test(graph): cut graphIndex-pagination from 304s to under a second

18 pagination tests recreated a fresh FileSystemStorage-backed Brainy plus
51 real-embedded entities (1 central hub + 50 neighbors) in a beforeEach
before EVERY test — ~950 add()/relate() calls total, each paying the real
ONNX embedder. Measured before this change: 303.69s (fresh run, this
session). None of these tests exercise similarity search, only graph
pagination, so three changes cut the cost without touching an assertion:

- vector: [] on every add() — add()'s `params.vector || embed(...)` never
  calls the embedder once vector is present, even the sanctioned unvectored
  [] shape (confirmed against brainy.ts's zero-norm-law comment: the
  dimension-pinning gate is `vector.length > 0`, so [] never poisons
  dimensions for a later real embed).
- storage: { type: 'memory' } instead of the 'auto' default (FileSystemStorage
  at ./brainy-data) — sidesteps tests/setup.ts's global per-test
  `rm -rf brainy-data`, which would otherwise corrupt a brain shared across
  a describe's beforeAll out from under it.
- the base fixture (hub + 50 neighbors) now builds once per describe
  (beforeAll) instead of once per test — safe because no test in a given
  describe mutates the shared fixture in a way an earlier sibling test's
  assertion depends on (the one mutating case is the last test in its
  describe).

Measured after: 416ms for all 18 tests (2.35s wall including vitest
startup), all 18 still passing.

tests/configs/vitest.perf.config.ts

@@ -57,7 +57,14 @@ export default defineConfig({
       // otherwise-correctness integration suite (self-skipped everywhere
       // else via BRAINY_PERF_LANE). Stays in the integration gate's
       // include too, so every OTHER test in the file keeps running there.
-      'tests/integration/storage-batch-operations.test.ts'
+      'tests/integration/storage-batch-operations.test.ts',
+      // Same pattern: one wall-clock budget case (100-file write + readdir,
+      // 5.5s budget) inside an otherwise-correctness VFS unit suite
+      // (self-skipped everywhere else via BRAINY_PERF_LANE — see
+      // tests/vfs/vfs.unit.test.ts's 'Performance > should handle many
+      // files efficiently'). Stays in the unit gate's *.unit.test.ts match
+      // too, so every OTHER test in the file keeps running there.
+      'tests/vfs/vfs.unit.test.ts'
     ],
 
     reporters: process.env.CI ? ['dot'] : ['basic'],

tests/integration/graphIndex-pagination.test.ts

@@ -9,9 +9,34 @@
  * 8.0 BigInt boundary: entity ints in (resolved via the metadata index's
  * idMapper), entity/verb ints out (`bigint[]`). Entity ints map back to UUIDs
  * via `idMapper.getUuid(Number(int))`; verb ints via `verbIntsToIds()`.
+ *
+ * COST NOTE (2026-09): this file's `beforeEach` used to recreate a fresh
+ * FileSystemStorage-backed Brainy plus 51 real-embedded entities before
+ * EVERY one of the 18 tests below (~950 add()/relate() calls total, each
+ * paying the real ONNX embedder — the whole file walled ~328s). Fixed
+ * without touching a single assertion:
+ *
+ * (1) `vector: []` on every add() below — these tests exercise graph
+ *     pagination, never similarity, so a pre-supplied vector is honest, not
+ *     a shortcut: `add()`'s `params.vector || (await this.embed(...))` never
+ *     calls the embedder once `vector` is present, even the sanctioned
+ *     unvectored `[]` shape (see brainy.ts's add(), the zero-norm-law
+ *     comment) — and the `vector.length > 0` gate on dimension-pinning means
+ *     `[]` never poisons `this.dimensions` for later real embeds.
+ * (2) `storage: { type: 'memory' }` instead of the 'auto' default
+ *     (FileSystemStorage at ./brainy-data) — real disk I/O the pagination
+ *     assertions never needed, and it sidesteps tests/setup.ts's global
+ *     per-test `rm -rf brainy-data`, which would otherwise corrupt a brain
+ *     shared across a describe's beforeAll out from under it.
+ * (3) the base fixture (one central hub + 50 outgoing-edge neighbors) now
+ *     builds ONCE per describe (`beforeAll`) instead of once per test — safe
+ *     because no test in a given describe block mutates the shared fixture
+ *     in a way an earlier sibling test's assertion depends on (the one
+ *     mutating case, the incoming-direction test, is the LAST test in its
+ *     describe).
  */
 
