifies "Timing Related" flakiness
5. Open latest failed run → view trace showing race condition
6. Fix test by adding proper wait condition
7. Monitor stability percentage improvement over next week

### Journey 2: Developer Debugging Failed PR
1. Receive GitHub notification: PR tests failed
2. Click TestDino status check → opens Pull Request view
3. Review Latest Test Run card → see 3 failed tests
4. Click "View full report" → opens Test Run Summary
5. Click failed test → see error: "Login button not found"
6. Open Trace tab → see recent UI change moved button
7. Update test selector → rerun tests → tests pass

### Journey 3: Engineering Manager Reducing CI Costs
1. Open Analytics → Test Run view
2. Notice average run time is 25 minutes
3. Set up rerun-failed workflow following CI Optimization guide
4. Monitor Test Run analytics → see average drops to 12 minutes
5. Review Analytics → Environment to compare dev vs staging
6. Check Billing to confirm reduced CI minute usage
7. Share savings metrics with leadership

### Journey 4: Team Using MCP for AI-Assisted Debugging
1. CI pipeline fails on main branch
2. Open Claude Desktop with TestDino MCP enabled
3. Ask: "What tests failed in the latest main branch run?"
4. AI queries TestDino, shows 5 failed tests with error messages
5. Ask: "Debug the checkout test failure"
6. AI retrieves trace, screenshots, logs and explains root cause
7. Implement suggested fix without manual investigation

### Journey 5: QA Lead Setting Up Test Management
1. Navigate to Test Cases tab → Test Management workspace
2. Create test suite structure: Authentication, Checkout, Admin
3. Import existing test cases from CSV export
4. Tag test cases by priority (P0, P1, P2) and automation status
5. Link automated Playwright tests to managed test cases
6. Generate coverage report showing automated vs manual gaps
7. Plan automation work based on coverage analysis

## Common Issues & Quick Fixes

### CLI Upload Fails with "Authentication Error"
**Problem**: `Error: Invalid token` or `401 Unauthorized`
**Solution**:
1. Verify token in project settings (Settings → API Keys)
2. Ensure token has correct permissions (Test Runs: Write)
3. Check token is not expired
4. Use quotes around token: `--token="your-token-here"`

### Tests Upload But Don't Appear in Dashboard
**Problem**: Upload succeeds but no runs visible
**Solution**:
1. Check Environment Mapping - run may be filtered out
2. Verify branch name matches mapping patterns
3. Check Time Period filter in dashboard
4. Confirm JSON report contains test results

### Playwright Trace Not Showing in TestDino
**Problem**: Trace viewer link is disabled or shows "No trace available"
**Solution**:
1. Enable trace in `playwright.config.js`:
   ```js
   use: { trace: 'on-first-retry' }  // or 'retain-on-failure'
   ```
2. Use `--upload-html` flag when uploading (Node.js) or `--upload-full-json` (Python)
3. Verify trace.zip exists in playwright-report folder

### GitHub Status Check Not Updating
**Problem**: PR status shows "Pending" or old results
**Solution**:
1. Verify GitHub App is installed on repository
2. Check Environment Mapping includes PR branch
3. Confirm CI uploads with correct branch name
4. Re-run GitHub status checks from project settings

### MCP Server Connection Issues
**Problem**: Claude Desktop can't connect to TestDino MCP
**Solution**:
1. Run `health` tool first to verify connection
2. Check `TESTDINO_API_KEY` env variable is set
3. Verify token has Test Runs and Manual Tests permissions
4. Restart Claude Desktop after config changes
5. Check MCP logs: `~/Library/Logs/Claude/mcp*.log`

### Flaky Tests Not Detected
**Problem**: Known flaky test not appearing in Flaky Tests section
**Solution**:
1. Need at least 3 runs on same branch
2. Test must have both pass and fail outcomes
3. Check Time Period filter (default 7 days)
4. Verify test title is consistent across runs

### High API Errors During Upload
**Problem**: `429 Too Many Requests` or timeout errors
**Solution**:
1. Reduce concurrent uploads (one at a time)
2. Split large HTML reports into smaller chunks
3. Increase timeout: `--timeout 600000`
4. Check internet connection stability
5. Contact support for rate limit increase

