> ## Documentation Index
> Fetch the complete documentation index at: https://www.bugzy.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Verify changes

> Bugzy reacts to pull requests, ticket transitions, and deployments — running the right tests and reporting results back to your team.

Change-related testing and deployment verification — every time your codebase changes, Bugzy ensures quality hasn't regressed. When a PR is opened, a ticket moves to QA, or a deployment lands, Bugzy automatically runs the relevant tests and reports results. This is the `verify-changes` task, and it's one of the most common ways teams interact with Bugzy.

## Triggers

| Trigger                | Source                | What happens                                                           |
| ---------------------- | --------------------- | ---------------------------------------------------------------------- |
| Pull request opened    | GitHub webhook        | Bugzy runs tests related to changed files, posts results as PR comment |
| Deployment completed   | GitHub/Vercel webhook | Bugzy runs smoke tests against the deployed URL                        |
| Ticket moved to QA     | Jira/Linear webhook   | Bugzy runs tests for the feature or fix described in the ticket        |
| Slack or Teams message | Team member           | "Hey Bugzy, verify the checkout changes" — Bugzy confirms and runs     |
| Manual trigger         | Dashboard             | Select tests and run against any environment                           |
| CI/CD pipeline         | API call              | Trigger via curl or GitHub Action                                      |

## Smart test selection

Bugzy reads the PR title, description, and diff to determine which tests are relevant. If the change touches checkout code, only checkout-related tests run. If Bugzy can't determine relevance, it runs the full smoke suite.

For tickets, Bugzy reads the ticket description and linked PRs to identify the affected area.

## Coverage gap handling

If Bugzy detects that a changed feature has no existing test coverage, it can generate tests on the fly — creating new Playwright scripts for the uncovered area before running them.

## Deployment verification

For deployment triggers (e.g., Vercel preview deploys):

<Steps>
  <Step title="Webhook fires">
    The deployment webhook fires with the preview URL.
  </Step>

  <Step title="Run smoke tests">
    Bugzy runs smoke tests against the preview.
  </Step>

  <Step title="Post results">
    Results are posted as a PR comment and GitHub check run.
  </Step>

  <Step title="Team sees status">
    The PR shows "Bugzy QA / Preview Tests" status.
  </Step>
</Steps>

## Multi-channel result routing

Results are reported through all connected channels:

* **PR comments** — GitHub
* **Channel messages** — Slack or Teams
* **Dashboard** — always available

If a product bug is found, it's filed in the connected issue tracker.

## Verifying AI-generated code

Bugzy doesn't care whether a PR was written by a human or an AI agent. When an AI coding agent (Claude Code, GitHub Copilot, Cursor, etc.) opens a PR and a preview is deployed, the same verify-changes flow runs — tests execute against the preview, results are posted as a GitHub check run, and the PR shows pass/fail status before any human reviews.

This creates an autonomous development loop:

```
AI agent creates PR → CI deploys preview → Bugzy tests preview → Results on PR → Human reviews
```

Teams can configure branch protection rules to require the Bugzy check run to pass before merging, creating an automated QA gate for AI-generated code. See the [Bugzy helping Bugzy](/docs/resources/case-studies/bugzy-helping-bugzy) case study for a real-world example.

## Manual verification checklists

For features that require human verification (visual checks, copy review), Bugzy generates a verification checklist alongside automated test results. The team uses this as a guide for manual sign-off.