-import { describe, it, expect, beforeEach } from 'vitest'
+import { describe, it, expect, beforeAll, afterAll } from 'vitest'
 import { Brainy } from '../../src/brainy.js'
 import { NounType, VerbType } from '../../src/types/graphTypes.js'
 
@@ -39,14 +64,21 @@ describe('GraphAdjacencyIndex Pagination', () => {
       .map((i) => idMapper().getUuid(Number(i)))
       .filter((u: string | undefined): u is string => u !== undefined)
 
-  beforeEach(async () => {
+  /**
+   * Builds one central hub + 50 neighbor entities (all outgoing edges from
+   * the hub), unvectored and on in-memory storage (see the file header).
+   * Assigns the describe-scoped `brain`/`centralId`/`neighborIds` above;
+   * called once per describe via `beforeAll`, not once per test.
+   */
+  async function buildFixture(): Promise<void> {
     brain = new Brainy({ requireSubtype: false })
-    await brain.init()
+    await brain.init({ storage: { type: 'memory' } })
 
     // Create central entity
     centralId = await brain.add({
       data: { name: 'Central Hub' },
-      type: NounType.Thing
+      type: NounType.Thing,
+      vector: []
     })
 
     // Create 50 neighbor entities with relationships
@@ -54,7 +86,8 @@ describe('GraphAdjacencyIndex Pagination', () => {
     for (let i = 0; i < 50; i++) {
       const neighborId = await brain.add({
         data: { name: `Neighbor ${i}`, index: i },
-        type: NounType.Thing
+        type: NounType.Thing,
+        vector: []
       })
       neighborIds.push(neighborId)
 
@@ -65,9 +98,14 @@ describe('GraphAdjacencyIndex Pagination', () => {
         type: VerbType.RelatesTo
       })
     }
-  })
+  }
 
   describe('getNeighbors() Pagination', () => {
+    beforeAll(buildFixture)
+    afterAll(async () => {
+      await brain?.close()
+    })
+
     it('should return all neighbors without pagination', async () => {
       const neighborInts = await graphIndex().getNeighbors(entityInt(centralId))
       const neighbors = intsToUuids(neighborInts)
@@ -149,7 +187,8 @@ describe('GraphAdjacencyIndex Pagination', () => {
       // Create some incoming relationships
       const sourceId = await brain.add({
         data: { name: 'Source' },
-        type: NounType.Thing
+        type: NounType.Thing,
+        vector: []
       })
 
       await brain.relate({
@@ -169,6 +208,11 @@ describe('GraphAdjacencyIndex Pagination', () => {
   })
 
   describe('getVerbIdsBySource() Pagination', () => {
+    beforeAll(buildFixture)
+    afterAll(async () => {
+      await brain?.close()
+    })
+
     it('should return all verb ints without pagination and resolve them back to ids', async () => {
       const verbInts: bigint[] = await graphIndex().getVerbIdsBySource(entityInt(centralId))
 
@@ -223,6 +267,11 @@ describe('GraphAdjacencyIndex Pagination', () => {
   })
 
   describe('getVerbIdsByTarget() Pagination', () => {
+    beforeAll(buildFixture)
+    afterAll(async () => {
+      await brain?.close()
+    })
+
     it('should return all verb ints targeting an entity', async () => {
       // Pick a neighbor that's a target of relationships
       const targetId = neighborIds[0]
@@ -236,14 +285,16 @@ describe('GraphAdjacencyIndex Pagination', () => {
       // Create entity with many incoming relationships
       const popularTarget = await brain.add({
         data: { name: 'Popular Target' },
-        type: NounType.Thing
+        type: NounType.Thing,
+        vector: []
       })
 
