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Useful tools for people who make things.

Original desktop tools selected for focused, independent work. The first release is HanziKana, an offline vocabulary trainer for Chinese and Japanese.

HanziKana green leaf app iconmacOS preview

Chinese · contextual recall

学习

xuéxí · to study; to learn

Japanese · next review

言葉

ことば · word; language

Due now
Development previewFree

HanziKana

Private, offline vocabulary practice for learners building a serious Chinese or Japanese word base—without accounts, subscriptions or cloud tracking.

Chinese
21,592
learnable units
Japanese
19,056
learnable units
Download development preview

Apple silicon · macOS 14+ · 88.7 MB disk image · not notarized

Inside HanziKana

Built around useful recall.

Vocabulary depth

40,648 learnable terms

21,592 Chinese units and 19,056 Japanese units in frequency-ranked study queues.

Private by design

No account. No cloud.

Lessons, search, progress and spaced review remain on your Mac with no runtime network dependency.

Built for recall

Study what is due

Context starters lead into direct recall, scheduling missed items sooner and spacing successful reviews.

What is included

  • 120 original contextual starter exercises across Chinese and Japanese
  • Frequency-ranked direct-recall study after the starter set
  • Offline dictionary search, spaced review and progress dashboards
  • System text-to-speech using voices installed on your Mac

Install the preview

  1. Download and open the disk image.
  2. Move HanziKana Studio to your Applications folder.
  3. Keep your exported progress backups before replacing a preview build.

Preview notes

Honest about what ships today.

This is an ad-hoc-signed development build for testing, not the final notarized commercial release. macOS may warn before opening software that has not completed Apple's notarization process.

Vocabulary breadth extends beyond intermediate, but HanziKana does not claim to provide a complete fluency curriculum. Grammar sequencing, broader contextual practice and native-speaker editorial review are still being expanded.

SHA-256: 0586450bfef2f266354a5f554130f101ea84765dd4f62c1ba2a49999fe94f4b7