reading-use-of-english

reading-use-of-english is a skill for Claude Code from OleksiiDotsenko/english-exam-coach. It costs 154 tokens per session (1,950 once invoked), scanned A, original, MIT.

A practice tool for English reading and use-of-English exam questions, where use of English means tasks such as grammar, word formation, and vocabulary in context. It supports question formats from IELTS, TOEFL iBT, and Cambridge exams.

In plain words
What is it for?
Use it to practise tasks such as matching headings, multiple choice, sentence completion, word formation, and key-word transformation, then receive scores and explanations.
Why use it?
It provides exercises matched to the selected exam instead of generating question types that the real exam does not contain.

Skill for Claude Code

Written for Claude Code: ${CLAUDE_PLUGIN_ROOT} variable.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the english-exam-coach plugin — 8 skills, 6 commands shipped together

Good fit Use it to practise tasks such as matching headings, multiple choice, sentence completion, word formation, and key-word transformation, then receive scores and explanations.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add OleksiiDotsenko/english-exam-coach
Claude Code
/plugin install english-exam-coach

Made for: Claude Code.

Or install english-exam-coach, the plugin that ships this one along with the rest of its 8 skills, 6 commands.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for reading-use-of-english

README.md
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Your own site
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Per session 154 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,950 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00154 $0.01950
Opus 5 $0.00077 $0.00975
Sonnet 5 $0.00031 $0.00390
Haiku 4.5 $0.00015 $0.00195

Measured 12d ago against content hash 7a720ceb756d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

reading-use-of-english scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/english-exam-coach/skills/reading-use-of-english/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.
    • TOEFL Complete the Words (~70 words, exactly 10 gaps): show the first 3–5 letters of each gapped word, then one underscore per missing letter, counted exactlyflow___ = flow + 3 = "flowers". Count the answer's letters and subtract the stem for every gap; an eyeballed count gives the learner a different puzzle from the key. Leave the opening sentence intact. Worked example: data/item-bank/seed/reading-use-of-english-items.md.
    • 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.

Read the full file on GitHub · 139 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 139 lines · 154 tokens per session scan A 7a720ceb756d

Subscribe to this mod's changes

reading-use-of-english is a skill published in the GitHub repository OleksiiDotsenko/english-exam-coach (8 stars, last pushed 1mo ago), licensed MIT. It adds 154 tokens to every session and 1,950 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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