feat(sp13): P0a atomic — Hold-pricing + dir_acc instrumentation (additive)
Tests user's hypothesis (Hold being FREE is the bug, not Hold itself) by
pricing Hold via ISV-driven adaptive controller targeting 20% Hold-rate.
11 new SP13 ISV slots [372..383). 5 new GPU kernels:
- aux_dir_acc_reduce_kernel.cu (correct/pos_pred/pos_label/valid → 3 scalars)
- hold_rate_observer_kernel.cu (packed batch_actions decode, count(Hold)/B)
- apply_fixed_alpha_ema_kernel.cu (preserves short/long timescale split that
Wiener-optimal apply_pearls_ad_kernel would collapse)
- aux_pred_to_isv_tanh_kernel.cu (mean(tanh(aux_pred)) → ISV[375])
- 3 reward-composition sites in experience_kernels.cu subtract isv[HOLD_COST]
on Hold actions (segment_complete pre-asymmetric-cap, positioned-non-event
per-bar, flat per-bar)
Host-side controller in training_loop.rs:
excess = max(0, observed - target)
hold_cost = HOLD_COST_BASE × (1 + 5 × excess), clamped [0.5×, 5.0×base]
Per-step observer + EMA chain in gpu_experience_collector.rs after
experience_action_select. Per-epoch HEALTH_DIAG emit:
aux_dir_acc target/short/long/pred_tanh
hold_pricing observed_rate/target/cost
4-way action space stays (ExposureLevel::Hold preserved). Replay buffer /
fxcache compatibility preserved. SP11 (11/11) + SP12 (14/14) tests no
regression. SP13 P0a oracle tests: 14/14 on RTX 3050 Ti.
Spec/plan: docs/superpowers/{specs,plans}/2026-05-04-sp13-redefine-success-for-predictive-skill.md (v3)
Audit: docs/dqn-wire-up-audit.md (SP13 P0a section appended)
v2 → v3 reframe: P0a.T3 v2 implementer's audit found DirectionAction enum
doesn't exist (codebase uses 8-variant fused ExposureLevel cascading through
77 files). v3 reframes from "eliminate Hold" (250 LOC + 32-test cascade) to
"price Hold" (additive, no contract change, no cross-crate cascade).
Tension with pearl_event_driven_reward_density_alignment acknowledged in spec
— per-bar Hold cost is exposure-NEGATIVE (pulls policy AWAY from Hold-default,
inverse of the pearl's failure mode), models real economic carry, ISV-bounded
by controller. Faithful reward modeling, not artificial shaping.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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