Avoid repeated Cask rename migrations during update

[joseph1020]

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update-report currently calls migrate_cask_rename once for every reporter:

hub.reporters.each(&:migrate_cask_rename)

However, migrate_cask_rename does not use any reporter-specific state. Each invocation loads all installed casks through Cask::Caskroom.casks and runs Cask::Migrator.migrate_if_needed across the same global set.

When several taps are updated in one run, this repeats the same installed-Cask traversal once per reporter.

This change moves the global Cask rename migration to ReporterHub and invokes it once:

hub.migrate_cask_renames

Reporter-specific tap and formula migrations remain unchanged.

I noticed this while investigating repeated load-time Cask DSL warnings during brew outdated with auto-update. With three updated taps, the same installed Cask warnings were emitted repeatedly as each reporter ran the global Cask rename migration.

To reproduce:

Have multiple taps receive updates in the same brew auto-update.
Have an installed third-party cask that emits a warning while its definition is loaded.
Run:
brew outdated

Before this change, the Cask rename migration loads the installed Cask set once per updated reporter. After this change, that migration loads it once for the update-report run.

The regression test verifies that ReporterHub#migrate_cask_renames calls Cask::Caskroom.casks once and processes the returned casks once.

The test was added first and failed with:

NoMethodError:
undefined method 'migrate_cask_renames' for an instance of ReporterHub

After the implementation change it passes.

Local verification:

./bin/brew tests --only=cmd/update-report
./bin/brew style --fix --changed
./bin/brew typecheck
./bin/brew tests --online --changed
./bin/brew lgtm --online
git diff --check

All passed successfully.

• I did not use AI/LLM to create this PR, or I disclosed the tool/model below and reviewed its output; I did not attribute commits to AI and will answer maintainer questions and review comments myself without AI/LLM.

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AI/LLM disclosure: I used ChatGPT (GPT-5.6 Sol) to help investigate the repeated Cask loading, trace the update-report and reporter code paths, review the historical structure, and draft the regression test and PR description. I manually reviewed the changes, reproduced the failing regression test before the implementation change, confirmed it passed afterwards, ran the full update-report spec, and ran the Homebrew validation commands listed above. I will answer maintainer questions and review comments myself without AI/LLM.

[MikeMcQuaid]

Makes sense, thanks!