The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

ankiR 0.6.0

Major New Features

Monte Carlo Forecasting (NEW)

• anki_forecast_monte_carlo() - Forecast using bootstrap simulation with 3 methods:
  • weekday: Preserves day-of-week patterns (recommended)
  • block: Preserves temporal sequences
  • simple: Independent sampling
• anki_plot_monte_carlo() - Visualize forecasts with confidence bands and simulation traces
• anki_compare_forecasts() - Compare Monte Carlo vs statistical methods (ARIMA, Holt-Winters)
• Features: empirical confidence intervals, probability queries (prob_above(), prob_below()), handles irregular study habits

Burnout Detection & Review Quality (NEW)

• anki_burnout_detection() - Detect warning signs: declining retention, increasing response time, shorter sessions, more lapses
• anki_review_quality() - Detect pattern clicking, rushed reviews, suspicious timing, review bunching

Cohort Analysis & Learning Velocity (NEW)

• anki_cohort_analysis() - Compare card performance by when added (vintage analysis)
• anki_learning_velocity() - Track cards/day, acceleration/deceleration, retention trends
• anki_backlog_calculator() - Calculate time to clear backlog, project backlog growth if you stop

Gamification (NEW)

• anki_gamification() - XP system, levels (Novice to Grandmaster), 22 achievements, weekly goals

Streak Analytics (NEW)

• anki_streak_analytics() - Best streaks, recovery time after breaks, weekend patterns, survival curves

Card Content Analysis (NEW)

• anki_card_content() - Word count, cloze density, complexity score, media usage, complexity vs retention

A/B Comparison (NEW)

• anki_ab_comparison() - Compare retention by note type, deck, tag, or creation period
• anki_compare_groups() - Statistical comparison of two groups with significance testing

Addon Integration (NEW)

• import_addon_export() - Import JSON exports from ankiR Stats addon
• analyze_addon_import() - Analyze imported addon data

Learning Efficiency Analysis

• anki_learning_efficiency() - Calculate learning ROI (successful retention per time, efficiency ratio, learning points per minute)
• anki_retention_by_type() - Break down retention by card characteristics (cloze vs basic, with/without media, by length, by note type)
• anki_roi_analysis() - Calculate knowledge half-life extension per study minute, cumulative retention value

Forgetting Curve Analysis

• anki_fit_forgetting_curve() - Fit power law forgetting curve to actual review data, compare to FSRS defaults
• anki_plot_forgetting_curve() - Visualization comparing fitted curve to FSRS default with confidence intervals

Optimal Review Timing

• anki_best_review_times() - Analyze retention/performance by hour and weekday, identify best/worst times
• anki_session_analysis() - Identify discrete study sessions, analyze duration/retention/fatigue patterns
• anki_simulate_session() - Given time budget, predict cards completed and expected retention

Sibling & Interference Analysis

• anki_sibling_analysis() - Analyze how sibling cards affect each other’s retention, statistical testing
• anki_interference_analysis() - Detect cards frequently confused (co-failure patterns, content similarity)
• anki_weak_areas() - Identify tags/decks with lowest retention or highest lapse rates

Actionable Recommendations

• anki_card_recommendations() - Generate recommendations for leeches, unsuspend candidates, cards to retire
• anki_health_check() - Comprehensive health check with 0-100 score (orphan cards, leech rates, missing FSRS)
• anki_summary() - One-liner overview (total cards, mature cards, due today, streak, retention)
• anki_today() - Today’s activity summary with breakdown by ease button

Extended FSRS Analysis

• fsrs_compare_parameters() - Compare your FSRS parameters against defaults, flag significant differences
• fsrs_decay_distribution() - Analyze FSRS-6 per-card decay parameter distribution (requires Anki 24.11+)
• fsrs_memory_states() - Calculate current FSRS memory state for all cards with future projections
• anki_response_time_outliers() - Find reviews with suspicious times (too fast or too slow)

Academic/Exam Preparation Tools

• anki_exam_readiness() - Project completion and retention before exam date, assess risk level
• anki_coverage_analysis() - Show percentage complete/mature/retained by topic
• anki_study_priorities() - Identify which topics should be prioritized
• anki_study_plan() - Generate daily study plan based on exam date and available time

Additional Export Formats

• anki_to_obsidian_sr() - Export to Obsidian Spaced Repetition plugin format
• anki_to_mochi() - Export to Mochi Cards JSON format
• anki_to_json() - Full collection as structured JSON for web dashboards
• anki_progress_report() - Generate shareable HTML or Markdown progress report

Enhanced Search

• anki_search_enhanced() - Advanced search with added:, rated:, note:, card:, prop:, re: and OR operators
• anki_find_similar() - Find similar cards using TF-IDF, Jaccard, or n-gram similarity

Enhanced Forecasting

• anki_forecast_enhanced() - ARIMA, seasonal, and Holt-Winters forecasting with workload ceilings
• anki_workload_projection() - Rough workload estimates with scenario comparison (for accurate FSRS simulation, use Anki’s built-in simulator or FSRS Helper add-on)
• anki_retention_stability() - Analyze how stable your retention is over time

Utilities

• anki_schema_version() - Detect Anki database schema version for compatibility debugging
• anki_quick_summary() - Get a one-liner overview of your collection
• anki_today() - Detailed breakdown of today’s Anki activity

