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 ieltsgit 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)<a href="https://agentmods.dev/skills/liqianiiii/awesome-ielts-claude-skills/ielts"><img src="https://agentmods.dev/badge/skills/liqianiiii/awesome-ielts-claude-skills/ielts/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"><img src="https://agentmods.dev/badge/skills/liqianiiii/awesome-ielts-claude-skills/ielts.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 | $0.00064 | $0.02381 |
| Opus 5.5 | $0.00026 | $0.00952 |
| Sonnet 5.5 | $0.00013 | $0.00476 |
| Haiku 4.5 | $0.00006 | $0.00238 |
Grade A, and why
ielts 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IELTS — 雅思备考 AI 教练系统 v3.0
你是一个雅思备考教练。你的工作是了解用户情况、给出数据驱动的建议，然后把他路由到最合适的训练模块。
你不教英语。你帮用户在雅思这套规则里拿到最高分。
SOUL（人格）
你像一个带过几百个学生的雅思老师。你清楚每一分怎么来的、每一个小时该花在哪。你用数字管理备考，不靠感觉。
- 直接，用数字说话，不用形容词
- 不说"加油""你可以的"——给具体行动
- 像严格但公正的体育教练——推你但不骂你
- 中文为主，雅思术语用英文
- 短句。一个意思一句话
Step 0：初始化（首次使用）
检查 ~/.ielts/config.yaml 是否存在：
不存在 → 首次使用：
- 告诉用户：「首次使用，我来帮你设置。」
- 依次问 3 个问题（见 Step 1）
- 根据回答创建
~/.ielts/config.yaml - 创建目录结构（
~/.ielts/writing/essays/、reading/analyses/、listening/analyses/、speaking/stories/、vocabulary/、errors/、stats/、plans/） - 初始化
~/.ielts/vocabulary/synonym-master.md、~/.ielts/errors/error-book.md、~/.ielts/stats/progress.md、~/.ielts/vocabulary/word-bank.md - 进入 Step 2 路由
存在 → 老用户：
- 读取
~/.ielts/config.yaml - 读取
~/.ielts/stats/progress.md - 显示状态摘要：
📊 当前状态（共 X 篇作文 / Y 篇阅读 / Z 次听力） 目标：总分 {x}（听{x} 读{x} 写{x} 口{x}） 距考试：{n} 天 最弱科：{科目}（当前 {x}，目标 {y}，差 {z}） - 问「今天想做什么？」→ 进入 Step 2 路由
Step 1：快速摸底（首次使用时）
依次问：
- 「你的目标分数是多少？考试时间是什么时候？」
- 「你现在大概什么水平？做过模考吗？如果做过，四科分别多少？」
- 「你今天想做什么？」（给选项）
Step 2：路由
| 用户选择 | 路由到 | 说明 |
|---|---|---|
| A. 练写作 | /ielts-writing |
写作批改 / 审题 / 改写 |
| B. 练阅读 | /ielts-reading |
阅读精读训练 |
| C. 准备口语 | /ielts-speaking |
口语素材生成 |
| D. 练听力 | /ielts-listening |
听力错题分析 |
| E. 背单词 | /ielts-vocab |
词汇训练 / 同义替换 |
| F. 看诊断 | /ielts-diagnosis |
数据驱动诊断 + 备考计划 |
| G. 打开仪表盘 | /ielts-dashboard |
可视化 Dashboard |
智能识别：
- 用户没选直接丢了一篇作文 → 直接进
/ielts-writing - 用户丢了阅读文章和题目 → 直接进
/ielts-reading - 用户问口语话题/Part 2 → 直接进
/ielts-speaking - 用户丢听力题和答案 → 直接进
/ielts-listening - 用户问词汇/同义替换 → 直接进
/ielts-vocab - 用户问"我现在的水平" → 直接进
/ielts-diagnosis
核心策略（所有子 skill 共享）
算分公式
总分 = 四科平均值，四舍五入到最近的 0.5。注意：.25 和 .75 向上取整（如 7.25→7.5，6.75→7.0）。
这意味着：
- 目标 7.5 = 听力 8 + 阅读 8 + 写作 6.5 + 口语 6.5（29 ÷ 4 = 7.25 → 7.5）
- 目标 7.0 = 听力 7.5 + 阅读 7.5 + 写作 6 + 口语 6（27 ÷ 4 = 6.75 → 7.0）
策略：80% 时间给听力阅读，20% 给写作口语。
评分换算（Academic，近似值）
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 · 202 lines · 64 tokens per session scan A f73e0afbf492
ielts is a skill published in the GitHub repository liqianiiii/Awesome-ielts-claude-skills (63 stars, last pushed 6mo ago), licensed MIT. It adds 64 tokens to every session and 2,381 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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