silhouette_samples(metric='precomputed') silently ignores metric_params, n_jobs, verbose

Problem

tslearn.clustering.silhouette_samples(X, labels, metric="precomputed", metric_params=..., n_jobs=..., verbose=...) silently drops all of metric_params, **kwds, n_jobs, and verbose. The docstring promises metric_params and **kwds are passed to the distance function, and silhouette_score raises on unexpected kwargs via sklearn forwarding, so the silent no-op is a contract inconsistency on the new API surface.

Suggested fix (design call)

Either (a) raise TypeError for any non-None metric_params/n_jobs/verbose/**kwds on the precomputed branch (loud rejection, parity with silhouette_score), or (b) explicitly document that these are ignored when metric == "precomputed".

Metadata

Severity: P3
Confidence: 75
Reviewer(s): api-contract, adversarial (ce-code-review run 20260821-221628-4e205155 on PR #703)
Finding ID: tslearn/clustering/utils.py:330 silhouette_samples(metric="precomputed") silently drops metric_params

Start in tslearn/clustering/utils.py around line 330 and inspect the precomputed branch of silhouette_samples alongside silhouette_score's argument handling. Resolve whether unsupported metric_params, n_jobs, verbose, and **kwds should be rejected or documented as ignored, then verify that none are silently dropped and that the behavior is covered by relevant silhouette tests.