Tracks cards reviewed during timed study sessions, logs each session's deck, target and actual time, and card count, and exports the history to CSV.
Alternatives to LLM Review Stats Exporter
AnkiWeb addon 700044641
AI answer
Startingโฆ
Answers are generated by Claude from the catalog data and may contain mistakes.
Similar addons (found without AI)
Displays session review statistics with rating breakdowns and pie charts, tracks XP and levels gamifying reviews, and logs session history for CSV export.
Exports tag data to a CSV file showing the number of cards per tag and each tag's ease score via the Files menu.
Exports the collectionโs normal deck hierarchy as Markdown full paths, copied to the clipboard or saved as a UTF-8 file for use as LLM context or structural review.
Exports selected Anki notes as LLM-friendly structured textโcopyable or savedโpreserving field contents unchanged while including note type, deck path, and optionally tags.
Explores collection statistics by deck and tag in a tree view with selectable columns, filtering, card browsing, and CSV export of all or visible rows.
Exports a collection's complete sorted tag list as plain text to the clipboard or a UTF-8 file, preserving hierarchical tags, with customizable keyboard shortcuts.
Exports non-empty deck descriptions, with full deck paths and Markdown/HTML format markers, to the clipboard or a UTF-8 file for inspection and LLM context.
Exports decks to HTML files using customizable field templates and styles, optionally converting to PDF via wkhtmltopdf, bulk-converting CSV files to multiple formats, and saving settings for reuse.
Tracks review history to rank your most-frequently missed cards by tag or deck, with time-frame and parent-tag filters, and double-click access to open cards in Anki's Browser.
Exports a field and tag legend stored as an HTML comment in a card template, copying it to the clipboard or saving it as a text file.
Generates an HTML dashboard summarizing daily, weekly, or monthly study sessions with retention, FSRS metrics, SVG growth graphs, narrative insights, and optional LLM-generated reflections from local collection data.