diag(sp14 B.12): per-epoch pearl_egf_diag HEALTH_DIAG emit

Adds a new HEALTH_DIAG[{epoch}]: pearl_egf_diag line immediately after
the aux_moe block in the per-epoch metrics section of training_loop.rs.
Reads all 13 SP14 ISV slots [383..396) — α_smoothed, α_raw, β, k_aux,
k_q, var_aux, var_q, var_α, q_dis_short, q_dis_long, gate1 state,
post_open_min, lockout — via the established read_isv_signal_at pattern,
giving forensic visibility into EGF pearl state each epoch.

gate1/gate2 sigmoid outputs are intentionally omitted: recomputing them
host-side would violate feedback_no_cpu_compute_strict; the sigmoid
inputs are sufficient for a reader to infer the output values.

docs/isv-slots.md updated (Invariant 7): records B.12 HEALTH_DIAG wire-up.

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

crates/ml/src/trainers/dqn/trainer/training_loop.rs

@@ -5070,6 +5070,66 @@ impl DQNTrainer {
                 );
             }
 
+            // SP14 Layer B Task B.12 (2026-05-05): per-epoch EGF pearl diagnostic.
+            // Reads the 13 SP14 ISV slots that the EGF pearl populates each step
+            // (producers in experience_kernels.cu launched by the B.1–B.11 chain).
+            // gate1/gate2 sigmoid outputs are intentionally omitted — recomputing
+            // sigmoid host-side would violate feedback_no_cpu_compute_strict; the
+            // inputs (k_aux, k_q, q_dis_short, var_*) are sufficient for a reader
+            // to infer the sigmoid outputs and diagnose gradient-hacking events.
+            {
+                use crate::cuda_pipeline::sp14_isv_slots::{
+                    ALPHA_GRAD_SMOOTHED_INDEX, ALPHA_GRAD_RAW_INDEX,
+                    BETA_RATE_LIMITER_ADAPTIVE_INDEX,
+                    K_AUX_ADAPTIVE_INDEX, K_Q_ADAPTIVE_INDEX,
+                    AUX_DIR_ACC_VARIANCE_EMA_INDEX, Q_DISAGREEMENT_VARIANCE_EMA_INDEX,
+                    ALPHA_GRAD_RAW_VARIANCE_EMA_INDEX,
+                    Q_DISAGREEMENT_SHORT_EMA_INDEX, Q_DISAGREEMENT_LONG_EMA_INDEX,
+                    GATE1_OPEN_STATE_INDEX, AUX_DIR_ACC_POST_OPEN_MIN_INDEX,
+                    GRADIENT_HACK_LOCKOUT_REMAINING_INDEX,
+                };
+                let (
+                    alpha_smoothed, alpha_raw, beta_adaptive,
+                    k_aux_curr, k_q_curr,
+                    var_aux, var_q, var_alpha,
+                    q_dis_short, q_dis_long,
+                    gate1_state, post_open_min, lockout,
+                ) = if let Some(ref fused) = self.fused_ctx {
+                    let trainer = fused.trainer();
+                    (
+                        trainer.read_isv_signal_at(ALPHA_GRAD_SMOOTHED_INDEX),
+                        trainer.read_isv_signal_at(ALPHA_GRAD_RAW_INDEX),
+                        trainer.read_isv_signal_at(BETA_RATE_LIMITER_ADAPTIVE_INDEX),
+                        trainer.read_isv_signal_at(K_AUX_ADAPTIVE_INDEX),
+                        trainer.read_isv_signal_at(K_Q_ADAPTIVE_INDEX),
+                        trainer.read_isv_signal_at(AUX_DIR_ACC_VARIANCE_EMA_INDEX),
+                        trainer.read_isv_signal_at(Q_DISAGREEMENT_VARIANCE_EMA_INDEX),
+                        trainer.read_isv_signal_at(ALPHA_GRAD_RAW_VARIANCE_EMA_INDEX),
+                        trainer.read_isv_signal_at(Q_DISAGREEMENT_SHORT_EMA_INDEX),
+                        trainer.read_isv_signal_at(Q_DISAGREEMENT_LONG_EMA_INDEX),
+                        trainer.read_isv_signal_at(GATE1_OPEN_STATE_INDEX),
+                        trainer.read_isv_signal_at(AUX_DIR_ACC_POST_OPEN_MIN_INDEX),
+                        trainer.read_isv_signal_at(GRADIENT_HACK_LOCKOUT_REMAINING_INDEX),
+                    )
+                } else {
+                    (0.0, 0.0, 0.5, 20.0, 15.0, 0.0, 0.0, 0.0, 0.5, 0.5, 0.0, 1.0, 0.0)
+                };
+                tracing::info!(
+                    "HEALTH_DIAG[{}]: pearl_egf_diag α_smoothed={:.4} α_raw={:.4} β={:.3} \
+                     k_aux={:.2} k_q={:.2} \
+                     var_aux={:.5} var_q={:.5} var_α={:.5} \
+                     q_dis_s={:.4} q_dis_l={:.4} \
+                     gate1={} post_open_min={:.3} lockout={}",
+                    epoch,
+                    alpha_smoothed, alpha_raw, beta_adaptive,
+                    k_aux_curr, k_q_curr,
+                    var_aux, var_q, var_alpha,
+                    q_dis_short, q_dis_long,
+                    if gate1_state == 1.0 { "open" } else { "closed" },
+                    post_open_min, lockout as u32,
+                );
+            }
+
             // C1/P1: propagate health to GPU replay buffer for diversity-weighted priorities.
             {
                 let mut agent = self.agent.write().await;

docs/isv-slots.md

@@ -388,5 +388,10 @@ Producer + consumer wiring lands in B.3-B.12; B.1 is additive
 infrastructure (slot constants), B.2 wires the 11 fold-reset registry
 entries + dispatch arms — both are additive only (no behavior change).
 
+B.12 (2026-05-05) adds the per-epoch `HEALTH_DIAG[{epoch}]: pearl_egf_diag`
+emit in `training_loop.rs` reading all 13 slots. gate1/gate2 sigmoid output
+values are omitted from the emit (recomputing host-side would violate
+`feedback_no_cpu_compute_strict`); the inputs are sufficient for inference.
+
 **Spec:** `docs/superpowers/specs/2026-05-05-sp14-aux-q-wire-earned-gradient-flow.md`
 **Plan:** `docs/superpowers/plans/2026-05-05-sp14-aux-q-wire-earned-gradient-flow.md`