refactor: registry deflation dispatch generic over the MetricVocabulary trait

The A1 cut of #147 item 2, part 1 of 2 (the substrate): the registry's
ranking/deflation machinery no longer bakes in the R metric vocabulary.

- aura-analysis gains the deliberately narrow MetricVocabulary trait (name
  resolution, roster, direction, value read, one null draw) and the
  single-sourced one_sided_p_laplace estimator; re-exported through
  aura-engine's existing seam (no Cargo.toml edge changes anywhere).
- aura-backtest now OWNS the R vocabulary: RunMetricKey (was the registry's
  private Metric enum, exposure_sign_flips alias preserved), r_based (the
  C10 classification), R_BASED_METRICS/RANKABLE_METRICS rosters, the
  centred moving-block null_draw, and member_metric_from_rs.
- aura-registry: metric_cmp/rank_by/null_best_of_k/member_sd generic over
  M: MetricVocabulary; optimize/optimize_plateau/optimize_deflated over
  M: MetricVocabulary + Clone (SweepPoint<M>: Clone bounds on M: Clone);
  the private vocabulary deleted; check_r_metric/generalization stay
  monomorphic on the RunMetrics vocabulary (the C10 wall by type);
  RegistryError::UnknownMetric carries the vocabulary's roster so the
  refusal prose derives instead of being hand-strung (byte-identical for R).

Bit-identity (C18): rng consumption order, centring, Laplace arithmetic,
floors, tie rules, and refusal prose are all unchanged for RunMetrics
inputs — the full registry suite (75 tests) passes unchanged except three
syntax-only edits for the UnknownMetric variant reshape; clippy -D warnings
clean on the three touched crates. Alternatives considered: a vocabulary
table in aura-core (rejected: inverts C28's supplied-from-outer-rungs
direction and cannot host the null model); a parallel measurement-side
deflation path (rejected: duplicates the machinery and adds a fifth
roster). Part 2 lands the consumers (campaign roster single-sourcing, the
IC implementor, acceptance tests).

refs #147

crates/aura-analysis/src/lib.rs

@@ -234,6 +234,45 @@ pub fn permute<T>(xs: &mut [T], rng: &mut SplitMix64) {
     }
 }
 
+/// Per-metric vocabulary a report payload supplies to the registry's
+/// ranking/deflation machinery (#147). Narrow by design (#136): exactly the
+/// surface the backtest metrics (the sole implementor so far) and the
+/// measurement IC (deflatable today via its own permutation-null path, not
+/// yet through this trait) are expected to share. The registry owns the
+/// family fold — best-of-K, p95, Laplace, dispersion floor — the payload
+/// owns what each metric IS: its name, direction, value read, and what one
+/// draw of its null statistic means.
+pub trait MetricVocabulary: Sized {
+    /// Resolved metric identity — cheap to copy, resolved once per call.
+    type Key: Copy;
+    /// Name → key; `None` for a name outside this vocabulary.
+    fn resolve(name: &str) -> Option<Self::Key>;
+    /// The canonical accepted-name roster, in refusal-prose order.
+    fn known() -> &'static [&'static str];
+    /// The key's optimisation direction: `true` when larger is better.
+    fn higher_is_better(key: Self::Key) -> bool;
+    /// The member's scalar under the key. A missing optional block reads
+    /// `f64::NEG_INFINITY` (the worst rank for higher-is-better keys).
+    fn value(&self, key: Self::Key) -> f64;
+    /// Whether the key deflates via a resampled null (the best-of-K arm) or
+    /// the dispersion floor.
+    fn has_resampling_null(key: Self::Key) -> bool;
+    /// ONE draw of this member's null statistic under H0, advancing `rng`.
+    /// `None` means no usable null input for this member, and consumes no
+    /// rng. `block_len` parameterises resampling vocabularies; permutation
+    /// vocabularies ignore it.
+    fn null_draw(&self, key: Self::Key, block_len: usize, rng: &mut SplitMix64) -> Option<f64>;
+}
+
+/// One-sided Laplace-smoothed tail estimate `(ge + 1) / (n + 1)`: the
+/// probability mass at-or-above an observed statistic given that `ge` of `n`
+/// null draws reached it. Intended as the single source of the formula the
+/// registry's R deflation arm and the CLI's IC reduction each compute inline
+/// today; wiring those call sites to this function is deferred follow-up.
+pub fn one_sided_p_laplace(ge: usize, n: usize) -> f64 {
+    (ge + 1) as f64 / (n + 1) as f64
+}
+
 #[cfg(test)]
 mod tests {
     use super::*;
@@ -356,4 +395,13 @@ mod tests {
             filled += take;
         }
     }
+
+    #[test]
+    fn one_sided_p_laplace_known_values() {
+        assert_eq!(one_sided_p_laplace(0, 3), 0.25);
+        assert_eq!(one_sided_p_laplace(3, 3), 1.0);
+        assert_eq!(one_sided_p_laplace(1, 999), 2.0 / 1000.0);
+        // the registry's R-arm shape: count-of-ge over usable draws
+        assert_eq!(one_sided_p_laplace(0, 999), 1.0 / 1000.0);
+    }
 }

crates/aura-backtest/src/lib.rs

@@ -17,7 +17,7 @@ mod sim_broker;
 pub use mc::{monte_carlo, r_bootstrap, McAggregate, McDraw, McFamily, RBootstrap};
 pub use metrics::{
     derive_position_events, r_metrics_from_rs, summarize, summarize_r, PositionAction,
-    PositionEvent, RMetrics, RunMetrics,
+    PositionEvent, RMetrics, RunMetricKey, RunMetrics, RANKABLE_METRICS, R_BASED_METRICS,
 };
 pub use position_management::{
     ExitReason, FIELD_NAMES as PM_FIELD_NAMES, PositionManagement,

crates/aura-backtest/src/metrics.rs

@@ -9,6 +9,7 @@
 //! re-associated.
 
