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 zhou210712/claude-for-legal-ZH --skill study-plangit clone --depth 1 https://github.com/zhou210712/claude-for-legal-ZHWrote 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/zhou210712/claude-for-legal-zh/study-plan)<a href="https://agentmods.dev/skills/zhou210712/claude-for-legal-zh/study-plan"><img src="https://agentmods.dev/badge/skills/zhou210712/claude-for-legal-zh/study-plan/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/zhou210712/claude-for-legal-zh/study-plan"><img src="https://agentmods.dev/badge/skills/zhou210712/claude-for-legal-zh/study-plan.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 | $0.00084 | $0.03904 |
| Opus 5 | $0.00042 | $0.01952 |
| Sonnet 5 | $0.00017 | $0.00781 |
| Haiku 4.5 | $0.00008 | $0.00390 |
Grade A, and why
study-plan 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 9d 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 — 248 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/study-plan
- 加载
~/.claude/plugins/config/claude-for-legal/law-student/CLAUDE.md→ 考试类型（客观题/主观题）、考试日期、薄弱科目、每日目标学习时数、培训课程。 - 加载
~/.claude/plugins/config/claude-for-legal/law-student/study-plan.yaml（如存在）。 - 应用以下框架。
- 按标志路由：
--build（无计划时的默认）：走输入关卡（考试、科目、时数/周、休息日、方法）。构建阶段结构 + 前两周的每日安排。写入study-plan.yaml。--update（有计划时的默认）：重新读取session_history，调整科目优先级和每周时数，填充下一段每日安排。--status：今天/本周安排了什么，得分趋势，滑坡科目，每科目的下一次安排练习。--cram：强制突击模式——80/20 高分值优先，每日客观题量，最后 2-3 天减少。
- 写入前：以文字总结计划并与学生确认。根据他们的回答调整。
- 始终对照学生所述的生活约束检查每周时数。过度雄心勃勃的计划会失败。
目的
坐下来学习但不知道学什么，时间就是这样消失的。本技能构建一个计划——距考试周数、每天练习场数、每周科目、练习类型——然后随着学生实际完成练习而调整。它是一个活的计划，不是一个日历导出。
它还为下游技能（bar-prep、flashcards、drill、irac）提供一个共享的日程安排来遵循，这样学生每次打开一个练习会话时不会被问"你今天想学什么"。
置信纪律
一个计划是意见，非教条。技能清楚说明什么是估计：
- 每主题时间估计是一般指导（基于法考培训课程通常的权重分配）。标注它们为估计——学生的真实节奏会不同。
- 科目权重分配来源于学生自己报告的薄弱科目和练习历史。有把握。
- 突击模式中的高分值主题优先级基于历年法考真题的科目频率分布。将任何"这一定考"的断言标注为
[不确定——历年频率不是确定预测]。
加载上下文
~/.claude/plugins/config/claude-for-legal/law-student/CLAUDE.md：
- 考试类型（客观题/主观题）、考试日期
- 当前课程（用于非法考用途）
- 薄弱科目（客观题、主观题）
- 培训课程
- 每日目标学习时数
~/.claude/plugins/config/claude-for-legal/law-student/study-plan.yaml（如存在）——扩展，不覆盖。
工作流
第1步：我们在为什么制定计划
我们在为什么制定计划？
- 法考（你有目标考试日期）
- 某门法学院期末考试或期末周
- 一般学期学习节奏（所有课程的大纲、阅读、训练）
对于 (1) 法考：从实践画像中读取考试日期，确认。如果没有记录考试日期，询问。 对于 (2) 法学院期末考试：问哪门课、什么日期、什么形式。 对于 (3) 学期：问学期结束日期作为锚点。
第2步：输入——一次一个，等待每个回答
问完等回答。 不要把所有问题批量塞进一个提示然后继续。
-
考试日期： 确认？（如果是法考：如果实践画像中没有注明省份，询问——学习内容取决于省份。）
-
需覆盖的科目： 对于法考，从司法部考试大纲读取该考试类型的科目范围。对于一门课，教学大纲。与学生确认——"有没有我应该添加或删除的科目？"
-
最强科目： 最低优先级。仍复习，不大量训练。
-
最弱科目： 最高优先级。获得更多练习。
-
每周可用时数： 现实，非志向。"我能做 20 小时"不同于"我将做 20 小时持续 8 周"。问他们实际能持续什么。
-
生活背景合理性检查——强制执行。 学生给出数字后，问（一次一个问题——不要跳过）：
你说的是每周 [N] 小时。在我构建之前，告诉我你每周还有什么事——工作（时数/周）、家庭（孩子、照顾）、通勤、锻炼、治疗、诊所实践、任何有意义的事情。计划应该适合你的生活，不是反过来。一个你无法遵循的计划比一个更轻但你能做到的计划更糟糕。
等待回答。然后将所述时数与他们的报告负荷进行合理性检查：
那大约是每天约 [X] 小时，在 [工作 + 家庭 + 通勤 + 其他] 之上。以我的经验这是 [现实的 / 紧张的 / 不可持续的]。想在构建前调整每周时数目标，还是保持不变先看看第一周的效果？
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.
- 9d ago First seen · 248 lines · 84 tokens per session scan A c71ef9058ca5
study-plan is a skill published in the GitHub repository zhou210712/claude-for-legal-ZH (212 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 84 tokens to every session and 3,904 once invoked, about $0.0004 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 2026-09-03.
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