feat(8.0): API simplification — remove neural()/Db.search, one storage path key, integration→0

8.0 RC cleanup toward "one place per thing, zero-config, no deprecation":

- Remove the `brain.neural()` clustering namespace (ImprovedNeuralAPI + the dead
  legacy NeuralAPI + the neural CLI + neural-only types). Similarity is `find({vector})`
  / `similar({to})`; attribute grouping is the aggregation `GROUP BY` engine. The separate
  entity-extraction / smart-import feature (NeuralImport, NeuralEntityExtractor, SmartExtractor,
  NaturalLanguageProcessor, `brain.extract()`/`brain.nlp()`) is kept.
- Remove `Db.search()`; `find()` is the one query verb (accepts a bare string or FindParams).
  Fix the bundled MCP client, which called a non-existent `brain.search(query, limit)` →
  now `find({ query, limit })`.
- Storage config: collapse to one canonical top-level `path` key. The pre-8.0 aliases
  (`rootDirectory`, `options.*`, `fileSystemStorage.*`) are removed and now THROW with the
  exact rename instead of silently defaulting to `./brainy-data` on upgrade. A single resolver
  feeds createStorage, the 7.x→8.0 migration probe, and the plugin-factory handoff, so a native
  storage provider resolves the identical root (no split-brain).
- Fix `similar({ threshold })`: the min-similarity filter was silently dropped; it is now
  applied as a post-filter on `result.score` (the documented way to bound semantic results).
- Fix `vfs.rename()` on a directory: child path updates spread the entity vector into `update()`
  and failed dimension validation; they are metadata-only updates now.
- Fix `vfs.move()`: copy+delete orphaned the content-addressed content blob (the destination
  shared the source hash, then unlink removed it). `move()` now delegates to `rename()` — an
  in-place path change that preserves the blob and the entity id, for files and directories.
- Fix streaming import: the bulk fast path never flushed mid-import nor signalled queryability.
  Entity writes are now chunked by a progressive flush interval (100 → 1000 → 5000); each chunk
  flushes and emits `progress.queryable`, so imported data is queryable during the import.
- Sweep all docs, comments, and JSDoc for the removed/changed APIs.

Integration suite: 49 files / 588 passed / 0 failed. Unit: 80 files / 1456 passed, no type errors.

docs/SCALING.md

@@ -20,7 +20,7 @@ const brain = new Brainy({ storage: { type: 'memory' } })
 ### On-Disk (Default for Node)
 ```typescript
 const brain = new Brainy({
-  storage: { type: 'filesystem', rootDirectory: './brainy-data' }
+  storage: { type: 'filesystem', path: './brainy-data' }
 })
 ```
 
@@ -88,11 +88,11 @@ match-set size and is the path to move onto the native provider first._
 const brain = new Brainy({
   storage: {
     type: 'filesystem',
-    rootDirectory: '/var/lib/brainy'
+    path: '/var/lib/brainy'
   }
 })
 ```
-- Stores everything in a sharded JSON tree under `rootDirectory`
+- Stores everything in a sharded JSON tree under `path`
 - Atomic writes via rename
 - Survives process restarts
 - Snapshot it off-site with `gsutil rsync`, `aws s3 sync`, `rclone`, or `tar` from your scheduler
@@ -108,10 +108,10 @@ const brain = new Brainy({ storage: { type: 'memory' } })
 ### Auto
 ```typescript
 const brain = new Brainy({
-  storage: { type: 'auto', rootDirectory: './data' }
+  storage: { type: 'auto', path: './data' }
 })
 ```
-- Picks `filesystem` when running on Node with a writable `rootDirectory`
+- Picks `filesystem` when running on Node with a writable `path`
 - Falls back to `memory` otherwise
 
 ## Scaling Patterns
@@ -125,7 +125,7 @@ const brain = new Brainy({ storage: { type: 'memory' } })
 ### Stage 2: Production (Filesystem)
 ```typescript
 const brain = new Brainy({
-  storage: { type: 'filesystem', rootDirectory: '/var/lib/brainy' }
+  storage: { type: 'filesystem', path: '/var/lib/brainy' }
 })
 // Most production workloads up to ~10M entities on a single host
 ```
@@ -133,7 +133,7 @@ const brain = new Brainy({
 ### Stage 3: Higher Throughput (Tune the Vector Index)
 ```typescript
 const brain = new Brainy({
-  storage: { type: 'filesystem', rootDirectory: '/var/lib/brainy' },
+  storage: { type: 'filesystem', path: '/var/lib/brainy' },
   vector: {
     recall: 'fast',                // Trade recall for latency
     persistMode: 'deferred'        // Batch persistence
@@ -142,14 +142,14 @@ const brain = new Brainy({
 ```
 
 ### Stage 4: Multi-Instance (Operator-Layer)
-Run multiple Brainy processes behind your own routing/service layer. Each process owns its own `rootDirectory`. Sync each artifact off-site independently. Brainy itself does not coordinate between processes.
+Run multiple Brainy processes behind your own routing/service layer. Each process owns its own `path`. Sync each artifact off-site independently. Brainy itself does not coordinate between processes.
 
 ## Real World Examples
 
 ### Example 1: Single-Node App With Backup
 ```typescript
 const brain = new Brainy({
-  storage: { type: 'filesystem', rootDirectory: '/var/lib/brainy' }
+  storage: { type: 'filesystem', path: '/var/lib/brainy' }
 })
 ```
 Schedule (cron / systemd timer):
@@ -170,7 +170,7 @@ function brainForTenant(tenantId: string) {
   return new Brainy({
     storage: {
       type: 'filesystem',
-      rootDirectory: `/var/lib/brainy/${tenantId}`
+      path: `/var/lib/brainy/${tenantId}`
     }
   })
 }
@@ -180,7 +180,7 @@ Your service layer handles routing and isolation; Brainy stays simple.
 ### Example 4: Higher Recall at Scale
 ```typescript
 const brain = new Brainy({
-  storage: { type: 'filesystem', rootDirectory: '/var/lib/brainy' },
+  storage: { type: 'filesystem', path: '/var/lib/brainy' },
   vector: {
     recall: 'accurate'
   }
@@ -226,7 +226,7 @@ const stats = await brain.stats()
 
 ## Best Practices
 
-1. **One process = one `rootDirectory`** — never share a directory between processes
+1. **One process = one `path`** — never share a directory between processes
 2. **Snapshot from your scheduler** — Brainy doesn't ship cloud SDKs; use `rclone` / `aws s3 sync` / `gsutil`
 3. **Profile before tuning** — `recall: 'balanced'` is right for most workloads
 4. **Install the native vector provider only when measured profiling shows it pays off**
@@ -236,4 +236,4 @@ const stats = await brain.stats()
 - Brainy 8.0 is a **library**, not a cluster
 - Storage adapters: `filesystem`, `memory`, `auto`
 - Vector tuning: `recall`, `persistMode`
-- Backup is an operator-layer concern — snapshot `rootDirectory`
+- Backup is an operator-layer concern — snapshot `path`