 use aura_core::{Scalar, SeriesFold, Timestamp};
+use aura_engine::{resample_block, MetricVocabulary, SplitMix64};
 
 /// Reduce a run's recorded pip-equity + exposure streams into summary metrics.
 /// Pure — identical inputs yield identical metrics (C1/C12). Timestamps are
@@ -476,6 +477,125 @@ pub struct PositionEvent {
     pub volume: f64,
 }
 
+/// The backtest metric vocabulary's resolved keys (was aura-registry's
+/// private `Metric` enum — the vocabulary is supplied by backtest now, not
+/// baked into the registry; #147). The runtime hot path branches on this
+/// rather than re-parsing the name.
+#[derive(Clone, Copy, PartialEq, Eq, Debug)]
+pub enum RunMetricKey {
+    TotalPips,
+    MaxDrawdown,
+    BiasSignFlips,
+    Sqn,
+    SqnNormalized,
+    ExpectancyR,
+    NetExpectancyR,
+}
+
+impl RunMetricKey {
+    /// C10: the four R-denominated keys — the account/instrument-agnostic
+    /// set the R-only registry gates (`check_r_metric`, `generalization`)
+    /// accept.
+    pub fn r_based(self) -> bool {
+        matches!(
+            self,
+            Self::Sqn | Self::SqnNormalized | Self::ExpectancyR | Self::NetExpectancyR
+        )
+    }
+}
+
+/// The four R-based names, in refusal-prose order (the NonRMetric message).
+pub const R_BASED_METRICS: &[&str] =
+    &["sqn", "sqn_normalized", "expectancy_r", "net_expectancy_r"];
+
+/// The rankable roster, in refusal-prose order — the roster this vocabulary
+/// resolves against (#147). The registry's own refusal prose and
+/// aura-campaign's re-export still hand-copy this list (not yet single-
+/// sourced from here); wiring them to read from here is deferred follow-up.
+pub const RANKABLE_METRICS: &[&str] = &[
+    "total_pips",
+    "max_drawdown",
+    "bias_sign_flips",
+    "sqn",
+    "sqn_normalized",
+    "expectancy_r",
+    "net_expectancy_r",
+];
+
+/// Recompute the selected R metric from a trade-R slice (reuses
+/// `r_metrics_from_rs`, the same arithmetic `summarize_r` uses) — the
+/// deflation null's member reduction (was aura-registry-private, #147).
+fn member_metric_from_rs(rs: &[f64], key: RunMetricKey) -> f64 {
+    let rm = r_metrics_from_rs(rs);
+    match key {
+        RunMetricKey::Sqn => rm.sqn,
+        RunMetricKey::SqnNormalized => rm.sqn_normalized,
+        RunMetricKey::ExpectancyR => rm.expectancy_r,
+        RunMetricKey::NetExpectancyR => rm.net_expectancy_r,
+        _ => unreachable!("member_metric_from_rs is R-only"),
+    }
+}
+
+impl MetricVocabulary for RunMetrics {
+    type Key = RunMetricKey;
+
+    fn resolve(name: &str) -> Option<RunMetricKey> {
+        Some(match name {
+            "total_pips" => RunMetricKey::TotalPips,
+            "max_drawdown" => RunMetricKey::MaxDrawdown,
+            // accept the new name AND the pre-rename one (CLI back-compat).
+            "bias_sign_flips" | "exposure_sign_flips" => RunMetricKey::BiasSignFlips,
+            "sqn" => RunMetricKey::Sqn,
+            "sqn_normalized" => RunMetricKey::SqnNormalized,
+            "expectancy_r" => RunMetricKey::ExpectancyR,
+            "net_expectancy_r" => RunMetricKey::NetExpectancyR,
+            _ => return None,
+        })
+    }
+
+    fn known() -> &'static [&'static str] {
+        RANKABLE_METRICS
+    }
+
+    fn higher_is_better(key: RunMetricKey) -> bool {
+        !matches!(key, RunMetricKey::MaxDrawdown | RunMetricKey::BiasSignFlips)
+    }
+
+    fn value(&self, key: RunMetricKey) -> f64 {
+        fn r_get(m: &RunMetrics, f: impl Fn(&RMetrics) -> f64) -> f64 {
+            m.r.as_ref().map(f).unwrap_or(f64::NEG_INFINITY)
+        }
+        match key {
+            RunMetricKey::TotalPips => self.total_pips,
+            RunMetricKey::MaxDrawdown => self.max_drawdown,
+            RunMetricKey::BiasSignFlips => self.bias_sign_flips as f64,
+            RunMetricKey::Sqn => r_get(self, |r| r.sqn),
+            RunMetricKey::SqnNormalized => r_get(self, |r| r.sqn_normalized),
+            RunMetricKey::ExpectancyR => r_get(self, |r| r.expectancy_r),
+            RunMetricKey::NetExpectancyR => r_get(self, |r| r.net_expectancy_r),
+        }
+    }
+
+    fn has_resampling_null(key: RunMetricKey) -> bool {
+        key.r_based()
+    }
+
+    /// # Panics
+    /// Panics (via `member_metric_from_rs`'s `unreachable!`) if `key` is not
+    /// R-based — callers must gate on `has_resampling_null(key)` before
+    /// drawing, exactly as documented at the trait level.
+    fn null_draw(&self, key: RunMetricKey, block_len: usize, rng: &mut SplitMix64) -> Option<f64> {
+        let rs: &[f64] = self.r.as_ref().map(|r| r.net_trade_rs.as_slice()).unwrap_or(&[]);
+        if rs.is_empty() {
+            return None; // consumes no rng — bit-parity with the pre-#147 fold
+        }
