The reworked app's learner model hangs off cards: recall evidence, the
phase-review checklist, the practice set, and the gate's "words he has
met". So every word a unit introduces has to be studiable — and 16 of the
371 were not. Eleven existed only as sentence chunks or dictionary rows
outside the review deck, and five (봐 읽어 갔어 봤어 먹었어) nowhere at all.
The build now marks exactly one reviewable lemma per roadmap word with the
unit that introduces it. Where the deck has the word, its row is chosen
deterministically (deck order, then source, then part of speech) — the
artifact tagged whichever card came last, which put the evidence for 이, 눈
and 저 on the wrong meaning. The sixteen get a `curriculum` lemma of their
own, glossed from the curated verb they conjugate (자 is "sleep", the 반말
of 자다 — not the dictionary's "ruler"), else from the sentence that uses
them, else the dictionary.
Lemmas also carry their topic, which the vocabulary filters need.
dict:assert gains the guarantee: 371/371 roadmap words as one card each.
Migration 7 adds the two columns; the rows arrive with the dictionary
reload a changed build now triggers on its own.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Cards point at lemmas by id, and an id was the entry's position in the
sorted build. One word added near the top of the dictionary would have
moved every card below it onto a different word — silently, because loaded
bands were recorded by number and a rebuilt dictionary never reached an
existing install anyway. A custom word took max(id)+1 on whichever device
added it, so the same id meant different words on a phone and a laptop.
An id is now lemmaId(headword, pos), a 53-bit hash defined once in
shared/ and used by the build, the loader, custom words and the migration.
The build asserts all 30,520 entries are collision-free, and a test pins the
function itself, since changing it re-keys every card.
Band files are format 2: they carry no ids at all. The loader derives each
id from the word, and a surface names its lemma by row index in the same
file. Writing hashed ids out cost 0.5 MB of incompressible digits; leaving
them out makes the files smaller than before (1.1 MB -> 1.0 MB).
The loaded dictionary is now versioned by its band hashes, so a rebuild
reloads on the next boot — safe only now that a reload cannot move a card.
Migration 6 re-keys an existing install without stamping anything: cards
and their tombstones move through the lemma rows still loaded, custom words
become custom_word rows (the learner's data, which can travel) carrying the
time their card was made, and the dictionary is dropped to reload.
Sync is paused until the protocol that replaces it lands: the server still
holds rows under the old ids, and exchanging them would plant cards that
name no word.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The PWA manifest declared icon-192.png, icon-512.png and favicon.svg. None
of the three existed, so install-to-home-screen and the browser tab both
resolved to nothing. That was a defect in what the last pass claimed as
done.
Drawn procedurally with Pillow rather than authored as SVG: there is no
dependable SVG rasteriser here to convert from, and ImageMagick falls back
to its MSVG renderer, which cannot be trusted with text. Pillow's
FreeType + RAQM stack shapes Hangul correctly, which is the only hard
requirement. The mark uses the app's own register — the serif face already
used for 한칸 on the boot screen, in --jade on --bg.
Two glyphs read well at 180px and up; at favicon sizes 한칸 turns to mush,
so the small sizes carry 한 alone.
icon-192 · icon-512 · apple-touch-icon (180) 한칸
icon-512-maskable 한칸 at 56%, inside
Android's circular crop
favicon.ico (16/32/48) · favicon-32 한
Sizing is a binary search on the drawn ink extent, and centring uses the ink
bounds rather than the font's line box — CJK metrics leave asymmetric space
above and below, which would otherwise sit the mark visibly high.
Re-running the generator writes byte-identical files.
Android launcher icons are untouched; Android work is out of scope.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Closes REVIEW.md §2. 167 of 371 roadmap words had no lexicon entry, so the
word rail silently showed nothing. Now:
Roadmap words: 371/371 resolve
Spiral targets: 35/35 resolve
Deck words: 386/386 resolve
and npm run dict:assert makes it a blocking build failure, not a silent
empty rail.
No runtime morphological analyser ships. lib/conjugation.js surfaceForms()
runs at BUILD time over every verb and adjective, so looking up a conjugated
form is an index hit on the surface table.
The frequency join had to be inverted. A subtitle frequency list holds
surface forms; a dictionary holds lemmas whose -다 citation form barely
occurs in running text, so joining on headword gives verbs a frequency of
roughly zero. Expanding each lemma into the forms it plausibly takes and
summing recovers 하다 from 118 to 89,041. Forms claimed by more than one
lemma are dropped rather than split, so homographs don't inherit each
other's mass. Those expansions score frequency only — the surface table
itself stays strictly surfaceForms() output plus the headword.
Bands are one per curriculum phase. Phase 1 admits no frequency band at
all: during the writing-system phase every word must be phonologically
legal for the unit reached, and a rank ceiling would hand the learner a
겹받침 during unit 1.4. shared/phonology.mjs lifts validate.mjs's own
feature ladder to enforce that; it agrees with the validator on all 371
words.
Sources are chosen automatically — KRDICT when vendored, otherwise the
kaikki.org extract. KRDICT's download is a JS form behind anti-bot
protection, so it cannot be fetched by CI; the derived band files are
committed instead, which the app needs offline regardless. Attribution and
the share-alike terms are in NOTICE.md.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