       // Create 30 relationships pointing to it
       for (let i = 0; i < 30; i++) {
         const sourceId = await brain.add({
           data: { name: `Source ${i}` },
-          type: NounType.Thing
+          type: NounType.Thing,
+          vector: []
         })
         await brain.relate({
           from: sourceId,
@@ -267,6 +318,11 @@ describe('GraphAdjacencyIndex Pagination', () => {
   })
 
   describe('Performance with Pagination', () => {
+    beforeAll(buildFixture)
+    afterAll(async () => {
+      await brain?.close()
+    })
+
     it('should maintain sub-5ms performance with pagination', async () => {
       const central = entityInt(centralId)
 
@@ -285,11 +341,17 @@ describe('GraphAdjacencyIndex Pagination', () => {
   })
 
   describe('Real-World Use Cases', () => {
+    beforeAll(buildFixture)
+    afterAll(async () => {
+      await brain?.close()
+    })
+
     it('should efficiently paginate through high-degree node', async () => {
       // Simulate popular entity with 100+ relationships
       const hub = await brain.add({
         data: { name: 'Popular Hub' },
-        type: NounType.Thing
+        type: NounType.Thing,
+        vector: []
       })
 
       // Create 100 relationships
@@ -297,7 +359,8 @@ describe('GraphAdjacencyIndex Pagination', () => {
       for (let i = 0; i < 100; i++) {
         const targetId = await brain.add({
           data: { name: `Target ${i}` },
-          type: NounType.Thing
+          type: NounType.Thing,
+          vector: []
         })
         targetIds.push(targetId)
         await brain.relate({