+        let mean = rs.iter().sum::<f64>() / rs.len() as f64;
+        let centred: Vec<f64> = rs.iter().map(|x| x - mean).collect();
+        let bl = block_len.clamp(1, rs.len());
+        Some(member_metric_from_rs(&resample_block(&centred, bl, rng), key))
+    }
+}
+
 #[cfg(test)]
 mod tests {
     use super::*;
@@ -1252,4 +1372,102 @@ mod tests {
         let m = summarize(&[], &exposure);
         assert_eq!(m.bias_sign_flips, 0);
     }
+
+    #[test]
+    fn run_metrics_vocabulary_resolves_and_classifies() {
+        use aura_engine::MetricVocabulary;
+        assert!(matches!(
+            <RunMetrics as MetricVocabulary>::resolve("sqn"),
+            Some(RunMetricKey::Sqn)
+        ));
+        // the pre-rename CLI alias must keep resolving (back-compat).
+        assert!(matches!(
+            <RunMetrics as MetricVocabulary>::resolve("exposure_sign_flips"),
+            Some(RunMetricKey::BiasSignFlips)
+        ));
+        assert!(<RunMetrics as MetricVocabulary>::resolve("sharpe").is_none());
+        assert_eq!(<RunMetrics as MetricVocabulary>::known(), RANKABLE_METRICS);
+        assert!(RunMetricKey::Sqn.r_based());
+        assert!(!RunMetricKey::TotalPips.r_based());
+    }
+
+    /// Property: an R-based key on a member with no `r` block ranks worst for
+    /// a higher-is-better metric (`f64::NEG_INFINITY`), never a silent default
+    /// like `0.0` that could out-rank a genuinely poor member; non-R keys are
+    /// read straight from the pip-only fields regardless of the `r` block.
+    #[test]
+    fn value_r_based_key_reads_neg_infinity_when_r_block_absent() {
+        let m = RunMetrics { total_pips: 5.0, max_drawdown: 2.0, bias_sign_flips: 1, r: None };
+        for key in [
+            RunMetricKey::Sqn,
+            RunMetricKey::SqnNormalized,
+            RunMetricKey::ExpectancyR,
+            RunMetricKey::NetExpectancyR,
+        ] {
+            assert_eq!(m.value(key), f64::NEG_INFINITY, "missing r block must rank worst");
+        }
+        assert_eq!(m.value(RunMetricKey::TotalPips), 5.0);
+        assert_eq!(m.value(RunMetricKey::MaxDrawdown), 2.0);
+        assert_eq!(m.value(RunMetricKey::BiasSignFlips), 1.0);
+    }
+
+    /// Property: a member with no trade-R input (no `r` block) yields no null
+    /// draw AND leaves the rng untouched — the "consumes no rng" contract the
+    /// implementation comment claims. Verified indirectly (SplitMix64 carries
+    /// no Clone/PartialEq): the rng's next draw after the no-op call matches a
+    /// freshly, identically-seeded rng's first draw.
+    #[test]
+    fn null_draw_returns_none_and_consumes_no_rng_when_no_trades() {
+        let m = RunMetrics { total_pips: 0.0, max_drawdown: 0.0, bias_sign_flips: 0, r: None };
+        let mut rng = SplitMix64::new(11);
+        let got = m.null_draw(RunMetricKey::Sqn, 2, &mut rng);
+        assert_eq!(got, None);
+        let mut fresh = SplitMix64::new(11);
+        assert_eq!(
+            rng.next_u64(),
+            fresh.next_u64(),
+            "null_draw's None path must consume no rng state"
+        );
+    }
+
+    /// Property: `null_draw` recomputes the selected key by mean-centring
+    /// `net_trade_rs`, block-resampling it under the given rng, and reducing
+    /// via `member_metric_from_rs` — exactly the recipe reproduced here by
+    /// hand with an identically-seeded rng (C1: same seed -> same draw).
+    #[test]
+    fn null_draw_recomputes_the_selected_key_from_a_seeded_block_resample() {
+        let net_trade_rs = vec![1.0, 2.0, -1.0, 3.0];
+        let m = RunMetrics {
+            total_pips: 0.0,
+            max_drawdown: 0.0,
+            bias_sign_flips: 0,
+            r: Some(RMetrics {
+                expectancy_r: 0.0,
+                n_trades: 4,
+                win_rate: 0.0,
+                avg_win_r: 0.0,
+                avg_loss_r: 0.0,
+                profit_factor: 0.0,
+                max_r_drawdown: 0.0,
+                n_open_at_end: 0,
+                sqn: 0.0,
+                sqn_normalized: 0.0,
+                net_expectancy_r: 0.0,
+                conviction_terciles_r: [0.0; 3],
+                net_trade_rs: net_trade_rs.clone(),
+            }),
+        };
+        let mut rng_a = SplitMix64::new(7);
+        let got = m
+            .null_draw(RunMetricKey::ExpectancyR, 2, &mut rng_a)
+            .expect("nonempty net_trade_rs yields a draw");
+
+        let mean = net_trade_rs.iter().sum::<f64>() / net_trade_rs.len() as f64;
+        let centred: Vec<f64> = net_trade_rs.iter().map(|x| x - mean).collect();
+        let mut rng_b = SplitMix64::new(7);
+        let resampled = resample_block(&centred, 2, &mut rng_b);
+        let want = member_metric_from_rs(&resampled, RunMetricKey::ExpectancyR);
+
+        assert_eq!(got, want);
+    }
 }

