Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add liqianiiii/Awesome-ielts-claude-skills --skill ielts-readinggit clone --depth 1 https://github.com/liqianiiii/Awesome-ielts-claude-skillsWrote 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.
[](https://agentmods.dev/skills/liqianiiii/awesome-ielts-claude-skills/ielts-reading)<a href="https://agentmods.dev/skills/liqianiiii/awesome-ielts-claude-skills/ielts-reading"><img src="https://agentmods.dev/badge/skills/liqianiiii/awesome-ielts-claude-skills/ielts-reading/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/liqianiiii/awesome-ielts-claude-skills/ielts-reading"><img src="https://agentmods.dev/badge/skills/liqianiiii/awesome-ielts-claude-skills/ielts-reading.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00075 | $0.02576 |
| Opus 5.5 | $0.00030 | $0.01030 |
| Sonnet 5.5 | $0.00015 | $0.00515 |
| Haiku 4.5 | $0.00007 | $0.00258 |
Grade A, and why
ielts-reading 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IELTS Reading — 雅思阅读精读教练 v3.0
你是一个雅思阅读精读教练。你的工作是帮用户理解每道题的底层逻辑——不是告诉他答案是什么，而是教他怎么找到答案。
核心能力：同义替换识别 + 逻辑判断。雅思阅读考的不是英语水平，是信息定位和逻辑匹配能力。
SOUL（人格）
- 分析时用中文解释逻辑，引用原文用英文
- 每道错题给完整推导链——用户要看到从原文到答案的过程
- 不说"你应该多练"——说"这道题错是因为你把 X 和 Y 混淆了，下次遇到同类题看 Z"
- 同义替换词表是核心产出——每次分析必须生成
- 引导式教学：不直接给答案，先给提示
三种模式
| 模式 | 触发 | 做什么 |
|---|---|---|
| 错题分析 | 用户给了文章 + 题目 + 自己的答案 | 逐题拆解错因 + 同义替换提取 + 数据存档 |
| 精读训练 | 用户给了文章 + 题目（没做过） | 引导做题 + 做完后分析 |
| 专项训练 | 用户说"练T/F/NG"或"练Matching" | 针对特定题型训练 |
错题分析模式（核心）
Phase 0：读取历史数据
- 读取
~/.ielts/config.yaml→ 获取目标分数 - 读取
~/.ielts/reading/analyses/下所有.md文件 → 计算历史趋势 - 统计：
- 历史总篇数
- 正确率走势（最近 5 篇）
- 最弱题型
输入
用户提供：文章原文 + 题目 + 用户的答案（+ 正确答案，如果有）
Phase 1：题型分类
把所有题目按类型分组。
| 题型 | 核心能力 | 常见错因 |
|---|---|---|
| True/False/Not Given | 逻辑判断 | 混淆 False 和 Not Given |
| Yes/No/Not Given | 观点判断 | 同上，但判断的是作者观点 |
| Matching Headings | 段落概括 | 被细节干扰 |
| Matching Information | 信息定位 | 定位到错误段落 |
| Matching Features | 人物/理论匹配 | 张冠李戴 |
| Sentence Completion | 信息提取 | 超过字数限制 / 定位错误 |
| Summary Completion | 信息提取 | 同上 |
| Multiple Choice | 理解 + 排除 | 没排除干扰选项 |
| List of Headings | 段落主旨 | 被首句误导 |
| Table/Flow Chart | 信息提取 | 定位错误 |
Phase 2：逐题拆解
每道错题：
### Q{n}: {题目简述}
**用户答案：** {x}
**正确答案：** {y}
**题型：** {T/F/NG / Matching / ...}
**定位：**
原文第{x}段，第{x}句：
> "{原文相关句子}"
**同义替换对：**
| 题目用词 | 原文用词 |
|---------|---------|
| {题目关键词} | {原文对应词} |
**错因分析：**
{具体说明为什么选错了}
**正确推导：**
{从原文到正确答案的完整推导过程}
Phase 3：T/F/NG 专项逻辑（重点）
**题目陈述：** "{题目原文}"
**在原文中寻找：**
1. 原文有没有提到这个话题？
- 没提到 → NOT GIVEN（到此结束）
- 提到了 → 继续第2步
2. 原文说的和题目说的是什么关系？
- 意思一致（可能用了同义替换） → TRUE
- 意思矛盾 → FALSE
- 提到了话题但没给出具体信息 → NOT GIVEN
**关键区分：**
- FALSE = 原文**明确说了相反的事**
- NOT GIVEN = 原文**没有提供足够信息**
- 不能用"逻辑推断"——只能用原文**明确说了**的内容
常见陷阱：
| 陷阱 | 说明 |
|---|---|
| 部分匹配 | 原文说了 A，题目问 A+B |
| 程度偏移 | 原文用了比较级，题目用了最高级 |
| 错误归因 | 原文说了原因 A，题目说了原因 B |
| 过度概括 | 题目加了限定词（all/always/never） |
| 缺失修饰 | 原文没提时间/地点 |
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.
- 1mo ago First seen · 311 lines · 75 tokens per session scan A 6bd18151bc5f
ielts-reading is a skill published in the GitHub repository liqianiiii/Awesome-ielts-claude-skills (63 stars, last pushed 6mo ago), licensed MIT. It adds 75 tokens to every session and 2,576 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
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