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anki_forecast_monte_carlo() - Forecast using bootstrap
simulation with 3 methods:
weekday: Preserves day-of-week patterns
(recommended)block: Preserves temporal sequencessimple: Independent samplinganki_plot_monte_carlo() - Visualize forecasts with
confidence bands and simulation tracesanki_compare_forecasts() - Compare Monte Carlo vs
statistical methods (ARIMA, Holt-Winters)prob_above(), prob_below()), handles
irregular study habitsanki_burnout_detection() - Detect warning signs:
declining retention, increasing response time, shorter sessions, more
lapsesanki_review_quality() - Detect pattern clicking, rushed
reviews, suspicious timing, review bunchinganki_cohort_analysis() - Compare card performance by
when added (vintage analysis)anki_learning_velocity() - Track cards/day,
acceleration/deceleration, retention trendsanki_backlog_calculator() - Calculate time to clear
backlog, project backlog growth if you stopanki_gamification() - XP system, levels (Novice to
Grandmaster), 22 achievements, weekly goalsanki_streak_analytics() - Best streaks, recovery time
after breaks, weekend patterns, survival curvesanki_card_content() - Word count, cloze density,
complexity score, media usage, complexity vs retentionanki_ab_comparison() - Compare retention by note type,
deck, tag, or creation periodanki_compare_groups() - Statistical comparison of two
groups with significance testingimport_addon_export() - Import JSON exports from ankiR
Stats addonanalyze_addon_import() - Analyze imported addon
dataanki_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 valueanki_fit_forgetting_curve() - Fit power law forgetting
curve to actual review data, compare to FSRS defaultsanki_plot_forgetting_curve() - Visualization comparing
fitted curve to FSRS default with confidence intervalsanki_best_review_times() - Analyze
retention/performance by hour and weekday, identify best/worst
timesanki_session_analysis() - Identify discrete study
sessions, analyze duration/retention/fatigue patternsanki_simulate_session() - Given time budget, predict
cards completed and expected retentionanki_sibling_analysis() - Analyze how sibling cards
affect each other’s retention, statistical testinganki_interference_analysis() - Detect cards frequently
confused (co-failure patterns, content similarity)anki_weak_areas() - Identify tags/decks with lowest
retention or highest lapse ratesanki_card_recommendations() - Generate recommendations
for leeches, unsuspend candidates, cards to retireanki_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 buttonfsrs_compare_parameters() - Compare your FSRS
parameters against defaults, flag significant differencesfsrs_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 projectionsanki_response_time_outliers() - Find reviews with
suspicious times (too fast or too slow)anki_exam_readiness() - Project completion and
retention before exam date, assess risk levelanki_coverage_analysis() - Show percentage
complete/mature/retained by topicanki_study_priorities() - Identify which topics should
be prioritizedanki_study_plan() - Generate daily study plan based on
exam date and available timeanki_to_obsidian_sr() - Export to Obsidian Spaced
Repetition plugin formatanki_to_mochi() - Export to Mochi Cards JSON
formatanki_to_json() - Full collection as structured JSON for
web dashboardsanki_progress_report() - Generate shareable HTML or
Markdown progress reportanki_search_enhanced() - Advanced search with
added:, rated:, note:,
card:, prop:, re: and OR
operatorsanki_find_similar() - Find similar cards using TF-IDF,
Jaccard, or n-gram similarityanki_forecast_enhanced() - ARIMA, seasonal, and
Holt-Winters forecasting with workload ceilingsanki_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 timeanki_schema_version() - Detect Anki database schema
version for compatibility debugginganki_quick_summary() - Get a one-liner overview of your
collectionanki_today() - Detailed breakdown of today’s Anki
activityThe 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
anki_plot_heatmap() - Calendar heatmap of review
activityanki_plot_retention() - Retention rate over time with
rolling averageanki_plot_forecast() - Workload forecast chartanki_plot_difficulty() - FSRS difficulty distribution
histogramanki_plot_intervals() - Card interval distributionanki_plot_stability() - FSRS stability
distributionanki_plot_hours() - Reviews by hour of dayanki_plot_weekdays() - Reviews by day of weekanki_compare_decks() - Side-by-side deck
statisticsanki_compare_periods() - Compare two time periodsanki_compare_by_age() - Retention by card ageanki_compare_deck_difficulty() - Rank decks by
difficultyanki_benchmark() - Compare your stats to FSRS
averagesanki_time_by_hour() - Detailed hourly statisticsanki_time_by_weekday() - Statistics by day of weekanki_session_stats() - Study session analysisanki_response_time() - Response time by
difficulty/intervalanki_monthly_summary() - Monthly statisticsanki_consistency() - Study consistency metricsanki_card_complexity() - Measure card complexityanki_similar_cards() - Find potential duplicatesanki_tag_analysis() - Tag usage and retention by
taganki_empty_cards() - Find cards with empty fieldsanki_long_cards() - Find overly long cardsanki_quality_report() - Comprehensive quality
assessmentfsrs_time_to_mastery() - Estimate when deck will be
learnedfsrs_forgetting_index() - Percentage of cards below
target retentionfsrs_review_burden() - Long-term daily review workload
estimatefsrs_optimal_new_rate() - Sustainable new card rate
recommendationfsrs_simulate_new_deck() - Project workload when adding
cardsanki_dashboard() - Launch Shiny dashboard with all
analyticsanki_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
formatfsrs_from_csv() - Import review data from other
sourcesanki_export_importable() - Export to Anki-importable
formatanki_ts_intervals() - Track interval progression over
timeanki_ts_retention() - Track retention rate changesanki_ts_stability() - FSRS stability trendsanki_ts_workload() - Workload trends over timeanki_ts_learning() - New cards learned per periodanki_ts_maturation() - Card maturation trackinganki_ts_decompose() - Decompose into
trend/seasonal/residualanki_ts_anomalies() - Detect unusual study daysanki_ts_forecast() - Forecast future reviewsanki_ts_autocorrelation() - Find cyclical patternsanki_ts_plot() - Plot any time series with trendanki_cards_full() - Cards joined with notes, decks,
modelsanki_tags() - Unique tags with countsanki_field_contents() - Parse note fields into
columnsanki_stats_deck() - Per-deck statisticsanki_stats_daily() - Daily review statsanki_retention_rate() - Actual retention from
historyanki_learning_curve() - Card progression over timeanki_heatmap_data() - Calendar heatmap dataanki_streak() - Current/longest streaksanki_search() - Anki-like search syntaxanki_suspended(), anki_buried(),
anki_leeches()anki_due(), anki_new(),
anki_mature()anki_media_list(), anki_media_unused(),
anki_media_missing()anki_media_path(), anki_media_stats()fsrs_difficulty_distribution(),
fsrs_stability_distribution()fsrs_current_retrievability(),
fsrs_simulate()fsrs_workload_estimate(),
fsrs_prepare_for_optimizer()fsrs_get_parameters()anki_to_csv(), anki_report(),
anki_export_revlog(), anki_forecast()anki_decks(), anki_models(),
fsrs_interval(), date_to_anki_timestamp()anki_cards_fsrs()fsrs_retrievability() functionThese 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.
Health stats visible at Monitor.