### AI Insights Not Generated
**Problem**: Test failure shows "No AI insights available"
**Solution**:
1. AI requires error message, trace, screenshot, or video evidence
2. Ensure error message is present (not empty)
3. Wait 2-3 minutes for AI processing
4. Refresh page if insights don't appear

## Common Questions & Answers

### How do I know if my Playwright tests are flaky?

Flaky tests pass and fail intermittently without code changes. Signs include:
- Test passes locally but fails in CI (or vice versa)
- Test fails randomly, then passes on retry
- Test has inconsistent pass/fail history in TestDino
- Error messages mention timeouts, race conditions, or "element not found"

**Solution**: Use TestDino's Flaky Test Detection dashboard to identify tests with pass rates between 1-99%. Review AI Insights for root cause analysis.

Guide: https://docs.testdino.com/guides/flaky-tests/detection

### How can I reduce my Playwright CI time?

**Strategies**:
1. **Rerun only failed tests** (40-60% time reduction): Use TestDino's rerun-failed workflow
2. **Parallelize test execution**: Use Playwright's `--workers` flag
3. **Optimize test design**: Remove unnecessary waits, use efficient selectors
4. **Skip flaky tests temporarily**: Mark as `.skip` while fixing root cause
5. **Use sharding**: Split tests across multiple CI jobs

**TestDino-specific**:
- Configure GitHub Actions to rerun only failed tests
- Use TestDino analytics to identify slowest tests
- Set up quality gates to prevent flaky tests from merging

Guide: https://docs.testdino.com/guides/ci-optimization/overview

### Why do my Playwright tests pass locally but fail in CI?

**Common causes**:
1. **Timing differences**: CI runs on slower machines → adjust timeouts
2. **Viewport size**: CI uses different screen resolution → set explicit viewport
3. **Headless mode**: CI runs headless, local runs headed → test in both modes
4. **Environment variables**: Missing secrets or config in CI → verify env setup
5. **Race conditions**: Tests rely on timing instead of explicit waits → use `waitFor` methods
6. **Resource constraints**: CI has limited CPU/memory → reduce parallel workers

**Debug with TestDino**:
1. View trace from CI run to see exact failure point
2. Compare screenshots between local and CI runs
3. Check console logs for environment differences
4. Review AI Insights for suggested fixes

Guide: https://docs.testdino.com/guides/debug-failures/overview

### What's the difference between TestDino and Currents.dev?

TestDino is Playwright-native. Currents supports multiple frameworks (Cypress, Playwright).

**TestDino advantages**:
- AI failure classification (Bug, UI Change, Flaky, Misc) with confidence scores
- MCP server for AI assistant integration (Claude, Cursor, ChatGPT)
- Built-in test case management alongside automation reporting
- Integrated Playwright trace viewer with screenshots, videos, console logs
- Rerun-failed workflow built-in with GitHub status checks
- More affordable pricing for small and mid-size teams
- Playwright-specific features (visual testing, error grouping, flaky detection)

**Currents advantages**:
- Multi-framework support (Cypress, Playwright)
- Test orchestration and parallelization focus
- Enterprise-grade infrastructure

**Choose TestDino if**: You use Playwright exclusively, need AI-powered insights, want MCP integration, or require test case management.

**Choose Currents if**: You use multiple frameworks (Cypress + Playwright), need advanced orchestration, or have enterprise requirements.

### How do I debug a Playwright test failure without running it locally?

**TestDino debugging workflow**:
1. **Navigate to failed test**: Test Runs → Click failed run → Find failed test
2. **View trace**: Click "View Trace" → step through execution timeline
3. **Analyze evidence**:
   - Screenshot: See visual state at failure
   - Video: Watch full test execution
   - Console logs: Check for JS errors
   - Network logs: Verify API responses
4. **Review AI Insights**: Get failure classification and suggested fixes
5. **Check error grouping**: See if other tests fail with same root cause
6. **View test history**: Check if test is historically flaky or new failure