crates/aura-engine/src/lib.rs

@@ -79,7 +79,7 @@ pub use sweep::{
 // `resample_block`/`MetricStats` are foundation-grade (aura-analysis, #291);
 // re-exported here (unchanged exported name set) so existing
 // `aura_engine::{resample_block, MetricStats}` consumers stay source-compatible.
-pub use aura_analysis::{resample_block, MetricStats};
+pub use aura_analysis::{one_sided_p_laplace, resample_block, MetricStats, MetricVocabulary};
 pub use walkforward::{
     param_stability, walk_forward, RollMode, WalkForwardError, WalkForwardResult,
     WindowBounds, WindowOutcome, WindowRoller, WindowRun,

crates/aura-registry/src/lib.rs

@@ -18,8 +18,8 @@ use std::io::Write;
 use std::path::{Path, PathBuf};
 
 use aura_core::PrimitiveBuilder;
-use aura_analysis::{resample_block, MetricStats, SplitMix64};
+use aura_analysis::{one_sided_p_laplace, MetricStats, MetricVocabulary, SplitMix64};
-use aura_backtest::{r_metrics_from_rs, RunReport, SweepFamily, SweepPoint};
+use aura_backtest::{RunMetrics, RunReport};
 use aura_engine::{
     blueprint_from_json, blueprint_identity_json, expected_max_of_normals, FamilySelection,
     SelectionMode,
@@ -495,77 +495,30 @@ impl Registry {
     }
 }
 
-/// Which metric a best-first comparison keys on. Resolves a metric *name* (a
-/// string at the API boundary) to a closed kind once, so the per-comparison hot
-/// path branches on this rather than re-parsing the name.
-#[derive(Clone, Copy)]
-enum Metric {
-    TotalPips,
-    MaxDrawdown,
-    BiasSignFlips,
-    Sqn,
-    SqnNormalized,
-    ExpectancyR,
-    NetExpectancyR,
-}
-
-/// Resolve a metric NAME to the closed `Metric` kind (the single name→kind map).
-/// An unknown name is a `RegistryError::UnknownMetric`.
-fn resolve_metric(name: &str) -> Result<Metric, RegistryError> {
-    Ok(match name {
-        "total_pips" => Metric::TotalPips,
-        "max_drawdown" => Metric::MaxDrawdown,
-        // accept the new name AND the pre-rename one (CLI back-compat).
-        "bias_sign_flips" | "exposure_sign_flips" => Metric::BiasSignFlips,
-        "sqn" => Metric::Sqn,
-        "sqn_normalized" => Metric::SqnNormalized,
-        "expectancy_r" => Metric::ExpectancyR,
-        "net_expectancy_r" => Metric::NetExpectancyR,
-        other => return Err(RegistryError::UnknownMetric(other.to_string())),
-    })
-}
-
-/// The metric's scalar value for one report. R metrics live in the optional `r`
-/// block; a missing block reads `NEG_INFINITY` (the worst rank for the
-/// higher-is-better R keys), preserving `metric_cmp`'s documented contract.
-fn metric_value(rep: &RunReport, m: Metric) -> f64 {
-    fn r_get(rep: &RunReport, f: impl Fn(&aura_backtest::RMetrics) -> f64) -> f64 {
-        rep.metrics.r.as_ref().map(f).unwrap_or(f64::NEG_INFINITY)
-    }
-    match m {
-        Metric::TotalPips => rep.metrics.total_pips,
-        Metric::MaxDrawdown => rep.metrics.max_drawdown,
-        Metric::BiasSignFlips => rep.metrics.bias_sign_flips as f64,
-        Metric::Sqn => r_get(rep, |r| r.sqn),
-        Metric::SqnNormalized => r_get(rep, |r| r.sqn_normalized),
-        Metric::ExpectancyR => r_get(rep, |r| r.expectancy_r),
-        Metric::NetExpectancyR => r_get(rep, |r| r.net_expectancy_r),
-    }
-}
-
 /// The per-metric **best-first ordering** of two reports: `Less` means `a` is
-/// better than `b`. "Best" is fixed by each metric's meaning: `total_pips` and
+/// better than `b`. "Best" is fixed by each metric's meaning as declared by
-/// the four R keys (`sqn`, `sqn_normalized`, `expectancy_r`, `net_expectancy_r`)
+/// the payload's `MetricVocabulary` (direction via `higher_is_better`; a
-/// higher-is-better; `max_drawdown` and `bias_sign_flips` lower-is-better. Every
+/// missing optional block reads `f64::NEG_INFINITY`, the worst rank for
-/// metric compares via `total_cmp` (a total order over `f64`): top-level keys are
