--- id: TASK-47 title: Add Anki card quality analytics with retention correlation insights status: To Do assignee: [] created_date: '2026-02-14 02:21' labels: - feature - anki - analytics - immersion dependencies: - TASK-28 priority: low --- ## Description Analyze existing Anki cards created by SubMiner to identify which card characteristics correlate with better retention, helping users understand what makes a "good" mining card for them personally. ## Motivation Not all mined cards are equal. Some are remembered easily; others become leeches. By analyzing retention data from Anki alongside card characteristics (sentence length, word frequency, JLPT level, context richness), SubMiner can provide personalized insights about optimal mining strategies. ## Features 1. **Card retention analysis**: Query Anki for review history of SubMiner-created cards, compute retention rates 2. **Characteristic correlation**: Correlate retention with: - Sentence length (words/characters) - Target word frequency rank - Target word JLPT level - Number of unknown words in the sentence (i+N analysis) - Whether audio/screenshot was included - Source media genre/type 3. **Insights dashboard**: Show actionable insights like "Your best-retained cards have 8-15 words and 1-2 unknown words" 4. **Mining recommendations**: Real-time suggestions during mining — "This sentence has 4 unknown words; consider a simpler example" 5. **Leech prediction**: Flag newly created cards that match the profile of past leeches ## Technical considerations - Requires querying Anki review history via AnkiConnect (cardInfo, getReviewsOfCards) - Analysis can run as a background task during idle time - Results should be cached locally (SQLite via TASK-28 or separate store) - Privacy-sensitive: all analysis is local, no data leaves the machine - Consider batch analysis (run nightly or on demand) vs real-time ## Design constraints - Must not slow down the mining workflow - Insights should be actionable, not just statistical - Analysis should work with existing card format (no retroactive changes needed) ## Acceptance Criteria - [ ] #1 Retention rates are computed for SubMiner-created Anki cards via AnkiConnect. - [ ] #2 Correlations between card characteristics and retention are computed and displayed. - [ ] #3 Insights dashboard shows actionable recommendations (optimal sentence length, i+N target). - [ ] #4 Real-time mining suggestions appear when creating cards with suboptimal characteristics. - [ ] #5 Analysis runs in background without impacting mining performance. - [ ] #6 All analysis is local — no data sent externally.