feat: SignalExtractor — behavioral feature computation#4
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- extractFeatures() computes FeatureVector from completed session - focus_ratio: typing rhythm signals / expected buckets (capped 1.0) - revision_intensity: (undos + pauses) / duration normalised (capped 1.0) - used_ai_tools: boolean from ai_tool_opened signal presence - relative_velocity: 1.0 MVP constant (Phase 2: 30-day baseline) - Sessions under 5 minutes return focus_ratio: 0 Privacy: all computations use signal counts only. signal_value never read as string — enforced by comment + test. Tests: 9 new tests, 28/28 total passing
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What this adds
src/processor/signal-extractor.ts— SignalExtractor classtests/processor/signal-extractor.test.ts— 9 testsFeatures computed
Privacy
Tests
28/28 passing (10 anonymizer + 9 database + 9 signal-extractor)