fix(tests): use whitelisted smoke job in quantum autorun status test

[cursor]

Summary

Hourly repo automation failed because two quantum integration tests used a non-whitelisted autorun job name (another). The run_autorun_job API validates job names before status lookup, so the tests never reached the list/dict status parsing they were meant to exercise.

Changes

• Updated test_run_autorun_job_reads_status_for_list_and_dict_shapes to use the whitelisted smoke job name in fixtures and assertions

Verification

• .venv/bin/python -m pytest tests/test_quantum_integration.py — 2 passed
• Full health cycle: .venv/bin/python scripts/repo_health_automation.py --once --repair-status --refresh-stale-status --run-agents --continue-on-fail — all steps passed (2725 unit tests, integration gate, repo agents)

  

Summary by Sourcery

Tests:

• Adjust quantum autorun job status test fixtures and expectations to use the whitelisted smoke job instead of a non-whitelisted job name.

[sourcery-ai]

Reviewer's guide (collapsed on small PRs)

Reviewer's Guide

This PR fixes a quantum integration test by switching it to use a whitelisted autorun job name so that the test exercises the status-shape handling logic instead of failing on job-name validation.

File-Level Changes

Change	Details	Files
Update quantum autorun status integration test to use the whitelisted 'smoke' job so validation passes and status parsing is exercised.	Change parametrized jobs_payload fixtures to use job name 'smoke' instead of 'another' for both list and dict payload shapes Update run_autorun_job invocation in the test to request job 'smoke' Adjust assertions to expect 'smoke' in job_name and status.name fields while still validating preset extraction	tests/test_quantum_integration.py

---

Tips and commands

Interacting with Sourcery

• Trigger a new review: Comment @sourcery-ai review on the pull request.
• Continue discussions: Reply directly to Sourcery's review comments.
• Generate a GitHub issue from a review comment: Ask Sourcery to create an
  issue from a review comment by replying to it. You can also reply to a
  review comment with @sourcery-ai issue to create an issue from it.
• Generate a pull request title: Write @sourcery-ai anywhere in the pull
  request title to generate a title at any time. You can also comment
  @sourcery-ai title on the pull request to (re-)generate the title at any time.
• Generate a pull request summary: Write @sourcery-ai summary anywhere in
  the pull request body to generate a PR summary at any time exactly where you
  want it. You can also comment @sourcery-ai summary on the pull request to
  (re-)generate the summary at any time.
• Generate reviewer's guide: Comment @sourcery-ai guide on the pull
  request to (re-)generate the reviewer's guide at any time.
• Resolve all Sourcery comments: Comment @sourcery-ai resolve on the
  pull request to resolve all Sourcery comments. Useful if you've already
  addressed all the comments and don't want to see them anymore.
• Dismiss all Sourcery reviews: Comment @sourcery-ai dismiss on the pull
  request to dismiss all existing Sourcery reviews. Especially useful if you
  want to start fresh with a new review - don't forget to comment
  @sourcery-ai review to trigger a new review!

Customizing Your Experience

Access your dashboard to:

• Enable or disable review features such as the Sourcery-generated pull request
  summary, the reviewer's guide, and others.
• Change the review language.
• Add, remove or edit custom review instructions.
• Adjust other review settings.

Getting Help

• Contact our support team for questions or feedback.
• Visit our documentation for detailed guides and information.
• Keep in touch with the Sourcery team by following us on X/Twitter, LinkedIn or GitHub.

[github-actions]

🟡 Coverage — dda50fb

Metric	Value
Total coverage	65.2%
→ vs main	0.0%
Minimum threshold	60%

Updated on every push · 2026-06-20