Anki vocab

Anki Vocab

Activation Contract

Use for the vocab mode of /learn on language-learning topics — any target language (the language named in mission.md), translated into the learner's native language (the Native language: line in mission.md, defaulting to Spanish when absent): generating a batch of Anki-importable vocabulary cards from words, phrases, or a situation/theme. Owns vocabulary.md (the learned-unit registry, from assets/vocabulary-template.md) and anki/ (batch exports, format fixture for an English-topic batch in assets/batch-format.txt) under each .ai/learning/<topic-slug>/.

Do not use for non-language topics: if mission.md shows the topic is not a language, say vocab mode only applies to language topics and ask (via native-question-ux) whether to pick a language topic or run another mode — never generate anyway. Do not create Leitner cards for exported units: Anki is their spaced-repetition system; review-queue.md stays for conceptual cues (add a vocab unit there only on explicit learner request).

Hard Rules

• Phrase as unit: every row anchors a common, natural phrase or chunk of the target language as native speakers use it — never an isolated dictionary word with a synthetic sentence.
• Situation-driven: sentences come from real situations relevant to the learner — the theme they passed, or contexts drawn from mission.md/path.md when they passed none.
• Reinforcement (i+1): build each sentence preferentially from units already in vocabulary.md and cues in review-queue.md, so one new element rides on known material. Due or recently demoted cards are preferred filler.
• No duplicates: a unit already in vocabulary.md is never re-exported as a new row's anchor (it may still appear inside other rows' sentences). Report skipped duplicates.
• Registry stays in sync: every generated batch appends its new units to vocabulary.md in the same session — an exported unit that is not registered breaks future reinforcement.
• Batch files are the one non-Markdown artifact in the learning state: plain UTF-8 .txt, exactly per the Output Format below.

Input Handling

Input after vocab	Behavior
words or phrases	One row per given unit, normalized into a natural chunk; sentences situation-grounded and reinforcement-built.
a situation/theme (e.g. "at the airport")	Select the most useful natural phrases for that situation; default batch size 12, confirmed via native-question-ux.
empty	Propose a batch: pick a situation from mission.md/path.md plus reinforcement of due/weak review-queue.md cards; confirm before generating.

Output Format

One row per card, no header line, no quoting, separator ;, five fields:

unit;meaning;part of speech;example;native translation

• unit: the phrase/word anchor, in the target language.
• meaning: short gloss of the unit, in simple target-language terms.
• part of speech: of the unit (phrase, phrasal verb, verb, noun, idiom, ...).
• example: one full natural target-language sentence using the unit in the situation.
• native translation: full-sentence translation of the example into the learner's native language from mission.md (Spanish by default; the fixture in assets/batch-format.txt shows the Spanish default).
• No ; and no double quotes inside any field — rephrase instead.
• File: .ai/learning/<topic-slug>/anki/NNNN-<batch-slug>.txt, NNNN sequential from 0001 within anki/, <batch-slug> from the theme or first unit.

Output Contract

End every batch by reporting: batch file path, row count, new units registered in vocabulary.md, duplicates skipped, a reinforcement summary (which known units were reused), and the Anki import reminder (File > Import, separator ;).