Quick Reference
| Feature | Where | What it does |
|---|---|---|
| Failure Classification | Test runs, test cases, dashboard | Labels failures as Bug, UI Change, Unstable, or Misc |
| Failure Patterns | AI Insights, error grouping | Identifies persistent and emerging failures across runs |
| Test Case Analysis | Individual test cases | Provides root cause, recommendations, and quick fixes |
| Error Grouping | Test runs, analytics | Groups similar errors by message and stack trace |
| QA Dashboard | Dashboard | Summarizes failure categories and trends |
| MCP Integration | AI assistants | Connects Claude, Cursor, and other AI tools to your test data |
All AI features are enabled by default. Disable individual features or all AI analysis from Project Settings. Changes apply from the next test run.
Failure Classification
Every failed test receives an AI-assigned category with a confidence score.
| Category | Meaning |
|---|---|
| Actual Bug | Consistent failure indicating a product defect. Fix first. |
| UI Change | Selector or DOM change broke a test step. Update locators. |
| Unstable Test | Intermittent failure that passes on retry. Stabilize or quarantine. |
| Miscellaneous | Setup, data, or CI issue outside the above categories. |
- Test run AI Insights tab
- Test case AI Insights panel
- QA Dashboard failure categories
Failure Patterns
AI Insights identifies how failures behave across recent runs.Persistent Failures
Tests failing across multiple runs in the selected window. These are high-impact, recurring problems.
Emerging Failures
Tests that started failing recently and are appearing again. Catch regressions early.
Pattern types also include:
- New Failures: tests that started failing within the selected window
- Regressions: tests that passed recently but now fail again
- Consistent Failures: tests failing across most or all recent runs
Test Case Analysis
For each failed or flaky test, AI provides a detailed breakdown.
| Section | What it provides |
|---|---|
| Category and Confidence | AI label with confidence score |
| Recommendations | Primary evidence and likely cause |
| Historical Insight | Behavior across recent runs (new or recurring) |
| Quick Fixes | Targeted changes to try first |
Error Grouping
AI groups similar errors by message text, stack trace patterns, and failure location. Error types include:- Assertion Failures
- Timeout Issues
- Element Not Found
- Network Issues
- JavaScript Errors
- Browser Issues
QA Dashboard
The QA Dashboard surfaces AI failure categories at a glance. Each category shows the total count and top-impacted tests, with trend indicators for rising or repeating patterns.
See QA Dashboard for the full view.
MCP Integration
Connect Claude Code, Cursor, or Claude Desktop to your TestDino workspace through the MCP server. Assistants query real test data, investigate failures, and suggest fixes using the same AI classification and patterns described above. See TestDino MCP Overview for setup and Tools Reference for all 12 available tools.Related
AI Insights
Cross-run failure analysis and patterns
Test Run AI
Per-run failure categorization and error analysis
Test Case AI
Individual test recommendations and quick fixes
TestDino MCP
Connect AI assistants to your test data