/** * Hooks Intelligence Learning — Audit Fix Smoke Tests * * AUDIT FINDINGS #4 & #5: * (A) hooks_intelligence_trajectory-end must feed the EWC consolidator a * gradient derived from the trajectory's REAL embedding (via * generateEmbedding) — NOT a synthetic sine wave. If no real embedding is * available, it must SKIP the EWC update rather than inject noise. * (B) hooks_intelligence_learn must actually TRIGGER a real learning/ * consolidation cycle (distillLearning), not merely echo stats. * * These tests isolate the handlers with mocks so no real DB/ONNX is required. */ import { describe, it, expect, vi, beforeEach } from 'vitest'; // --- Mocks (must be declared before importing the module under test) --- // Capture the gradient passed to EWC so we can assert it is the real embedding. const recordGradient = vi.fn(); const getConsolidationStats = vi.fn(() => ({ avgPenalty: 0.42, consolidationCount: 1, highImportancePatterns: 0, totalPatterns: 1, })); vi.mock('../src/memory/ewc-consolidation.js', () => ({ getEWCConsolidator: vi.fn(async () => ({ recordGradient, getConsolidationStats, })), })); // SONA optimizer present and "learns" so the success branch runs. vi.mock('../src/memory/sona-optimizer.js', () => ({ getSONAOptimizer: vi.fn(async () => ({ processTrajectoryOutcome: vi.fn(() => ({ learned: true, patternKey: 'pattern-x', confidence: 0.9, })), getStats: vi.fn(() => ({ totalPatterns: 3, successfulRoutings: 2, failedRoutings: 1, trajectoriesProcessed: 3, avgConfidence: 0.7, })), })), })); // REAL embedding signal — a distinctive vector that is clearly NOT a sine wave. const REAL_EMBEDDING = new Array(384).fill(0).map((_, i) => (i % 2 === 0 ? 0.5 : 0.25)); vi.mock('../src/memory/memory-initializer.js', () => ({ generateEmbedding: vi.fn(async () => ({ embedding: REAL_EMBEDDING, dimensions: REAL_EMBEDDING.length, model: 'mock-onnx', })), // storeEntry must succeed so the success/learning branch (which contains the // EWC update) is reached in trajectory-end. storeEntry: vi.fn(async () => ({ success: true, id: 'mock-trajectory-id' })), })); // Intelligence layer — distillLearning is the real DISTILL+CONSOLIDATE path. const distillLearning = vi.fn(async () => ({ patternsDistilled: 5, ewcPenalty: 0.13 })); const runBackgroundLearning = vi.fn(async () => {}); vi.mock('../src/memory/intelligence.js', () => ({ distillLearning, runBackgroundLearning, })); // graph-edge-writer is fire-and-forget; stub it. vi.mock('../src/memory/graph-edge-writer.js', () => ({ insertGraphEdge: vi.fn(async () => {}), })); import { hooksTrajectoryStart, hooksTrajectoryStep, hooksTrajectoryEnd, hooksIntelligenceLearn, } from '../src/mcp-tools/hooks-tools.js'; import { generateEmbedding } from '../src/memory/memory-initializer.js'; describe('AUDIT FIX #4 — trajectory-end feeds REAL embedding gradient to EWC', () => { beforeEach(() => { recordGradient.mockClear(); (generateEmbedding as ReturnType).mockClear(); }); it('records a gradient equal to the real trajectory embedding, not a sine wave', async () => { const started = (await hooksTrajectoryStart.handler({ task: 'do work', agent: 'coder' })) as any; const trajectoryId = started.trajectoryId as string; await hooksTrajectoryStep.handler({ trajectoryId, action: 'edit-file', result: 'ok', quality: 0.9 }); const ended = (await hooksTrajectoryEnd.handler({ trajectoryId, success: true })) as any; // generateEmbedding was used to derive the gradient (mirrors DISTILL path) expect(generateEmbedding).toHaveBeenCalledTimes(1); // EWC received the REAL embedding, not synthetic noise expect(recordGradient).toHaveBeenCalledTimes(1); const passedGradient = recordGradient.mock.calls[0][1] as number[]; expect(passedGradient).toEqual(REAL_EMBEDDING); // Guard: the OLD synthetic gradient was sin(i*0.01)*(steps/10). With 1 step // that produced values like sin(0)=0, sin(0.01)*0.1 ~= 0.001 — confirm the // gradient is NOT that degenerate sine sequence. expect(passedGradient[0]).not.toBeCloseTo(Math.sin(0) * (1 / 10), 6); expect(passedGradient[1]).not.toBeCloseTo(Math.sin(0.01) * (1 / 10), 6); expect(ended.learning.ewcConsolidation).toBe(true); }); it('SKIPS the EWC update (no synthetic gradient) when no real embedding is available', async () => { (generateEmbedding as ReturnType).mockResolvedValueOnce({ embedding: [], dimensions: 0, model: 'none', }); const started = (await hooksTrajectoryStart.handler({ task: 'task2', agent: 'coder' })) as any; const trajectoryId = started.trajectoryId as string; await hooksTrajectoryStep.handler({ trajectoryId, action: 'a', result: 'ok' }); const ended = (await hooksTrajectoryEnd.handler({ trajectoryId, success: true })) as any; // No gradient recorded — we skip rather than inject noise. expect(recordGradient).not.toHaveBeenCalled(); expect(ended.learning.ewcConsolidation).toBe(false); }); }); describe('AUDIT FIX #5 — hooks_intelligence_learn actually triggers a learning cycle', () => { beforeEach(() => { distillLearning.mockClear(); runBackgroundLearning.mockClear(); }); it('calls the real distillLearning (DISTILL+CONSOLIDATE) path, not just stats echo', async () => { const result = (await hooksIntelligenceLearn.handler({ consolidate: true })) as any; expect(distillLearning).toHaveBeenCalledTimes(1); expect(result.cycleTriggered).toBe(true); expect(result.patternsDistilled).toBe(5); expect(result.implementation).toBe('real-distill-consolidate'); expect(result.learned).toBe(true); }); });