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 hwl668/Scientific-learning-skills- --skill word-deep-divegit clone --depth 1 https://github.com/hwl668/Scientific-learning-skills-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.
[](https://agentmods.dev/skills/hwl668/scientific-learning-skills-/word-deep-dive)<a href="https://agentmods.dev/skills/hwl668/scientific-learning-skills-/word-deep-dive"><img src="https://agentmods.dev/badge/skills/hwl668/scientific-learning-skills-/word-deep-dive/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/hwl668/scientific-learning-skills-/word-deep-dive"><img src="https://agentmods.dev/badge/skills/hwl668/scientific-learning-skills-/word-deep-dive.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 | $0.00095 | $0.02486 |
| Opus 5 | $0.00048 | $0.01243 |
| Sonnet 5 | $0.00019 | $0.00497 |
| Haiku 4.5 | $0.00010 | $0.00249 |
Grade A, and why
word-deep-dive 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 11d 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
目标
把一个英语单词讲透，并根据目标考试给出针对性的备考建议。同时支持选择性单词记忆系统——间隔复习、薄弱追踪，不在无价值的词上浪费复习时间。
适用场景
- 阅读/做题中遇到一个词，想彻底搞懂
- 背单词时想知道"这个词和那个词到底有什么区别"
- 写作时想知道该用哪个词更准确
- 备考阶段想知道这个词会不会考、怎么考、为此我该做什么
- 希望建立自己的"主动词汇记忆库"，按间隔复习而不是一次查完就忘
Memory 系统
类型
内容记忆——存储具体单词和复习状态，使用共享复习引擎管理间隔。
存储位置
memory/word-deep-dive/words.json
复习引擎
间隔规则和复习算法见 memory/review-engine.md。本 Skill 遵循其中的：
- 间隔规则（1→2→4→8→16→32）
- 复习抽取算法（优先级排序）
- 自评机制
- 掌握标准（连续 5 次正确 = mastered）
两种记忆模式
| 模式 | 行为 | 适用场景 |
|---|---|---|
| 标记模式（默认） | 仅在单词前加 ! 时存入记忆 |
日常查词为主，只重点记忆真正需要掌握的 |
| 自动模式 | 每次查词自动存入记忆 | 集中背词阶段，查一个记一个 |
模式切换
| 用户说 | 效果 |
|---|---|
切换自动记忆 / 打开自动记忆 |
切换到自动模式 |
切换标记记忆 / 关闭自动记忆 |
切换回标记模式 |
当前记忆模式 |
显示当前模式和已存词数 |
标记语法
!complimentary → 标记模式下的存入，考试=通用
!complimentary 六级 → 存入并绑定六级
complimentary → 标记模式下仅查词不存入
自动模式下 ! 前缀仍然有效，仅用于强调。
复习功能
| 用户说 | 行为 |
|---|---|
复习单词 / 单词复习 |
按 review-engine.md 算法抽取到期词汇 |
复习全部单词 |
忽略间隔，复习全部已存词 |
复习 [考试名] 单词 |
只复习绑定到该考试的词（如 复习六级单词） |
管理命令
| 命令 | 行为 |
|---|---|
单词记忆状态 |
显示：模式、总词数、已掌握/复习中/待复习 |
单词列表 |
按考试分组列出所有已存词 |
删除单词 [word] |
从记忆中移除 |
清除 word-deep-dive 记忆 |
删除 memory/word-deep-dive/（二次确认） |
输入判断
解析规则
首先判断用户意图：
是查词请求？ → 解析单词和考试，输出词典卡片
是记忆命令？ → 执行对应操作（切换模式/复习/管理）
查词格式：
| 输入 | 解析 |
|---|---|
undermine |
查词，通用模式。标记模式下不存入记忆 |
!undermine |
查词 + 存入记忆。自动模式下仅强调 |
undermine 六级 |
查词，考试=六级 |
!undermine 六级 |
查词 + 存入记忆，绑定六级 |
支持的考试：六级、考研、雅思、托福、GRE、专四、专八、高考。
上下文判断
- 如果用户同时给了上下文（如一个句子），优先基于上下文解释该义项。
- 如果这个词和记忆中已有的词有派生/近义/形近关系，自动关联提示。
执行流程
解析输入 → 判断意图
├─ 记忆命令 → 执行模式切换/复习/管理 → 结束
└─ 查词请求 → 词典卡片输出 → (存入记忆?) → 完成
查词卡片流程：
解析（单词 + 考试 + 是否存入） → 多义项展开 → 用法搭配 → 词根词缀派生 → 形近词辨析 → 近义词梯度 → 反义词 → 针对性考法 → 备考建议 → 常见误区 → 记忆锚点 → 记忆状态标记
1. 多义项展开
按使用频率从高到低排列义项。每个义项给出：中文含义、英文释义、典型例句。
如果义项之间有逻辑引申关系，用 → 标注。如果指定了考试，标注各义项的考查频率。
2. 用法搭配
列出最常见的 2-4 个搭配/句型，标注语域。如果指定了考试，优先列出该考试中出现的搭配。
3. 词根词缀派生
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.
- 11d ago First seen · 254 lines · 95 tokens per session scan A c30f384e0be1
word-deep-dive is a skill published in the GitHub repository hwl668/Scientific-learning-skills- (13 stars, last pushed 1mo ago), licensed MIT. It adds 95 tokens to every session and 2,486 once invoked, about $0.0005 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 2026-08-30.
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