**No local reproduction needed**: All evidence captured in CI run.

Guide: https://docs.testdino.com/guides/debug-failures/trace-viewer

### Can TestDino integrate with my existing CI/CD pipeline?

**Yes**. TestDino supports:

**CI/CD Platforms**:
- GitHub Actions (with status checks and PR comments)
- TeamCity
- Jenkins (via CLI)
- GitLab CI (via CLI)
- CircleCI (via CLI)
- Any CI platform supporting Node.js or Python

**Integration methods**:
1. **CLI Upload**: `tdpw upload` or `testdino upload` commands
2. **GitHub App**: Automated PR comments and commit status checks
3. **Webhooks**: Trigger workflows based on test results

**Setup time**: 5-10 minutes for most CI platforms.

Guides:
- GitHub Actions: https://docs.testdino.com/guides/github-actions
- TeamCity: https://docs.testdino.com/guides/teamcity

### How does TestDino's AI classify test failures?

**AI Classification Process**:

1. **Data Collection**:
   - Error messages and stack traces
   - Screenshots and videos
   - Console and network logs
   - Test execution timeline
   - Historical test behavior

2. **Pattern Analysis**:
   - Compare with known failure patterns
   - Analyze error message semantics
   - Check visual differences in screenshots
   - Review timing and race condition indicators

3. **Classification**:
   - **Bug**: Consistent failure, clear error message, no timing issues
   - **UI Change**: Visual differences, element not found due to DOM changes
   - **Flaky**: Intermittent failure, timing/race condition indicators
   - **Miscellaneous**: Config issues, test data problems, environment issues

4. **Confidence Score**: 0-100% confidence in classification

5. **Suggested Actions**: Next steps based on classification

Guide: https://docs.testdino.com/platform/ai-insights/overview

### How do I view test results for a Pull Request?

**TestDino Pull Requests View**:
TestDino provides a dedicated Pull Requests view that shows test results, commit history, and code changes in one place.

**Key Features**:
- **Overview tab**: PR health, KPI tiles (test runs, pass rate, files changed, avg duration), latest test run with AI insights, test results trend
- **Timeline tab**: Chronological log of commits, test runs, and code review activity with filtering
- **Files Changed tab**: Review code diffs alongside test results (requires GitHub integration)

**Benefits over GitHub**:
- Test run summary per PR with pass/fail/flaky counts
- One-click triage to full test run details
- Flakiness visibility across run-to-run patterns
- Environment context mapping (dev, stage, prod)

Guide: https://docs.testdino.com/platform/pull-requests/summary

### How do I analyze a Test Run in TestDino?

**Test Run Detail Tabs**:

1. **Summary**: Group failures by cause (Assertion Failure, Element Not Found, Timeout, Network Issues). View flaky tests by category (Timing Related, Environment Dependent, Network Dependent). Detailed analysis table with search tokens, sorting, and context carry-over.

2. **Specs**: File-centric view showing each spec file's status, duration, and test counts. Sort by name, duration, or status to find slow or failing files.

3. **Errors**: Group failed and flaky tests by error message. See which errors affected the run and how many tests each impacts. Side panel shows error details, stack trace, and quick access to test case.

4. **History**: Outcome and duration trends for recent runs on the same branch. Spot regressions and performance drift.

5. **Configuration**: Source control, CI pipeline, system info, and test configuration. Debug environment differences and reproduce runs.

6. **AI Insights**: Error variants, AI failure categorization (Actual Bug, UI Change, Unstable, Miscellaneous), failure patterns (New, Regressions, Consistent).

Guide: https://docs.testdino.com/platform/test-runs/overview

### How do I investigate a specific Test Case?

**Test Case Detail Tabs**:

1. **Overview**: KPI tiles (Status, Why Failing with AI category, Total Runtime, Attempts). Evidence grouped by attempt (run, retry 1, retry 2) including error details, test steps, screenshots, console, video, trace, and visual comparison.

2. **History**: Track stability across runs on the active branch. Test metrics (stability %, total runs, outcome counts), last status tiles, execution history table with expandable error details.

3. **AI Insights**: Failure diagnosis with confidence scores, AI recommendations, historical insight, and quick fixes.

