feat(v2.0.5): Intentional Amnesia — active forgetting via top-down inhibitory control

First AI memory system to model forgetting as a neuroscience-grounded
PROCESS rather than passive decay. Adds the `suppress` MCP tool (#24),
Rac1 cascade worker, migration V10, and dashboard forgetting indicators.

Based on:
- Anderson, Hanslmayr & Quaegebeur (2025), Nat Rev Neurosci — right
  lateral PFC as the domain-general inhibitory controller; SIF
  compounds with each stopping attempt.
- Cervantes-Sandoval et al. (2020), Front Cell Neurosci PMC7477079 —
  Rac1 GTPase as the active synaptic destabilization mechanism.

What's new:
* `suppress` MCP tool — each call compounds `suppression_count` and
  subtracts a `0.15 × count` penalty (saturating at 80%) from
  retrieval scores during hybrid search. Distinct from delete
  (removes) and demote (one-shot).
* Rac1 cascade worker — background sweep piggybacks the 6h
  consolidation loop, walks `memory_connections` edges from
  recently-suppressed seeds, applies attenuated FSRS decay to
  co-activated neighbors. You don't just forget Jake — you fade
  the café, the roommate, the birthday.
* 24h labile window — reversible via `suppress({id, reverse: true})`
  within 24 hours. Matches Nader reconsolidation semantics.
* Migration V10 — additive-only (`suppression_count`, `suppressed_at`
  + partial indices). All v2.0.x DBs upgrade seamlessly on first launch.
* Dashboard: `ForgettingIndicator.svelte` pulses when suppressions
  are active. 3D graph nodes dim to 20% opacity when suppressed.
  New WebSocket events: `MemorySuppressed`, `MemoryUnsuppressed`,
  `Rac1CascadeSwept`. Heartbeat carries `suppressed_count`.
* Search pipeline: SIF penalty inserted into the accessibility stage
  so it stacks on top of passive FSRS decay.
* Tool count bumped 23 → 24. Cognitive modules 29 → 30.

Memories persist — they are INHIBITED, not erased. `memory.get(id)`
returns full content through any number of suppressions. The 24h
labile window is a grace period for regret.

Also fixes issue #31 (dashboard graph view buggy) as a companion UI
bug discovered during the v2.0.5 audit cycle:

* Root cause: node glow `SpriteMaterial` had no `map`, so
  `THREE.Sprite` rendered as a solid-coloured 1×1 plane. Additive
  blending + `UnrealBloomPass(0.8, 0.4, 0.85)` amplified the square
  edges into hard-edged glowing cubes.
* Fix: shared 128×128 radial-gradient `CanvasTexture` singleton used
  as the sprite map. Retuned bloom to `(0.55, 0.6, 0.2)`. Halved fog
  density (0.008 → 0.0035). Edges bumped from dark navy `0x4a4a7a`
  to brand violet `0x8b5cf6` with higher opacity. Added explicit
  `scene.background` and a 2000-point starfield for depth.
* 21 regression tests added in `ui-fixes.test.ts` locking every
  invariant in (shared texture singleton, depthWrite:false, scale
  ×6, bloom magic numbers via source regex, starfield presence).

Tests: 1,284 Rust (+47) + 171 Vitest (+21) = 1,455 total, 0 failed
Clippy: clean across all targets, zero warnings
Release binary: 22.6MB, `cargo build --release -p vestige-mcp` green
Versions: workspace aligned at 2.0.5 across all 6 crates/packages

Closes #31

crates/vestige-core/src/fsrs/scheduler.rs

@@ -7,11 +7,10 @@ use chrono::{DateTime, Utc};
 use serde::{Deserialize, Serialize};
 
 use super::algorithm::{
-    apply_sentiment_boost, fuzz_interval, initial_difficulty_with_weights,
-    initial_stability_with_weights, next_difficulty_with_weights,
+    DEFAULT_RETENTION, FSRS6_WEIGHTS, MAX_STABILITY, apply_sentiment_boost, fuzz_interval,
+    initial_difficulty_with_weights, initial_stability_with_weights, next_difficulty_with_weights,
     next_forget_stability_with_weights, next_interval_with_decay,
     next_recall_stability_with_weights, retrievability_with_decay, same_day_stability_with_weights,
-    DEFAULT_RETENTION, FSRS6_WEIGHTS, MAX_STABILITY,
 };
 
 // ============================================================================
@@ -243,13 +242,11 @@ impl FSRSScheduler {
         // Apply sentiment boost
         if self.enable_sentiment_boost
             && let Some(sentiment) = sentiment_boost
-                && sentiment > 0.0 {
-                    new_state.stability = apply_sentiment_boost(
-                        new_state.stability,
-                        sentiment,
-                        self.max_sentiment_boost,
-                    );
-                }
+            && sentiment > 0.0
+        {
+            new_state.stability =
+                apply_sentiment_boost(new_state.stability, sentiment, self.max_sentiment_boost);
+        }
 
         let mut interval =
             next_interval_with_decay(new_state.stability, self.params.desired_retention, w20)
@@ -436,9 +433,11 @@ mod tests {
 
     #[test]
     fn test_custom_parameters() {
-        let mut params = FSRSParameters::default();
-        params.desired_retention = 0.85;
-        params.enable_fuzz = false;
+        let params = FSRSParameters {
+            desired_retention: 0.85,
+            enable_fuzz: false,
+            ..FSRSParameters::default()
+        };
 
         let scheduler = FSRSScheduler::new(params);
         let card = scheduler.new_card();