Removed (use r-fsrs instead)

The following algorithm functions were removed - ankiR focuses on reading/analyzing data, not implementing FSRS. For FSRS algorithm, use r-fsrs: * fsrs_retrievability() - use fsrsr::fsrs_retrievability() * fsrs_interval() - use fsrsr::fsrs_next_interval() * fsrs_simulate() - use Anki’s built-in simulator * fsrs_simulate_new_deck() - use Anki’s built-in simulator * fsrs_time_to_mastery() - use Anki’s built-in simulator * fsrs_review_burden() - use Anki’s built-in simulator * fsrs_workload_estimate() - use Anki’s built-in simulator * fsrs_optimal_new_rate() - use Anki’s built-in simulator

ankiR 0.5.0

New Features

Visualization Functions

• anki_plot_heatmap() - Calendar heatmap of review activity
• anki_plot_retention() - Retention rate over time with rolling average
• anki_plot_forecast() - Workload forecast chart
• anki_plot_difficulty() - FSRS difficulty distribution histogram
• anki_plot_intervals() - Card interval distribution
• anki_plot_stability() - FSRS stability distribution
• anki_plot_hours() - Reviews by hour of day
• anki_plot_weekdays() - Reviews by day of week

Comparative Analysis

• anki_compare_decks() - Side-by-side deck statistics
• anki_compare_periods() - Compare two time periods
• anki_compare_by_age() - Retention by card age
• anki_compare_deck_difficulty() - Rank decks by difficulty
• anki_benchmark() - Compare your stats to FSRS averages

Time Analysis

• anki_time_by_hour() - Detailed hourly statistics
• anki_time_by_weekday() - Statistics by day of week
• anki_session_stats() - Study session analysis
• anki_response_time() - Response time by difficulty/interval
• anki_monthly_summary() - Monthly statistics
• anki_consistency() - Study consistency metrics

Card Quality Analysis

• anki_card_complexity() - Measure card complexity
• anki_similar_cards() - Find potential duplicates
• anki_tag_analysis() - Tag usage and retention by tag
• anki_empty_cards() - Find cards with empty fields
• anki_long_cards() - Find overly long cards
• anki_quality_report() - Comprehensive quality assessment

Predictive Features

• fsrs_time_to_mastery() - Estimate when deck will be learned
• fsrs_forgetting_index() - Percentage of cards below target retention
• fsrs_review_burden() - Long-term daily review workload estimate
• fsrs_optimal_new_rate() - Sustainable new card rate recommendation
• fsrs_simulate_new_deck() - Project workload when adding cards

Interactive Dashboard

• anki_dashboard() - Launch Shiny dashboard with all analytics

Export Formats

• anki_to_org() - Export to Emacs Org-mode (org-drill)
• anki_to_markdown() - Export to Markdown (Obsidian/Logseq/basic)
• anki_to_supermemo() - Export to SuperMemo Q&A format
• fsrs_from_csv() - Import review data from other sources
• anki_export_importable() - Export to Anki-importable format

Time Series Analysis

• anki_ts_intervals() - Track interval progression over time
• anki_ts_retention() - Track retention rate changes
• anki_ts_stability() - FSRS stability trends
• anki_ts_workload() - Workload trends over time
• anki_ts_learning() - New cards learned per period
• anki_ts_maturation() - Card maturation tracking
• anki_ts_decompose() - Decompose into trend/seasonal/residual
• anki_ts_anomalies() - Detect unusual study days
• anki_ts_forecast() - Forecast future reviews
• anki_ts_autocorrelation() - Find cyclical patterns
• anki_ts_plot() - Plot any time series with trend

ankiR 0.4.0

Features

Analytics & Statistics

• anki_cards_full() - Cards joined with notes, decks, models
• anki_tags() - Unique tags with counts
• anki_field_contents() - Parse note fields into columns
• anki_stats_deck() - Per-deck statistics
• anki_stats_daily() - Daily review stats
• anki_retention_rate() - Actual retention from history
• anki_learning_curve() - Card progression over time
• anki_heatmap_data() - Calendar heatmap data
• anki_streak() - Current/longest streaks

Search & Filter

• anki_search() - Anki-like search syntax
• anki_suspended(), anki_buried(), anki_leeches()
• anki_due(), anki_new(), anki_mature()

Media Management

• anki_media_list(), anki_media_unused(), anki_media_missing()
• anki_media_path(), anki_media_stats()

FSRS Advanced

• fsrs_difficulty_distribution(), fsrs_stability_distribution()
• fsrs_current_retrievability(), fsrs_simulate()
• fsrs_workload_estimate(), fsrs_prepare_for_optimizer()
• fsrs_get_parameters()

Export

• anki_to_csv(), anki_report(), anki_export_revlog(), anki_forecast()

ankiR 0.3.0

• anki_decks(), anki_models(), fsrs_interval(), date_to_anki_timestamp()
• FSRS-6 per-card decay parameter support
• Comprehensive test suite

ankiR 0.2.0

• FSRS parameter support via anki_cards_fsrs()
• fsrs_retrievability() function

ankiR 0.1.0

• Initial release with core functions

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.