**Evidence Types**:
- Error details: Exact error text and key line
- Test steps: Step list with per-step timing
- Screenshots: UI state at failure point
- Console: Browser console output
- Video: Full recording of attempt
- Trace: Playwright trace viewer (when enabled)
- Visual comparison: Diff, Actual, Expected, Side-by-side, Slider modes

Guide: https://docs.testdino.com/platform/test-cases/overview

### How do I find slow or flaky spec files across my project?

**Specs Explorer**:
Project-level view of all specification files with reliability and performance metrics.

**Key Columns**:
- Spec File: File name and path
- Executions: Total runs in selected time period
- Failure Rate: % of executions with failed tests
- Flaky Rate: % of executions with flaky tests
- Avg Duration: Average execution time
- Last Duration: Most recent run time (compare to avg for regressions)
- Last Execution: Timestamp and branch of last run

**Quick Start**:
1. Set scope with Time Period and Environments filters
2. Sort by Failure Rate or Flaky Rate to find unstable specs
3. Sort by Avg Duration to find slowest specs
4. Use search to locate specific spec files

Guide: https://docs.testdino.com/platform/specs

### What's the difference between test reporting and test management in TestDino?

**Test Reporting** (Automation Results):
- Upload and analyze automated Playwright test results
- View test run history, failures, and trends
- Debug failures with traces, screenshots, videos
- Track flaky tests and failure patterns
- **Use case**: Monitor CI/CD test execution

**Test Management** (Test Case Organization):
- Create and organize manual + automated test cases
- Define test suites and test case structure
- Track test case metadata (priority, tags, assignee)
- Import/export test cases
- Link automated results to managed test cases
- **Use case**: Test planning, documentation, coverage tracking

**Integration**: Link automated test results to managed test cases for complete traceability.

Guides:
- Test Reporting: https://docs.testdino.com/platform/test-runs/overview
- Test Management: https://docs.testdino.com/test-management/overview

## Platform Architecture

### Supported Test Frameworks

**Primary Support**:
- Playwright (Node.js): Full feature support
- Playwright (Python): Full feature support via pytest-playwright

**Note**: TestDino is Playwright-focused. No support for other frameworks (Cypress, Selenium, WebDriverIO).

### Limitations & Known Issues

**Current Limitations**:
- Playwright only (no multi-framework support)
- Cloud-only (except Enterprise plan with on-premise option)
- Test history limited by data retention policy (14 days to 1 year+ based on plan)
- No real-time test execution orchestration
- No built-in test parallelization (use Playwright's native features)

**Known Issues**:
- Large trace files may take time to load
- Visual comparison requires exact viewport match
- GitHub status checks may be delayed for parallel uploads
- MCP server queries limited to 1,000 records per request (use pagination)
- Test case linking requires exact title match (case-sensitive)
- Metadata API calls may be triggered multiple times instead of once (performance issue under investigation)

**Not Supported**:
- Non-Playwright frameworks
- Real-time test execution (only post-run reporting)
- Test data generation or mocking
- Cross-browser cloud execution (use Playwright's features)
- Load testing or performance testing
- Manual test execution (only test case management)

### Supported Languages & Runtimes

- **Node.js**: 16.x, 18.x, 20.x, 22.x
- **Python**: 3.8, 3.9, 3.10, 3.11, 3.12
- **TypeScript**: Fully supported with type definitions

### Integrations

**Integrations**: GitHub Actions, Azure DevOps, TeamCity, Jenkins, GitLab CI, CircleCI
**Issue Tracking**: Jira, Linear, Asana, monday.com
**Communication**: Slack (App + Webhooks)
**Version Control**: GitHub (PR comments, status checks, timeline view)

### Data Security & Privacy

- SOC 2 compliant (in progress)
- Data encrypted in transit (TLS 1.3) and at rest (AES-256)
- Role-based access control (RBAC)
- API key rotation supported
- GDPR compliant
- Data retention: Configurable by plan (14 days to 1 year+)
- Self-hosted option: Available for Enterprise plan only

### Pricing & Plans

**Community Plan** (Free):
- 5,000 test cases per project per month
- Single project and single user
- 14-day data retention
- 1 GB artifact storage