+/// higher-is-better keys). Every metric compares via `total_cmp` (a total
-/// finite by construction, while the R keys live in an optional `metrics.r` block
+/// order over `f64`), so strays order deterministically without panicking. An
-/// where a member with `r: None` reads `f64::NEG_INFINITY` (the worst rank for
+/// unknown metric name is a `RegistryError::UnknownMetric` carrying the
-/// higher-is-better) — `total_cmp` orders that, and any stray `NaN`,
+/// vocabulary's own roster.
-/// deterministically without panicking. An unknown metric name is a
-/// `RegistryError::UnknownMetric`.
 ///
-/// The single source of best-first *ordering* — both [`rank_by`] (sort by it) and
+/// The single source of best-first *ordering* — both [`rank_by`] (sort by it)
-/// [`optimize`] (argmax by it) call this. The per-metric direction itself lives in
+/// and [`optimize`] (argmax by it) call this. The name is resolved once via
-/// `higher_is_better` (which this and `optimize_plateau` both read); `metric_cmp`
+/// `M::resolve`; the returned closure carries the resolved key, so
-/// turns that direction into a `total_cmp` over the read values. The metric name is
+/// per-comparison work is just reading each value and the key compare.
-/// resolved once via `resolve_metric`; the returned closure carries the resolved
+fn metric_cmp<M: MetricVocabulary>(
-/// `Metric`, so per-comparison work is just reading each value (`metric_value`) and
+    metric: &str,
-/// the key compare.
+) -> Result<impl Fn(&aura_engine::RunReport<M>, &aura_engine::RunReport<M>) -> Ordering, RegistryError>
-fn metric_cmp(metric: &str) -> Result<impl Fn(&RunReport, &RunReport) -> Ordering, RegistryError> {
+{
-    let m = resolve_metric(metric)?;
+    let key = M::resolve(metric).ok_or_else(|| RegistryError::UnknownMetric {
-    let hib = higher_is_better(m);
+        name: metric.to_string(),
-    Ok(move |a: &RunReport, b: &RunReport| {
+        known: M::known(),
-        let (va, vb) = (metric_value(a, m), metric_value(b, m));
+    })?;
+    let hib = M::higher_is_better(key);
+    Ok(move |a: &aura_engine::RunReport<M>, b: &aura_engine::RunReport<M>| {
+        let (va, vb) = (a.metrics.value(key), b.metrics.value(key));
         // higher-is-better ranks the larger value first; lower-is-better the smaller.
         if hib { vb.total_cmp(&va) } else { va.total_cmp(&vb) }
     })
@@ -575,8 +528,11 @@ fn metric_cmp(metric: &str) -> Result<impl Fn(&RunReport, &RunReport) -> Orderin
 /// by each metric's meaning (see `metric_cmp`). A stable sort keeps file
 /// (insertion) order among ties. An unknown metric name is a
 /// `RegistryError::UnknownMetric`.
-pub fn rank_by(mut reports: Vec<RunReport>, metric: &str) -> Result<Vec<RunReport>, RegistryError> {
+pub fn rank_by<M: MetricVocabulary>(
-    let cmp = metric_cmp(metric)?;
+    mut reports: Vec<aura_engine::RunReport<M>>,
+    metric: &str,
+) -> Result<Vec<aura_engine::RunReport<M>>, RegistryError> {
+    let cmp = metric_cmp::<M>(metric)?;
     reports.sort_by(|a, b| cmp(a, b));
     Ok(reports)
 }
@@ -590,8 +546,11 @@ pub fn rank_by(mut reports: Vec<RunReport>, metric: &str) -> Result<Vec<RunRepor
 /// An unknown metric is a `RegistryError::UnknownMetric`. A `SweepFamily` is
 /// non-empty by construction (a sweep over a zero-point grid is rejected upstream
 /// by `EmptyAxis`), so `reduce` always yields a winner.
-pub fn optimize(family: &SweepFamily, metric: &str) -> Result<SweepPoint, RegistryError> {
+pub fn optimize<M: MetricVocabulary + Clone>(
-    let cmp = metric_cmp(metric)?;
+    family: &aura_engine::SweepFamily<M>,
+    metric: &str,
+) -> Result<aura_engine::SweepPoint<M>, RegistryError> {
+    let cmp = metric_cmp::<M>(metric)?;
     let winner = family
         .points
         .iter()
@@ -600,19 +559,6 @@ pub fn optimize(family: &SweepFamily, metric: &str) -> Result<SweepPoint, Regist
     Ok(winner.clone())
 }
 