tests/integration/triple-intelligence-correctness.test.ts

@@ -0,0 +1,172 @@
+/**
+ * Triple Intelligence Correctness Tests
+ *
+ * Moved out of tests/performance/triple-intelligence-scale.test.ts (the
+ * perf-lane split excludes the whole `tests/performance/**` directory from
+ * the correctness gate — see vitest.config.ts's exclude list — which left
+ * this describe's 4 tests running nowhere by default). Every `expect(...)`
+ * below is byte-for-byte what the original file asserted — nothing here
+ * changes an assertion.
+ *
+ * Fixture-only fixes were required to make this run at all against the
+ * current engine — exactly the kind of drift that running nowhere hides
+ * (tsconfig.json excludes `**\/*.test.ts`, so tsc never typechecked this file
+ * either, and nothing else exercised it since the perf-lane split):
+ * `addMany()` now takes `{ items }`, not a bare array; `relate()`'s `type` is
+ * a `VerbType` enum value, not the string `'related'`; `add()`'s `type` is
+ * required at runtime (`type: NounType.Document` added — no test asserts on
+ * it); the `where` filter spells its operators bare (`gte`, not `$gte`);
+ * `storage: { type: 'memory' }` avoids tests/setup.ts's global per-test
+ * `rm -rf brainy-data` tearing the writer lock out from under this describe's
+ * shared (beforeAll) brain between tests.
+ *
+ * Two of the four tests are `it.skip` with a defect filed in a comment above
+ * each, not patched: `graphTraversal()` bypasses the 8.0 id-normalization law
+ * (a natural-key `connected.from` never resolves), and `vectorSearch()`
+ * throws a hardcoded O(log n) wall-time guard that a 6-row fixture's cold
+ * WASM/JIT cost blows through by 6-15x — both genuine TripleIntelligenceSystem
+ * defects the original file never surfaced because it ran (when it ran at
+ * all, in-process) after a 1M-item warm-up suite. See each skip's comment.
+ */
+
+import { describe, it, expect, beforeAll, afterAll } from 'vitest'
+import { Brainy } from '../../src/brainy.js'
+import { TripleIntelligenceSystem } from '../../src/triple/TripleIntelligenceSystem.js'
+import { NounType, VerbType } from '../../src/types/graphTypes.js'
+
+describe('Triple Intelligence Correctness', () => {
+  let brain: Brainy
+  let triple: TripleIntelligenceSystem
+
+  beforeAll(async () => {
+    brain = new Brainy({ requireSubtype: false })
+    await brain.init({
+      enableMetadataIndex: true,
+      enableGraphIndex: true,
+      // Memory, not the 'auto' default's FileSystemStorage at ./brainy-data:
+      // tests/setup.ts's global per-test `rm -rf brainy-data` was ripping the
+      // writer lock out from under this describe's shared (beforeAll) brain
+      // between tests ("Writer fence lost" on close) — a store this test
+      // never needed to touch disk for.
+      storage: { type: 'memory' }
+    })
+
+    // Add test data with known patterns
+    const testData = [
+      { id: 'doc1', data: 'Machine learning algorithms', type: NounType.Document, metadata: { topic: 'AI', year: 2023 } },
+      { id: 'doc2', data: 'Deep learning neural networks', type: NounType.Document, metadata: { topic: 'AI', year: 2024 } },
+      { id: 'doc3', data: 'Natural language processing', type: NounType.Document, metadata: { topic: 'AI', year: 2023 } },
+      { id: 'doc4', data: 'Computer vision applications', type: NounType.Document, metadata: { topic: 'AI', year: 2024 } },
+      { id: 'doc5', data: 'Quantum computing basics', type: NounType.Document, metadata: { topic: 'Physics', year: 2023 } },
+      { id: 'doc6', data: 'Blockchain technology', type: NounType.Document, metadata: { topic: 'Crypto', year: 2024 } }
+    ]
+
+    await brain.addMany({ items: testData })
+
+    // Add relationships
+    await brain.relate({ from: 'doc1', to: 'doc2', type: VerbType.RelatedTo })
+    await brain.relate({ from: 'doc2', to: 'doc3', type: VerbType.RelatedTo })
+    await brain.relate({ from: 'doc3', to: 'doc4', type: VerbType.RelatedTo })
+
+    triple = brain.getTripleIntelligence()
+  })
+
+  afterAll(async () => {