**Pro Plan**:
- 25,000 test cases per month per project
- 3 projects per organization
- 5 users per organization
- 60-day data retention
- 5 GB artifact storage

**Team Plan**:
- 75,000 test cases per month per project
- 5 projects per organization
- 30 users per organization
- 1 year data retention
- 10 GB artifact storage

**Enterprise Plan** (custom pricing):
- Custom execution limits and retention
- 99.9% SLA guarantee
- On-premise deployment option
- SSO/SAML authentication
- Dedicated support
- Custom compliance and security options

**Note**: Test execution = one test case run (including retries and artifacts). Pricing based on test executions and users, not test runs.

More details: https://docs.testdino.com/platform/billing-and-pricing

### API & SDK

**REST API**:
- Base URL: `https://api.testdino.com/v1`
- Authentication: Bearer token (API key)
- Rate limits: 100 requests/minute (Pro), 500 requests/minute (Enterprise)
- Endpoints: Test Runs, Test Cases, Specs, Analytics, Test Management

**CLI/SDK**:
- **Node.js**: `@testdino/tdpw` (npm package)
  - Upload test results
  - Rerun failed tests
  - Query test data
  - Manage test cases
- **Python**: `testdino` (pip package)
  - Upload pytest-playwright results
  - Query test history
  - Manage test cases

**MCP Server**:
- Package: `@testdino/mcp-server`
- Protocol: Model Context Protocol (MCP)
- Compatible: Claude Desktop, Cursor, any MCP client
- Tools: 15+ tools for querying and managing test data

**Webhooks**:
- Events: test_run.completed, test_run.failed, flaky_test.detected
- Payload: JSON with test run details
- Retry logic: 3 retries with exponential backoff
- Security: HMAC signature verification

## Documentation Structure

### Getting Started
- Platform Overview: https://docs.testdino.com/ - AI-powered Playwright test reporting platform for tracking test health, analyzing failures, and managing test cases
- Setup Guide: https://docs.testdino.com/getting-started - Step-by-step guide to configure TestDino with your Playwright project in under 5 minutes
- CLI Overview: https://docs.testdino.com/cli/overview - Command-line interface for uploading Playwright test results to TestDino
- Node.js CLI: https://docs.testdino.com/cli/nodejs - Install and configure the TestDino CLI for Node.js Playwright projects
- Python CLI: https://docs.testdino.com/cli/python - Install and configure the TestDino CLI for Python Playwright projects
- Generate API Keys: https://docs.testdino.com/guides/generate-api-keys - Create and manage API keys for CLI authentication and CI/CD integration
- FAQs: https://docs.testdino.com/faqs - Frequently asked questions about TestDino features, pricing, and troubleshooting

### Guides

#### Flaky Tests
- Flaky Tests Overview: https://docs.testdino.com/guides/flaky-tests/overview - Understand flaky test detection, categorization, and resolution strategies in TestDino
- Flaky Test Detection: https://docs.testdino.com/guides/flaky-tests/detection - How TestDino identifies flaky tests using pass/fail pattern analysis across runs
- Flaky Test Root Cause Analysis: https://docs.testdino.com/guides/flaky-tests/root-cause-analysis - Diagnose timing issues, race conditions, and environment dependencies causing flakiness
- Flaky Test Prevention: https://docs.testdino.com/guides/flaky-tests/prevention - Best practices to write stable Playwright tests and prevent flaky behavior

#### Debug Failures
- Debug Failures Overview: https://docs.testdino.com/guides/debug-failures/overview - Debug Playwright test failures without running tests locally using traces, screenshots, and logs
- Trace Viewer: https://docs.testdino.com/guides/debug-failures/trace-viewer - Step through Playwright execution timeline with actions, network calls, and DOM snapshots
- Visual Evidence: https://docs.testdino.com/guides/debug-failures/visual-evidence - Use screenshots and videos to diagnose UI failures and visual regressions
- Error Grouping: https://docs.testdino.com/guides/debug-failures/error-grouping - Group similar test failures by error message to identify common root causes

