feat(api): add current_skill / learning_curve / log_evidence / predict_*

New public query methods on History:

- current_skill(&K) -> Option<Gaussian>: latest posterior for a key
- learning_curve(&K) -> Vec<(T, Gaussian)>: single-key history
- learning_curves() -> HashMap<K, Vec<(T, Gaussian)>>: all-keys history
- log_evidence() -> f64: total log-evidence (was log_evidence(false,&[]))
- log_evidence_for(&[&K]) -> f64: subset log-evidence
- predict_quality(&[&[&K]]) -> f64: draw-probability match quality
- predict_outcome(&[&[&K]]) -> Vec<f64>: 2-team win probabilities

learning_curves() changed from returning HashMap<Index, Vec<(i64, Gaussian)>>
to HashMap<K, Vec<(T, Gaussian)>>. A new learning_curves_by_index()
helper preserves the old Index-keyed shape for callers that ingest via
the pub(crate) Index path.

log_evidence(false, &[]) was renamed to log_evidence_internal and made
pub(crate); the new zero-arg log_evidence() wraps it.

predict_outcome is T2 2-team-only; N-team deferred to T4.

KeyTable::get no longer requires ToOwned<Owned = K> (only needed for
get_or_create), allowing query methods to use simpler bounds.

Part of T2 of docs/superpowers/specs/2026-04-23-trueskill-engine-redesign-design.md.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

examples/atp.rs

@@ -64,7 +64,7 @@ fn main() {
         ("wilander", "w023", 32600),
     ];
 
-    let curves = hist.learning_curves();
+    let curves = hist.learning_curves_by_index();
 
     let mut x_spec = (f64::MAX, f64::MIN);
     let mut y_spec = (f64::MAX, f64::MIN);