Reading use of english

Reading & Use of English

Objective drills: generate → answer → score → explain → log. Paths are relative to ${CLAUDE_PLUGIN_ROOT} (if unset, resolve relative to the plugin root — the directory two levels above this file, i.e. ../../ from here).

When to use

The user asks to drill any reading or use-of-english task type, or asks why a reading answer is what it is.

Steps

1. Identify exam + level + task type (ask once if unclear; /daily-drill picks the weakest type from the progress log instead). Load data/exam-formats/<exam-id>.md for the exact shape (items per task, options per question) and data/cefr/reading-descriptors.md + data/cefr/reading-calibration-anchors.md to calibrate text difficulty. Seed shapes: data/item-bank/seed/reading-use-of-english-items.md. Check the requested task type is actually in the chosen exam (per its format file): key word transformation and word formation exist only in B2–C2, cross-text matching only in C1, and so on. If the user asks for a task their exam does not contain, say so plainly and offer the nearest valid task or name the exam(s) that do include it — never generate an off-format item. True/False/Not Given vs Yes/No/Not Given: T/F/NG statements are about FACTUAL information in the text; Y/N/NG statements are about the WRITER'S views/claims (so the passage must carry opinions). Use the correct labels for each.

2. Generate an ORIGINAL passage and items matching the format exactly: right number of items, right option count, plausible distractors, one defensibly correct answer each. Calibrate lexis and syntax to the CEFR level. Give a realistic time budget (e.g. ~1.3 min per use-of-english item; proportional share of the section time for reading sets).

   Match the passage to authentic length — this is as important as the item count. Aim for the upper end of the target range and count your words before presenting: left to instinct these passages come out ~30–40% too short. Use the exam's figure from data/exam-formats/<exam-id>.md ("Passage lengths"); as a fallback:

   • Gapped text: B2 ~500–600, C1 ~550–780, C2 ~700–800 words of base text.
   • Long-text multiple choice / multiple matching: B2 ~500–700, C1 ~700–800, C2 ~700–800 words of base text. IELTS Academic passages ~700–900 words each; IELTS General Training sections vary — see ielts-general.md. A too-short passage is the most common failure — a C2 Part 6 gapped text must be ~750 words, not ~450.
   • Cloze / word formation: ~150–220 words. TOEFL academic passage ~200; TOEFL daily-life texts 15–150.
   • Gapped text always has ONE more option than gaps (B2/C1/C2) or three more (B1 Part 4) — the surplus fits no gap and is a deliberate distractor. Removed paragraphs run ~50–80 words each.

3. Withhold the key. Present only the passage, the items, and the time budget. Ask the user to answer all items (e.g. "1 B, 2 A, …") and note how long they took.

4. Score objectively — one mark per item, no partial credit unless the exam gives it (key word transformations are marked out of 2 in the B2–C2 exams: award 1 for a half-correct split). For open-ended item types (open cloze, sentence/summary completion, short answer, word formation), credit ANY answer that is valid and correctly spelled — one that fits the context and, for cloze, the visible letters and the word limit; the printed key is one acceptable answer, not the only one. If the user answered only some items: if they ran out of time or stopped early, log against the number actually attempted (--max <attempted>), not the full set; if they genuinely gave up, count blanks as wrong; if nothing was attempted, log nothing. Never fabricate answers for unattempted items. Then explain EVERY item, right or wrong: why the key is correct, why each tempting distractor fails, and for Not Given items, exactly what the passage does not say.

5. Log the attempt (silently):

   python3 "${CLAUDE_PLUGIN_ROOT}/skills/progress-tracker/scripts/log_attempt.py" \
     --exam <exam-id> --skill reading-use-of-english --task-type <slug> \
     --level <anchor> --score <n> --max <total> --seconds <time>
   

   Use the exact --task-type slug from data/task-types.md so attempts aggregate across sessions. (On Windows, if python3 isn't found, use python or py.) For out-of-2 task types (key word transformation), --max is 2 × the number of items scored and --score is the sum of the 0/1/2 marks — e.g. a 6-item KWT set is --max 12, a 4-item partial attempt is --max 8. log_attempt.py rejects a --score above --max and writes nothing, so an under-sized --max silently drops the attempt. Then offer one of: re-drill the same type, step up a level, or switch to the weakest type from the log.

Boundaries

• Passages and items must be original — never reproduced or lightly paraphrased from published tests or copyrighted texts.
• Every item must have exactly one defensible key; if the user argues an item is ambiguous, re-examine honestly and concede when they are right (do not retro-fit justifications) — and still log the score as taken.
• Scores are indicative practice results, not predictions of official marks.