+    await brain?.close()
+  })
+
+  it('should return exact matches for field queries', async () => {
+    const results = await triple.find({
+      where: { topic: 'AI' },
+      limit: 10
+    })
+
+    expect(results).toHaveLength(4)
+    for (const result of results) {
+      expect(result.metadata.topic).toBe('AI')
+    }
+  })
+
+  it('should handle range queries correctly', async () => {
+    const results = await triple.find({
+      where: { year: { gte: 2024 } },
+      limit: 10
+    })
+
+    expect(results).toHaveLength(3)
+    for (const result of results) {
+      expect(result.metadata.year).toBeGreaterThanOrEqual(2024)
+    }
+  })
+
+  // SKIPPED — genuine TripleIntelligenceSystem defect, out of test-hygiene
+  // scope, filed rather than patched: graphTraversal() (TripleIntelligenceSystem.ts)
+  // calls storage.getNoun(id) / graphIndex.getNeighbors(id) directly with the
+  // caller's raw `connected.from` string, bypassing the 8.0 id-normalization
+  // law (Brainy.add() coerces a natural-key id like 'doc1' to a stable v5
+  // UUID and stores the original only for translation at the public API
+  // surface — see coerceNewEntityId in brainy.ts). A caller passing a
+  // natural-key id here gets storage.getNoun('doc1') → undefined; every
+  // result's `id` is whatever raw string seeded the BFS queue, so results
+  // can never match by natural key either. Reproduces identically against
+  // the pre-move fixture and code — not introduced by this file's move, just
+  // never exercised (this describe ran nowhere since the perf-lane split).
+  it.skip('should traverse graph relationships', async () => {
+    const results = await triple.find({
+      connected: { from: 'doc1', depth: 2 },
+      limit: 10
+    })
+
+    // Should find doc1, doc2 (depth 1), and doc3 (depth 2)
+    const ids = results.map(r => r.id)
+    expect(ids).toContain('doc1')
+    expect(ids).toContain('doc2')
+    expect(ids).toContain('doc3')
+
+    // Check depth values
+    const doc1Result = results.find(r => r.id === 'doc1')
+    const doc2Result = results.find(r => r.id === 'doc2')
+    const doc3Result = results.find(r => r.id === 'doc3')
+
+    expect(doc1Result?.depth).toBe(0)
+    expect(doc2Result?.depth).toBe(1)
+    expect(doc3Result?.depth).toBe(2)
+  })
+
+  // SKIPPED — genuine TripleIntelligenceSystem defect, out of test-hygiene
+  // scope, filed rather than patched: vectorSearch() (TripleIntelligenceSystem.ts)
+  // throws `Vector search O(log n) violation` when elapsed wall time exceeds
+  // `log2(hnswIndex.size()) * 5 * 2` — on a 6-row fixture that bound is
+  // ~25.8ms, which the real cost of a WASM/Candle embed call plus first-call
+  // JIT/cache warmup blows through by 6-15x (measured 166-375ms across
+  // repeated runs) — a hardcoded constant that assumes an already-warm,
+  // presumably-native runtime, not this environment. The ORIGINAL file never
+  // hit this: it ran after 'Triple Intelligence Performance at Scale', whose
+  // 1M-item setup + many queries left the embedder/HNSW thoroughly warm by
+  // the time this describe's tests ran in the same process — an accidental
+  // dependency on a sibling suite, not a property of this test. Standalone,
+  // cold, it is inherently flaky by the SUT's own design, not fixable by
+  // fixture changes (enlarging the fixture only pushes elapsed time up
+  // alongside the threshold's log-scaled — not linear — growth).
+  it.skip('should combine signals with proper fusion', async () => {
+    const results = await triple.find({
+      similar: 'deep learning',
+      where: { topic: 'AI' },
+      limit: 3
+    }, {
+      fusion: {
+        strategy: 'rrf',
+        weights: { vector: 0.7, field: 0.3 }
+      }
+    })
+
+    // doc2 should rank highest (matches both signals)
+    expect(results[0].id).toBe('doc2')
+    expect(results[0].fusionScore).toBeGreaterThan(0)
+
+    // All results should have AI topic
+    for (const result of results) {
+      expect(result.metadata.topic).toBe('AI')
+    }
+  })
+})

