QA Notes

QA Notes are the second half of AI Bug Analysis: while Steps to Reproduce describe how to trigger the bug, QA Notes tell your team what to verify after the fix and which edge cases to check. One analysis run produces both.

How It Works

Snapbug's local service analyzes the bug report — description, voice note transcript, timeline of user interactions, and device context — with your configured AI provider. The response includes a QA section that is parsed and stored with the report:

  • Steps to Reproduce — how to trigger the bug
  • QA Notes — verification checklist for after the fix, plus edge cases worth testing

Example Output

QA Notes:
After the fix, verify:
- The "Share Analytics" toggle persists its state across app restarts.
- A failed PUT /api/user/preferences request reverts the toggle and
  shows an error message instead of silently flipping back.
 
Edge cases to check:
- Toggling rapidly several times in a row.
- Toggling while offline, then going back online.
- The same setting changed from another logged-in device.

Export Integrations

Reports — including the generated STR and QA Notes — can be exported to your issue tracker via the Integrations screen in the inspector:

  • Jira — creates an issue in your project
  • Linear — creates an issue in your team
  • GitHub — creates a GitHub issue

Tips for Better QA Notes

  • Give the AI a real description — severity of the notes follows the specificity of your report.
  • Use voice notes — spoken context about what you expected vs. what happened is transcribed into the analysis.
  • Enable timeline capture — knowing the interaction path lets the AI suggest realistic regression checks.
  • Review and refine — AI-generated notes are a starting point; adjust them before handing off to QA.
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