refactor(examples): split multi-concept examples into focused single-topic files

- Split pruning_and_callbacks into pruning and early_stopping
- Split advanced_features into async_parallel, journal_storage, ask_and_tell, multi_objective
- Each example now requires only its own feature flag
- Trim sampler_comparison winner logic and verbose header
- Update CI workflow and README to match new example names

examples/ask_and_tell.rs

@@ -0,0 +1,51 @@
+//! Ask-and-tell interface — decouple sampling from evaluation.
+//!
+//! Use `ask()` to get a trial with sampled parameters, evaluate it however
+//! you like (workers, GPUs, external processes), then `tell()` the result.
+//! This is useful for batch evaluation or custom scheduling.
+//!
+//! Run with: `cargo run --example ask_and_tell`
+
+use optimizer::prelude::*;
+
+fn main() -> optimizer::Result<()> {
+    let study: Study<f64> = Study::new(Direction::Minimize);
+
+    let x = FloatParam::new(-5.0, 5.0).name("x");
+    let y = FloatParam::new(-5.0, 5.0).name("y");
+
+    for batch in 0..3 {
+        let batch_size = 5;
+        let mut trials = Vec::with_capacity(batch_size);
+
+        // ask() creates trials with sampled parameters
+        for _ in 0..batch_size {
+            let mut trial = study.ask();
+            let xv = x.suggest(&mut trial)?;
+            let yv = y.suggest(&mut trial)?;
+            trials.push((trial, xv, yv));
+        }
+
+        // Evaluate the batch (could be sent to workers, GPUs, etc.)
+        for (trial, xv, yv) in trials {
+            let value = xv * xv + yv * yv;
+            study.tell(trial, Ok::<_, &str>(value));
+        }
+
+        println!(
+            "Batch {}: evaluated {batch_size} trials (total: {})",
+            batch + 1,
+            study.n_trials(),
+        );
+    }
+
+    let best = study.best_trial()?;
+    println!(
+        "Best: f({:.3}, {:.3}) = {:.6}",
+        best.get(&x).unwrap(),
+        best.get(&y).unwrap(),
+        best.value,
+    );
+
+    Ok(())
+}