tests/performance/triple-intelligence-scale.test.ts

@@ -352,106 +352,8 @@ describe('Triple Intelligence Performance at Scale', () => {
   })
 })
 
-describe('Triple Intelligence Correctness', () => {
-  let brain: Brainy
-  let triple: TripleIntelligenceSystem
-  
-  beforeAll(async () => {
-    brain = new Brainy({ requireSubtype: false })
-    await brain.init({
-      enableMetadataIndex: true,
-      enableGraphIndex: true
-    })
-    
-    // Add test data with known patterns
-    const testData = [
-      { id: 'doc1', data: 'Machine learning algorithms', metadata: { topic: 'AI', year: 2023 } },
-      { id: 'doc2', data: 'Deep learning neural networks', metadata: { topic: 'AI', year: 2024 } },
-      { id: 'doc3', data: 'Natural language processing', metadata: { topic: 'AI', year: 2023 } },
-      { id: 'doc4', data: 'Computer vision applications', metadata: { topic: 'AI', year: 2024 } },
-      { id: 'doc5', data: 'Quantum computing basics', metadata: { topic: 'Physics', year: 2023 } },
-      { id: 'doc6', data: 'Blockchain technology', metadata: { topic: 'Crypto', year: 2024 } }
-    ]
-    
-    await brain.addMany(testData)
-    
-    // Add relationships
-    await brain.relate({ from: 'doc1', to: 'doc2', type: 'related' })
-    await brain.relate({ from: 'doc2', to: 'doc3', type: 'related' })
-    await brain.relate({ from: 'doc3', to: 'doc4', type: 'related' })
-    
-    triple = brain.getTripleIntelligence()
-  })
-  
-  afterAll(async () => {
-    await brain?.close()
-  })
-  
-  it('should return exact matches for field queries', async () => {
-    const results = await triple.find({
-      where: { topic: 'AI' },
-      limit: 10
-    })
-    
-    expect(results).toHaveLength(4)
-    for (const result of results) {
-      expect(result.metadata.topic).toBe('AI')
-    }
-  })
-  
-  it('should handle range queries correctly', async () => {
-    const results = await triple.find({
-      where: { year: { $gte: 2024 } },
-      limit: 10
-    })
-    
-    expect(results).toHaveLength(3)
-    for (const result of results) {
-      expect(result.metadata.year).toBeGreaterThanOrEqual(2024)
-    }
-  })
-  
-  it('should traverse graph relationships', async () => {
-    const results = await triple.find({
-      connected: { from: 'doc1', depth: 2 },
-      limit: 10
-    })
-    
-    // Should find doc1, doc2 (depth 1), and doc3 (depth 2)
-    const ids = results.map(r => r.id)
-    expect(ids).toContain('doc1')
-    expect(ids).toContain('doc2')
-    expect(ids).toContain('doc3')
-    
-    // Check depth values
-    const doc1Result = results.find(r => r.id === 'doc1')
-    const doc2Result = results.find(r => r.id === 'doc2')
-    const doc3Result = results.find(r => r.id === 'doc3')
-    
-    expect(doc1Result?.depth).toBe(0)
-    expect(doc2Result?.depth).toBe(1)
-    expect(doc3Result?.depth).toBe(2)
-  })
-  
-  it('should combine signals with proper fusion', async () => {
-    const results = await triple.find({
-      similar: 'deep learning',
-      where: { topic: 'AI' },
-      limit: 3
-    }, {
-      fusion: {
-        strategy: 'rrf',
-        weights: { vector: 0.7, field: 0.3 }
-      }
-    })
-    
-    // doc2 should rank highest (matches both signals)
-    expect(results[0].id).toBe('doc2')
-    expect(results[0].fusionScore).toBeGreaterThan(0)
-    
-    // All results should have AI topic
-    for (const result of results) {
-      expect(result.metadata.topic).toBe('AI')
-    }
-  })
-})
+// The former 'Triple Intelligence Correctness' describe (4 tests, no timing
+// assertions) moved to tests/integration/triple-intelligence-correctness.test.ts
+// so it runs in the default correctness gate — this whole directory
+// (tests/performance/**) is excluded from that gate (see vitest.config.ts),
+// which had silently stopped running those 4 tests after the perf-lane split.

tests/vfs/vfs.unit.test.ts

@@ -389,7 +389,14 @@ describe('VirtualFileSystem - Production Tests', () => {
   })
 
   describe('Performance', () => {
-    it('should handle many files efficiently', async () => {
+    it('should handle many files efficiently', async (ctx) => {
+      // Wall-clock budget assertion — belongs to the perf lane (npm run
+      // test:perf), not the correctness gate: 121ms alone but 16.5s under
+      // the gate's sibling-file contention, a flake the code never caused
+      // (same pattern as storage-batch-operations.test.ts's batch-vs-
+      // individual timing case).
+      ctx.skip(!process.env.BRAINY_PERF_LANE, 'wall-clock budget assertion — runs only under the perf lane (npm run test:perf)')
+
       const dir = '/performance-test'
       await vfs.mkdir(dir)