#### CI Optimization
- CI Optimization Overview: https://docs.testdino.com/guides/ci-optimization/overview - Reduce CI time and cost with TestDino caching and selective test reruns
- Re-run Only Failed Tests: https://docs.testdino.com/guides/ci-optimization/rerun-failed - Reduce CI time by 40-60% by running only tests that failed in the previous run with sharded execution support

#### CI Integration
- GitHub Actions: https://docs.testdino.com/guides/github-actions - Configure Playwright tests with TestDino in GitHub Actions workflows
- GitHub Status Checks: https://docs.testdino.com/guides/github-status-checks - Add TestDino test results as GitHub PR status checks and commit statuses
- TeamCity: https://docs.testdino.com/guides/teamcity - Integrate TestDino with TeamCity CI for Playwright test reporting

#### Other Guides
- Environment Mapping: https://docs.testdino.com/guides/environment-mapping - Map test runs to environments (dev, staging, production) using branch patterns
- Playwright Visual Testing: https://docs.testdino.com/guides/playwright-visual-testing - Compare screenshots with TestDino's visual comparison viewer for toHaveScreenshot assertions

### Platform Features

#### Dashboard
- Dashboard Overview: https://docs.testdino.com/platform/dashboard/overview - Role-based dashboards for QA Engineers, Developers, and Engineering Managers
- QA Dashboard: https://docs.testdino.com/platform/dashboard/qa - Monitor test stability, flaky tests, and failure patterns for QA teams
- Developer Dashboard: https://docs.testdino.com/platform/dashboard/developer - Track branch-specific failures and PR-linked test results for developers

#### Pull Requests
- Pull Requests: https://docs.testdino.com/platform/pull-requests/summary - View test results, commit history, and code changes for each PR in one place
- PR Overview: https://docs.testdino.com/platform/pull-requests/overview - Check PR health with KPI tiles, latest test run, and test results trend
- PR Timeline: https://docs.testdino.com/platform/pull-requests/timeline - Chronological log of commits, test runs, and code review activity for a PR
- PR Files Changed: https://docs.testdino.com/platform/pull-requests/files-changed - Review code diffs alongside test results with GitHub integration

#### Test Runs
- Test Runs Overview: https://docs.testdino.com/platform/test-runs/overview - View and analyze every Playwright test execution with filters and search
- Test Run Summary: https://docs.testdino.com/platform/test-runs/summary - Group failures by cause (assertion, timeout, network) and drill down to specific tests
- Test Run Specs: https://docs.testdino.com/platform/test-runs/specs - Review test results by spec file with duration and status metrics
- Test Run Errors: https://docs.testdino.com/platform/test-runs/errors - Group failed and flaky tests by error message to prioritize fixes
- Test Run History: https://docs.testdino.com/platform/test-runs/history - Compare recent runs to spot regressions and performance drift
- Test Run Configuration: https://docs.testdino.com/platform/test-runs/configuration - View source control, CI pipeline, system info, and test settings for a run
- Test Run AI Insights: https://docs.testdino.com/platform/test-runs/ai-insights - AI-powered error clustering, failure categorization, and pattern detection

#### Test Cases
- Test Cases Overview: https://docs.testdino.com/platform/test-cases/overview - Inspect test status, failure cause, runtime, retries, and evidence for each attempt
- Test Case History: https://docs.testdino.com/platform/test-cases/history - Track stability, retries, and failures across runs for a single test case
- Test Case AI Insights: https://docs.testdino.com/platform/test-cases/ai-insights - AI diagnosis with confidence scores, recommendations, and quick fixes

#### Specs Explorer
- Specs Explorer: https://docs.testdino.com/platform/specs - Find slow, flaky, and failing spec files across your project with reliability metrics

#### Analytics
- Analytics Overview: https://docs.testdino.com/platform/analytics/overview - Project-wide test analytics with trends, metrics, and insights
- Analytics Summary: https://docs.testdino.com/platform/analytics/summary - High-level test suite health metrics and KPIs
- Analytics Test Run: https://docs.testdino.com/platform/analytics/test-run - Test run trends, pass rates, and execution patterns over time
- Analytics Test Case: https://docs.testdino.com/platform/analytics/test-case - Individual test case performance and stability analytics
- Analytics Environment: https://docs.testdino.com/platform/analytics/environment - Compare test results across environments (dev, staging, production)
- Analytics Errors: https://docs.testdino.com/platform/analytics/errors - Error trends and most common failure patterns across test runs