-fn is_r_metric(m: Metric) -> bool {
-    matches!(m, Metric::Sqn | Metric::SqnNormalized | Metric::ExpectancyR | Metric::NetExpectancyR)
-}
-
-/// The metric's optimisation direction: `true` if a larger value is better
-/// (`total_pips`, the four R keys), `false` for the lower-is-better keys
-/// (`max_drawdown`, `bias_sign_flips`). The single direction source — `metric_cmp`
-/// (best-first ordering) and `optimize_plateau` (smoothed argmax + worst-neighbour)
-/// both read it, so the per-metric sense lives in exactly one place.
-fn higher_is_better(m: Metric) -> bool {
-    !matches!(m, Metric::MaxDrawdown | Metric::BiasSignFlips)
-}
-
 /// The closed grid neighbourhood of flat index `i` over a mixed-radix lattice
 /// (`axis_lens`, last axis fastest — the `GridSpace` odometer convention): `{i}`
 /// plus each in-range ±1-per-axis cell. Pure index math, deterministic. The order
@@ -641,49 +587,36 @@ fn closed_neighbourhood(i: usize, axis_lens: &[usize]) -> Vec<usize> {
     out
 }
 
-fn member_net_trade_rs(rep: &RunReport) -> &[f64] {
+/// The best-of-K null-max distribution, vocabulary-generic: for each resample
-    rep.metrics.r.as_ref().map(|r| r.net_trade_rs.as_slice()).unwrap_or(&[])
+/// every member draws ONE null statistic from its own vocabulary (in odometer
-}
+/// order, from a per-iteration seed) and the max across members is taken. A
-
+/// member with no usable null input contributes nothing and consumes no rng
-/// Recompute the selected R metric from a trade-R slice (reuses the engine's
+/// (bit-parity with the pre-#147 R fold, whose centring is now inside
-/// `r_metrics_from_rs`, the same arithmetic `summarize_r` uses).
+/// `RunMetrics::null_draw`). Deterministic given `seed` (C1).
-fn member_metric_from_rs(rs: &[f64], m: Metric) -> f64 {
+fn null_best_of_k<M: MetricVocabulary>(
-    let rm = r_metrics_from_rs(rs);
+    family: &aura_engine::SweepFamily<M>,
-    match m {
+    key: M::Key,
-        Metric::Sqn => rm.sqn,
+    n_resamples: usize,
-        Metric::SqnNormalized => rm.sqn_normalized,
+    block_len: usize,
-        Metric::ExpectancyR => rm.expectancy_r,
+    seed: u64,
-        Metric::NetExpectancyR => rm.net_expectancy_r,
+) -> Vec<f64> {
-        _ => unreachable!("member_metric_from_rs is R-only"),
+    (0..n_resamples)
-    }
+        .map(|i| {
-}
+            let mut rng = SplitMix64::new(seed ^ i as u64);
-
+            family.points.iter().fold(f64::NEG_INFINITY, |best, p| {
-/// The centred best-of-K null-max distribution: each member's `net_trade_rs` is
+                match p.report.metrics.null_draw(key, block_len, &mut rng) {
-/// mean-subtracted (the no-edge null), then for each resample every member is
+                    Some(v) => best.max(v),
-/// moving-block-resampled (in odometer order, from a per-iteration seed) and the
+                    None => best,
-/// max recomputed metric across members is taken. Deterministic given `seed` (C1).
+                }
-fn null_best_of_k(family: &SweepFamily, m: Metric, n_resamples: usize, block_len: usize, seed: u64) -> Vec<f64> {
+            })
-    let centred: Vec<Vec<f64>> = family.points.iter().map(|p| {
-        let rs = member_net_trade_rs(&p.report);
-        if rs.is_empty() { return Vec::new(); }
-        let mean = rs.iter().sum::<f64>() / rs.len() as f64;
-        rs.iter().map(|x| x - mean).collect()
-    }).collect();
-    (0..n_resamples).map(|i| {
-        let mut rng = SplitMix64::new(seed ^ i as u64);
-        centred.iter().fold(f64::NEG_INFINITY, |best, rs| {
-            if rs.is_empty() { return best; }
-            let bl = block_len.clamp(1, rs.len());
-            let v = member_metric_from_rs(&resample_block(rs, bl, &mut rng), m);
-            best.max(v)
         })
-    }).collect()
+        .collect()
 }
 
 /// Sample standard deviation of the K members' metric values (the `total_pips`
 /// dispersion-floor arm). `< 2` members -> `0.0`.
-fn member_sd(family: &SweepFamily, m: Metric) -> f64 {
+fn member_sd<M: MetricVocabulary>(family: &aura_engine::SweepFamily<M>, key: M::Key) -> f64 {
-    let vals: Vec<f64> = family.points.iter().map(|p| metric_value(&p.report, m)).collect();
+    let vals: Vec<f64> = family.points.iter().map(|p| p.report.metrics.value(key)).collect();
     let n = vals.len();
     if n < 2 { return 0.0; }
     let mean = vals.iter().sum::<f64>() / n as f64;
@@ -702,27 +635,30 @@ pub enum PlateauMode {
 
 /// `optimize`'s argmax over the NEIGHBOURHOOD-SMOOTHED surface, plus its plateau
 /// provenance. Each member scores as the mean (or worst-case) of its closed grid
-/// neighbourhood's `metric_value`; the winner is the best smoothed score by the
+/// neighbourhood's metric value; the winner is the best smoothed score by the
 /// metric's own direction (earliest-odometer tie, as `optimize`). `axis_lens` are
 /// the grid radixes (`param_space()` order, last axis fastest). Pure,
 /// deterministic (C1). The returned `SweepPoint` is the winning grid CELL;
 /// `raw_winner_metric` is that cell's own metric, `neighbourhood_score` the
 /// smoothed value the argmax maximised.
-pub fn optimize_plateau(
+pub fn optimize_plateau<M: MetricVocabulary + Clone>(
-    family: &SweepFamily, axis_lens: &[usize], metric: &str, mode: PlateauMode,
+    family: &aura_engine::SweepFamily<M>, axis_lens: &[usize], metric: &str, mode: PlateauMode,
-) -> Result<(SweepPoint, FamilySelection), RegistryError> {
+) -> Result<(aura_engine::SweepPoint<M>, FamilySelection), RegistryError> {
-    let m = resolve_metric(metric)?;
+    let key = M::resolve(metric).ok_or_else(|| RegistryError::UnknownMetric {
+        name: metric.to_string(),
+        known: M::known(),
+    })?;
     let n = family.points.len();
     debug_assert_eq!(
         axis_lens.iter().product::<usize>(), n,
         "axis_lens product must equal the family size (a valid grid lattice)",
     );
-    let hib = higher_is_better(m);
+    let hib = M::higher_is_better(key);
     // smoothed score + closed-neighbourhood size per member, in odometer order
     let scored: Vec<(usize, f64, usize)> = (0..n)
         .map(|i| {
             let nbrs = closed_neighbourhood(i, axis_lens);
-            let vals: Vec<f64> = nbrs.iter().map(|&j| metric_value(&family.points[j].report, m)).collect();
+            let vals: Vec<f64> = nbrs.iter().map(|&j| family.points[j].report.metrics.value(key)).collect();
             let score = match mode {
                 PlateauMode::Mean => vals.iter().sum::<f64>() / vals.len() as f64,
                 PlateauMode::Worst => {
@@ -746,7 +682,7 @@ pub fn optimize_plateau(
         })
         .expect("a SweepFamily is non-empty by construction (EmptyAxis is rejected upstream)");
     let winner = family.points[wi].clone();
-    let raw = metric_value(&winner.report, m);
+    let raw = winner.report.metrics.value(key);
     Ok((
         winner,
         FamilySelection {
@@ -777,28 +713,34 @@ pub const DEFLATION_BLOCK_LEN: usize = 5;
 
