Add custom RuboCop cop for consistent exception logging format

[p-datadog]

What does this PR do?
Adds CustomCops::ExceptionMessageCop that enforces consistent exception logging format inside rescue blocks.

The cop detects three patterns:

• e.message → should be e (to_s and message have different contracts; #{e} calls to_s, which is the convention)
• e.class.name → should be e.class (Class#to_s already returns the name)
• #{e} without #{e.class} in the same string → the convention requires the class name

Auto-corrects e.message and e.class.name within string interpolation. The missing-class check flags but does not auto-correct.

Motivation:
Follow-up to #5514 which standardized #{e.class}: #{e} across the codebase. This cop prevents the old patterns from being reintroduced. Suggested by @vpellan during review.

Change log entry
None.

Additional Notes:
Only applies to lib/**/* files (same scope as other custom cops).

How to test the change?

bundle exec rake spec:custom_cop

[datadog-prod-us1-4]

✅ Tests

🎉 All green!

❄️ No new flaky tests detected
🧪 All tests passed

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 95.35% (+0.00%)

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 0c3dcaf | Docs | Datadog PR Page | Was this helpful? React with 👍/👎 or give us feedback!}

[pr-commenter]

Benchmarks

Benchmark execution time: 2026-04-13 22:55:36

Comparing candidate commit 0c3dcaf in PR branch custom-cop/exception-log-format with baseline commit 3260714 in branch master.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 45 metrics, 1 unstable metrics.

Explanation

This is an A/B test comparing a candidate commit's performance against that of a baseline commit. Performance changes are noted in the tables below as:

• 🟩 = significantly better candidate vs. baseline
• 🟥 = significantly worse candidate vs. baseline

We compute a confidence interval (CI) over the relative difference of means between metrics from the candidate and baseline commits, considering the baseline as the reference.

If the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD), the change is considered significant.

Feel free to reach out to #apm-benchmarking-platform on Slack if you have any questions.

More details about the CI and significant changes

You can imagine this CI as a range of values that is likely to contain the true difference of means between the candidate and baseline commits.

CIs of the difference of means are often centered around 0%, because often changes are not that big:

---------------------------------(------|---^--------)-------------------------------->
                              -0.6%    0%  0.3%     +1.2%
                                 |          |        |
         lower bound of the CI --'          |        |
sample mean (center of the CI) -------------'        |
         upper bound of the CI ----------------------'

As described above, a change is considered significant if the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD).

For instance, for an execution time metric, this confidence interval indicates a significantly worse performance:

----------------------------------------|---------|---(---------^---------)---------->
                                       0%        1%  1.3%      2.2%      3.1%
                                                  |   |         |         |
       significant impact threshold --------------'   |         |         |
                      lower bound of CI --------------'         |         |
       sample mean (center of the CI) --------------------------'         |
                      upper bound of CI ----------------------------------'