#### AI Insights
- AI Insights Overview: https://docs.testdino.com/platform/ai-insights/overview - AI-powered failure classification, root cause analysis, and suggested fixes

### MCP Integration
- MCP Overview: https://docs.testdino.com/mcp/overview - Connect AI assistants (Claude, ChatGPT, Cursor) to TestDino using Model Context Protocol
- MCP Tools Reference: https://docs.testdino.com/mcp/tools-reference - Complete reference for TestDino MCP server tools and capabilities
- MCP Troubleshooting: https://docs.testdino.com/mcp/troubleshooting - Debug common MCP connection and authentication issues

### Test Management
- Test Management Overview: https://docs.testdino.com/test-management/overview - Organize manual and automated test cases with suites and metadata
- Test Suites: https://docs.testdino.com/test-management/suites - Create and organize test suites to group related test cases
- Test Case Structure: https://docs.testdino.com/test-management/test-case/structure - Define test case fields, steps, expected results, and metadata
- Creating & Editing Test Cases: https://docs.testdino.com/test-management/test-case/creating-editing - Add, edit, and manage test cases in TestDino
- Organizing at Scale: https://docs.testdino.com/test-management/test-case/organizing-at-scale - Best practices for managing large test case libraries
- Import/Export: https://docs.testdino.com/test-management/import-export - Import test cases from CSV/Excel and export for backup or migration

### Integrations
- Integrations Overview: https://docs.testdino.com/integrations/overview - Connect TestDino with CI/CD, issue tracking, and communication tools
- GitHub Integration: https://docs.testdino.com/integrations/ci-cd/github - Connect GitHub for PR comments, status checks, and timeline sync
- Azure DevOps Integration: https://docs.testdino.com/integrations/ci-cd/azure-devops - View test runs, failure trends, and flaky tests directly inside Azure DevOps
- TeamCity Integration: https://docs.testdino.com/integrations/ci-cd/teamcity - Configure TeamCity to upload Playwright results to TestDino
- Jira Integration: https://docs.testdino.com/integrations/issue-tracking/jira - Create Jira issues from failed tests with one click
- Linear Integration: https://docs.testdino.com/integrations/issue-tracking/linear - Create Linear issues from failed tests with one click
- Asana Integration: https://docs.testdino.com/integrations/issue-tracking/asana - Create Asana tasks from failed tests with one click
- monday Integration: https://docs.testdino.com/integrations/issue-tracking/mon - Create monday items from failed tests and view test runs in monday dashboards
- Slack App: https://docs.testdino.com/integrations/slack/app - Receive test run notifications and alerts in Slack channels
- Slack Webhook: https://docs.testdino.com/integrations/slack/webhook - Configure Slack webhooks for custom test result notifications

### Administration
- Organizations Overview: https://docs.testdino.com/platform/organizations/overview - Manage organization settings, members, and projects
- Projects: https://docs.testdino.com/platform/organizations/projects - Create and configure projects for different test suites or applications
- Users & Roles: https://docs.testdino.com/platform/organizations/users-roles - Invite team members and assign roles with appropriate permissions
- Organization Settings: https://docs.testdino.com/platform/organizations/settings - Configure organization-level preferences and defaults
- Permissions: https://docs.testdino.com/platform/permissions - Role-based access control and permission levels in TestDino
- Settings: https://docs.testdino.com/platform/settings - Configure project settings, notifications, and integrations
- Billing & Pricing: https://docs.testdino.com/platform/billing-and-pricing - Subscription plans, usage limits, and billing management

## Resources

- **Website**: https://testdino.com
- **Documentation**: https://docs.testdino.com
- **Sandbox**: https://sandbox.testdino.com
- **Changelog**: https://changelog.testdino.com
- **GitHub**: https://github.com/testdino-hq
- **Discord**: https://discord.gg/hGY9kqSm58
- **YouTube**: https://youtube.com/@TestDino1
- **Support**: support@testdino.com

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