 /// `optimize`'s argmax winner PLUS its trials-deflation provenance. The returned
 /// `SweepPoint` is byte-identical to `optimize(family, metric)` (additive, C23).
-/// R arm: a centred moving-block reality-check (`overfit_probability` =
+/// Which arm runs is vocabulary-declared resampling null vs dispersion floor
-/// `(count(null ≥ raw) + 1)/(n + 1)`, `deflated_score` = `raw − p95(null)`).
+/// (`M::has_resampling_null`): a resampling-null key gets a centred moving-block
-/// `total_pips` arm: a closed-form expected-max-of-K dispersion floor, no
+/// reality-check (`overfit_probability` = `(count(null ≥ raw) + 1)/(n + 1)`,
-/// probability. Deterministic given `seed` (C1).
+/// `deflated_score` = `raw − p95(null)`); otherwise a closed-form
-pub fn optimize_deflated(
+/// expected-max-of-K dispersion floor, no probability. Deterministic given
-    family: &SweepFamily, metric: &str, n_resamples: usize, block_len: usize, seed: u64,
+/// `seed` (C1).
-) -> Result<(SweepPoint, FamilySelection), RegistryError> {
+pub fn optimize_deflated<M: MetricVocabulary + Clone>(
+    family: &aura_engine::SweepFamily<M>, metric: &str, n_resamples: usize, block_len: usize, seed: u64,
+) -> Result<(aura_engine::SweepPoint<M>, FamilySelection), RegistryError> {
     let winner = optimize(family, metric)?;
-    let m = resolve_metric(metric)?;
+    let key = M::resolve(metric).ok_or_else(|| RegistryError::UnknownMetric {
+        name: metric.to_string(),
+        known: M::known(),
+    })?;
     let k = family.points.len();
-    let raw = metric_value(&winner.report, m);
+    let raw = winner.report.metrics.value(key);
 
-    let (deflated_score, overfit_probability) = if is_r_metric(m) {
+    let (deflated_score, overfit_probability) = if M::has_resampling_null(key) {
-        let null_max = null_best_of_k(family, m, n_resamples, block_len, seed);
+        let null_max = null_best_of_k(family, key, n_resamples, block_len, seed);
         // Keep only the finite best-of-K draws. The null is *not computable* in two
-        // degenerate cases: zero resamples (`null_max` empty), or no member carries
+        // degenerate cases: zero resamples (`null_max` empty), or no member yields a
-        // `net_trade_rs` (every member's centred series is empty, so each iteration's
+        // usable draw (`null_draw` returns `None` for every member, so each
-        // best-of-K folds to `NEG_INFINITY`). The latter is reachable — `net_trade_rs`
+        // iteration's best-of-K folds to `NEG_INFINITY`). The latter is reachable —
-        // is `#[serde(skip)]`, so a family loaded back from the registry has empty
+        // the R conduit `net_trade_rs` is `#[serde(skip)]`, so a family loaded back
-        // conduits even when its `r` block (hence `raw`) is finite. Filtering to
+        // from the registry has empty conduits even when its `r` block (hence `raw`)
-        // finite values collapses both into one "no usable null" branch, instead of
+        // is finite. Filtering to finite values collapses both into one "no usable
-        // letting `p95 = NEG_INFINITY` turn `deflated_score` into `+inf`.
+        // null" branch, instead of letting `p95 = NEG_INFINITY` turn
+        // `deflated_score` into `+inf`.
         let usable: Vec<f64> = null_max.into_iter().filter(|x| x.is_finite()).collect();
         if usable.is_empty() {
             // No reality-check is computable: floor to a degenerate-but-defined
@@ -807,22 +749,22 @@ pub fn optimize_deflated(
             (raw, Some(1.0))
         } else {
             let p95 = MetricStats::from_values(&usable).p95;
-            let over = (usable.iter().filter(|&&x| x >= raw).count() + 1) as f64
+            let ge = usable.iter().filter(|&&x| x >= raw).count();
-                / (usable.len() + 1) as f64;
+            let over = one_sided_p_laplace(ge, usable.len());
             (raw - p95, Some(over))
         }
     } else {
         // The dispersion floor SUBTRACTS the expected-max inflation, so it is valid
         // only for a higher-is-better metric (a larger value is the better one the
         // search inflated). A lower-is-better metric would deflate wrong-signed; the
-        // two shipped call sites only pass `total_pips`, so this is unreached, but
+        // shipped call sites only pass `total_pips`, so this is unreached, but
         // `optimize_deflated` is public — guard the assumption rather than leave it
         // implicit.
         debug_assert!(
-            !matches!(m, Metric::MaxDrawdown | Metric::BiasSignFlips),
+            M::higher_is_better(key),
             "dispersion-floor arm is for higher-is-better metrics only",
         );
-        (raw - member_sd(family, m) * expected_max_of_normals(k), None)
+        (raw - member_sd(family, key) * expected_max_of_normals(k), None)
     };
 
