feat: add thinking token extraction (#798)

* feat: add thinking token tracking and historical analytics

- extractThinkingTokens(): separate thinking from output tokens
- TokenUsageTracker class for historical analytics
- Track: cache hit rate, most used model, requests per hour/day
- Analytics: average tokens per request, totals
- Add tests (7 passing)

PR 4B: Features 1.10 + 1.11

* refactor: extract thinking and analytics to separate files

- Create thinkingTokenExtractor.ts with ThinkingTokenAnalyzer
- Create tokenAnalytics.ts with TokenUsageTracker
- Add production-grade methods and tests
- Update test imports

src/utils/tokenAnalytics.test.ts

@@ -0,0 +1,84 @@
+import { describe, expect, it, beforeEach } from 'bun:test'
+import { TokenUsageTracker } from './tokenAnalytics.js'
+
+describe('TokenUsageTracker', () => {
+  let tracker: TokenUsageTracker
+
+  beforeEach(() => {
+    tracker = new TokenUsageTracker(100)
+  })
+
+  it('records token usage', () => {
+    tracker.record({
+      input_tokens: 1000,
+      output_tokens: 500,
+      cache_read_input_tokens: 200,
+      cache_creation_input_tokens: 100,
+      model: 'claude-sonnet-4-5-20250514',
+    })
+
+    expect(tracker.size).toBe(1)
+  })
+
+  it('calculates analytics', () => {
+    tracker.record({
+      input_tokens: 1000,
+      output_tokens: 500,
+      model: 'claude-sonnet-4-5-20250514',
+    })
+
+    tracker.record({
+      input_tokens: 2000,
+      output_tokens: 300,
+      model: 'claude-sonnet-4-5-20250514',
+    })
+
+    const analytics = tracker.getAnalytics()
+
+    expect(analytics.totalRequests).toBe(2)
+    expect(analytics.totalInputTokens).toBe(3000)
+    expect(analytics.totalOutputTokens).toBe(800)
+    expect(analytics.averageInputPerRequest).toBe(1500)
+    expect(analytics.averageOutputPerRequest).toBe(400)
+  })
+
+  it('tracks cache hit rate', () => {
+    tracker.record({
+      input_tokens: 1000,
+      output_tokens: 500,
+      cache_read_input_tokens: 500, // 33% cache
+      model: 'claude-sonnet-4-5-20250514',
+    })
+
+    const analytics = tracker.getAnalytics()
+
+    expect(analytics.cacheHitRate).toBeGreaterThan(0)
+  })
+
+  it('tracks most used model', () => {
+    tracker.record({ input_tokens: 1000, output_tokens: 100, model: 'sonnet' })
+    tracker.record({ input_tokens: 1000, output_tokens: 100, model: 'sonnet' })
+    tracker.record({ input_tokens: 1000, output_tokens: 100, model: 'opus' })
+
+    expect(tracker.getAnalytics().mostUsedModel).toBe('sonnet')
+  })
+
+  it('respects max entries limit', () => {
+    const smallTracker = new TokenUsageTracker(3)
+
+    smallTracker.record({ input_tokens: 1, output_tokens: 1, model: 'a' })
+    smallTracker.record({ input_tokens: 2, output_tokens: 2, model: 'b' })
+    smallTracker.record({ input_tokens: 3, output_tokens: 3, model: 'c' })
+    smallTracker.record({ input_tokens: 4, output_tokens: 4, model: 'd' })
+    smallTracker.record({ input_tokens: 5, output_tokens: 5, model: 'e' })
+
+    expect(smallTracker.size).toBe(3)
+  })
+
+it('clears history', () => {
+      tracker.record({ input_tokens: 1000, output_tokens: 100, model: 'test' })
+      tracker.clear()
+
+      expect(tracker.size).toBe(0)
+    })
+})