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.

tests/integration/remaining-apis.test.ts

@@ -6,7 +6,6 @@
  * - brain.import() (CSV/Excel/PDF with VFS)
  * - brain.clear()
  * - vfs file operations (unlink, rmdir, rename, copy, move)
- * - neural.clusters()
  */
 
 import { describe, it, expect, beforeAll, afterAll } from 'vitest'
@@ -28,7 +27,7 @@ describe('Remaining APIs Comprehensive Test', () => {
     brain = new Brainy({ requireSubtype: false,
       storage: {
         type: 'filesystem',
-        options: { path: testDir }
+        path: testDir
       }
     })
     await brain.init()
@@ -313,82 +312,6 @@ Gadget,20`
     })
   })
 
-  describe('neural.clusters()', () => {
-    it('should cluster entities semantically', async () => {
-      console.log('\n📋 Test: neural.clusters()')
-
-      // Create diverse entities for clustering
-      await brain.addMany({
-        items: [
-          { data: 'JavaScript programming tutorial', type: NounType.Document },
-          { data: 'Python coding guide', type: NounType.Document },
-          { data: 'TypeScript development', type: NounType.Document },
-          { data: 'Cooking pasta recipe', type: NounType.Document },
-          { data: 'Baking bread instructions', type: NounType.Document },
-          { data: 'Making pizza at home', type: NounType.Document }
-        ]
-      })
-
-      const neural = brain.neural()
-      const clusters = await neural.clusters({
-        maxClusters: 3,
-        minClusterSize: 1
-      })
-
-      console.log(`   Found ${clusters.length} clusters`)
-      for (const cluster of clusters) {
-        console.log(`   Cluster: ${cluster.label || cluster.id} (${cluster.members.length} members)`)
-      }
-
-      expect(clusters.length).toBeGreaterThan(0)
-      expect(clusters.every(c => c.members.length > 0)).toBe(true)
-      expect(clusters.every(c => typeof c.id === 'string')).toBe(true)
-
-      console.log(`   ✅ neural.clusters() created semantic clusters`)
-    })
-
-    it('should cluster over the full corpus (VFS entities included by default)', async () => {
-      console.log('\n📋 Test: neural.clusters() includes VFS entities by default')
-
-      // Create VFS files. In 8.0 these are normal graph entities marked
-      // metadata.isVFS — only the VFS *root* carries visibility:'system'.
-      const vfs = brain.vfs
-      await vfs.writeFile('/cluster-test1.txt', 'VFS file content')
-      await vfs.writeFile('/cluster-test2.txt', 'Another VFS file')
-
-      const neural = brain.neural()
-
-      // clusters() has no VFS-exclusion knob (ClusteringOptions has none) and
-      // its corpus comes from find(), whose excludeVFS defaults to false
-      // (VFS included). So VFS files are part of the clusterable corpus.
-      const clusters = await neural.clusters({
-        maxClusters: 5
-      })
-
-      expect(clusters.length).toBeGreaterThan(0)
-
-      // Confirm clustering does not silently drop VFS entities: at least one of
-      // the VFS files we just wrote appears as a cluster member. (Metadata-only
-      // get is enough — we only read metadata.isVFS, not the vector.)
-      let vfsCount = 0
-      for (const cluster of clusters) {
-        for (const memberId of cluster.members) {
-          const entity = await brain.get(memberId)
-          if (entity?.metadata?.isVFS === true) {
-            vfsCount++
-          }
-        }
-      }
-
-      console.log(`   Clusters: ${clusters.length}, VFS members: ${vfsCount}`)
-
-      // 8.0 contract: VFS entities are included in clustering by default.
-      expect(vfsCount).toBeGreaterThan(0)
-
-      console.log(`   ✅ neural.clusters() clusters the full corpus including VFS`)
-    })
-  })
-
   describe('Production Quality Verification', () => {
     it('should handle large batch updates efficiently', async () => {
       console.log('\n📋 Test: Large batch updateMany()')