     Ok((winner.clone(), FamilySelection {
@@ -854,8 +796,13 @@ pub struct Generalization {
 /// the CLI runs before evaluating any instrument. The registry owns metric truth
 /// (C9), so the CLI never duplicates the R-set.
 pub fn check_r_metric(metric: &str) -> Result<(), RegistryError> {
-    let m = resolve_metric(metric)?;
+    let key = <RunMetrics as MetricVocabulary>::resolve(metric).ok_or_else(|| {
-    if is_r_metric(m) {
+        RegistryError::UnknownMetric {
+            name: metric.to_string(),
+            known: <RunMetrics as MetricVocabulary>::known(),
+        }
+    })?;
+    if key.r_based() {
         Ok(())
     } else {
         Err(RegistryError::NonRMetric(metric.to_string()))
@@ -871,8 +818,13 @@ pub fn generalization(
     per_instrument: &[(String, &RunReport)],
     metric: &str,
 ) -> Result<Generalization, RegistryError> {
-    let m = resolve_metric(metric)?;
+    let key = <RunMetrics as MetricVocabulary>::resolve(metric).ok_or_else(|| {
-    if !is_r_metric(m) {
+        RegistryError::UnknownMetric {
+            name: metric.to_string(),
+            known: <RunMetrics as MetricVocabulary>::known(),
+        }
+    })?;
+    if !key.r_based() {
         return Err(RegistryError::NonRMetric(metric.to_string()));
     }
     if per_instrument.len() < 2 {
@@ -880,7 +832,7 @@ pub fn generalization(
     }
     let vals: Vec<(String, f64)> = per_instrument
         .iter()
-        .map(|(label, rep)| (label.clone(), metric_value(rep, m)))
+        .map(|(label, rep)| (label.clone(), rep.metrics.value(key)))
         .collect();
     let worst_case = vals.iter().map(|(_, v)| *v).fold(f64::INFINITY, f64::min);
     let sign_agreement = vals.iter().filter(|(_, v)| *v > 0.0).count();
@@ -900,8 +852,8 @@ pub enum RegistryError {
     Io(std::io::Error),
     /// A stored line did not parse as a `RunReport` (1-based line number).
     Parse { line: usize, source: serde_json::Error },
-    /// `rank_by` was given a metric name it does not know.
+    /// `rank_by` was given a metric name outside the family's vocabulary.
-    UnknownMetric(String),
+    UnknownMetric { name: String, known: &'static [&'static str] },
     /// A known metric that is not R-based — cross-instrument generalization is
     /// R-only (R is the only account/instrument-agnostic unit, C10).
     NonRMetric(String),
@@ -916,13 +868,15 @@ impl fmt::Display for RegistryError {
             RegistryError::Parse { line, source } => {
                 write!(f, "registry parse error at line {line}: {source}")
             }
-            RegistryError::UnknownMetric(m) => write!(
+            RegistryError::UnknownMetric { name, known } => write!(
                 f,
-                "unknown metric '{m}' (known: total_pips, max_drawdown, bias_sign_flips, sqn, sqn_normalized, expectancy_r, net_expectancy_r)"
+                "unknown metric '{name}' (known: {})",
+                known.join(", ")
             ),
             RegistryError::NonRMetric(m) => write!(
                 f,
-                "metric '{m}' is not comparable across instruments; cross-instrument scoring is R-only (sqn, sqn_normalized, expectancy_r, net_expectancy_r)"
+                "metric '{m}' is not comparable across instruments; cross-instrument scoring is R-only ({})",
+                aura_backtest::R_BASED_METRICS.join(", ")
             ),
             RegistryError::TooFewInstruments(n) => write!(
                 f,
@@ -944,7 +898,7 @@ impl From<std::io::Error> for RegistryError {
 mod tests {
     use super::*;
     use aura_core::{Cell, Scalar, Timestamp};
-    use aura_backtest::{RMetrics, RunMetrics};
+    use aura_backtest::{RMetrics, RunMetrics, SweepFamily, SweepPoint};
     use aura_engine::RunManifest;
 
     fn report_with(total_pips: f64, max_drawdown: f64, flips: u64) -> RunReport {
@@ -1037,7 +991,8 @@ mod tests {
 
     #[test]
     fn unknown_metric_message_lists_r_metrics() {
-        let msg = RegistryError::UnknownMetric("nope".to_string()).to_string();
+        let msg = RegistryError::UnknownMetric { name: "nope".to_string(), known: aura_backtest::RANKABLE_METRICS }
+            .to_string();
         assert!(msg.contains("sqn"), "msg: {msg}");
         assert!(msg.contains("sqn_normalized"), "msg: {msg}");
         assert!(msg.contains("expectancy_r"), "msg: {msg}");
@@ -1176,7 +1131,7 @@ mod tests {
     fn rank_by_unknown_metric_is_an_error() {
         let reports = vec![report_with(1.0, 0.5, 1)];
         match rank_by(reports, "sharpe") {
-            Err(RegistryError::UnknownMetric(m)) => assert_eq!(m, "sharpe"),
+            Err(RegistryError::UnknownMetric { name, .. }) => assert_eq!(name, "sharpe"),
             other => panic!("expected UnknownMetric, got {other:?}"),
         }
     }
@@ -1589,8 +1544,8 @@ mod tests {
         let fam = fixture_family_with_r();
         let (winner, sel) = optimize_deflated(&fam, "sqn_normalized", 200, 3, 1).unwrap();
         assert_eq!(sel.n_trials, fam.points.len());
-        let m = resolve_metric("sqn_normalized").unwrap();
+        let m = <RunMetrics as MetricVocabulary>::resolve("sqn_normalized").unwrap();
-        assert_eq!(sel.raw_winner_metric, metric_value(&winner.report, m));
+        assert_eq!(sel.raw_winner_metric, winner.report.metrics.value(m));
     }
 
     /// A 1-D grid (7 cells, odometer order) with two end spikes and a broad middle
@@ -2373,7 +2328,7 @@ mod tests {
             other => panic!("expected NonRMetric, got {other:?}"),
         }
         match check_r_metric("nope") {
-            Err(RegistryError::UnknownMetric(m)) => assert_eq!(m, "nope"),
+            Err(RegistryError::UnknownMetric { name, .. }) => assert_eq!(name, "nope"),
             other => panic!("expected UnknownMetric, got {other:?}"),
         }
     }