Decks

Decks

Turn your Obsidian notes into flashcards. No special syntax. No separate deck to build.

Tag a file with #decks. Every header you wrote becomes the front of a card; every paragraph below becomes the back. Tables, image occlusion, and ==cloze== highlights work the same way. Scheduling is handled by FSRS — the modern spaced-repetition algorithm.

Discord · Release notes · Buy me a coffee

Why Decks

• Your notes are already the deck. Tag a file, every header becomes a front, every paragraph becomes a back. Coming from Anki, there's nothing to author twice.
• Four formats, no syntax to learn. Headers, two-column tables, image occlusion, and ==cloze== from highlights you already use.
• FSRS-native scheduling. Three profiles (Standard / Intensive / Trained), per-tag retention targets, no SM-2 baggage.
• Algorithm tuning. One-click optimizer trains the FSRS weights on your own review history — better scheduling for your forgetting curve, all client-side.
• Real multi-device sync. Database merges across iCloud/Dropbox automatically — review on phone and desktop, no lost history.
• Built for mobile. Touch-tuned review UI, safe-area aware, tested daily on phones.

60-second quick start

1. Install Decks from Community Plugins, enable it.

2. Open any note. Add #decks to its frontmatter or as an inline tag.

3. Write a header, then a paragraph below it. Repeat for as many cards as you want:

   ---
   tags: [decks/spanish]
   ---
   
   # What does "Hola" mean?
   
   Hello.
   
   # How do you say "Thank you" in Spanish?
   
   Gracias.
   

4. Click the brain icon in the ribbon to open the Decks panel. Click your file. Start reviewing.

The filename becomes the deck name. Cards sync automatically when you save the note.

Card formats

Decks supports four ways to write cards. Pick whichever matches how you already write notes.

---
tags: [decks/spanish]
---

# What does "Hola" mean in English?

Hello.

# How do you say "Thank you" in Spanish?

Gracias.

The filename becomes the deck name. Header level is configurable per profile.

## Concepts

| Question                | Answer                                            |
| ----------------------- | ------------------------------------------------- |
| What is photosynthesis? | The process plants use to convert sunlight        |
| Define gravity          | The force that attracts objects toward each other |

• First column = front, second column = back. Header row is ignored.
• Tables must sit directly under a header (no other paragraphs inside).
• Add a third "Notes" column for hints/mnemonics shown via toggle (press N) during review.

## The Solar System

The ==Sun== is the star at the center of our solar system. The closest planet to the Sun is ==Mercury==, and the largest planet is ==Jupiter==.

Each highlight becomes one card. During review the active blank shows as [...]; tap to reveal. Cloze also works inside table cells. Two context modes per profile (hide or show other clozes). Enabled by default.

## Bones of the arm

![[arm_bones.png]]

1. ==Humerus==
2. ==Radius==
3. ==Ulna==

Each list item is one card. The image (with its numbered labels) shows on the front; the matching item is blanked on the back. Builds on cloze, so cloze must be enabled on the profile.

Title format — the filename becomes the front, the entire file becomes the back. Set "Title" as the header level in your profile.

Reverse cards — add reverse: true to a file's frontmatter to auto-generate a reversed copy of every card. Progress is tracked separately per direction.

Per-card tags — add #tag directly in headers (e.g., ## What is photosynthesis? #plants #high-school). Tags are stripped from the displayed front, shown as chips during review, and inherited by table rows and reverse cards. Build "filter decks" that pull every card with a given tag across your vault.

What you get

• Browse mode and timed review sessions with daily limits.
• Per-tag profiles (Standard / Intensive FSRS, retention target, daily quotas).
• Custom decks built from filter rules — e.g., every card tagged #high-school.
• Statistics: heatmap, retention, future-due forecast, intervals, hourly breakdown, answer-button stats.
• Anki export, automatic backups, multi-device merge sync.
• Keyboard shortcuts: Space to flip, 1–4 to rate.

Personalized scheduling

FSRS ships with sensible defaults that work well out of the box. Once you've accumulated ~100 reviews, you can train the algorithm's 21 weights against your own review history and get card schedules tailored to your specific forgetting curve — the same kind of thing Anki desktop does, but client-side, no server, no telemetry.

Settings → Algorithm tuning → Optimize parameters. Training runs in seconds for typical decks; you'll see a before/after log-loss comparison, click Apply to use the trained weights or Discard to keep defaults. Re-train any time to refine the weights as you accumulate more reviews.

Trained weights are global but per-profile applied — pick Trained in any profile's FSRS profile dropdown to opt that profile in. Intensive profiles continue to use their sub-day defaults; existing card data is preserved through training.

The optimizer matches the open-spaced-repetition reference methodology: Adam optimizer over binary cross-entropy loss, cosine-annealed learning rate, parameter clipping against published FSRS-6 bounds. Step count scales with your review history (more reviews → more iterations).

The implementation has been validated against the published FSRS-6 spec (1396/1396 forward-pass cases match bit-exact) and benchmarked against 443M anonymized Anki reviews — calibration of shipped defaults agrees with empirical recall to within 0.8 percentage points. See docs/FSRS_OPTIMIZER.md for the full write-up: comparison with the reference benchmark, what to expect at different deck sizes, and known limitations.

Settings

Open Settings → Decks for daily limits, retention targets, search paths, session duration, and backup options. Per-tag overrides via the gear icon on any deck.

Profile settings (Manage profiles in the deck panel):

• New cards per day, review cards per day (per deck)
• Retention target (default 90%)
• FSRS profile: Standard, Intensive, or Trained (Trained available after optimizing parameters)
• Header level for parsing (or "Title" to use the filename)
• Review order: oldest due first, or random
• Cloze deletions: enabled by default
• Cloze context: hidden or open

Review settings: session duration (1–60 min), next-day rollover hour (default 4 AM), keyboard shortcuts toggle.

Parsing settings: scan the entire vault, or restrict to a folder.

Other: background refresh interval, automatic backup count, debug logging.

Release notes & support

• Release notes for each version are in release-notes/.
• Discuss on Discord — join the server.
• Support development — Buy me a coffee.

License

See LICENSE.