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 study-plan-buildergit 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-/study-plan-builder)<a href="https://agentmods.dev/skills/hwl668/scientific-learning-skills-/study-plan-builder"><img src="https://agentmods.dev/badge/skills/hwl668/scientific-learning-skills-/study-plan-builder.svg" alt="Measured on agentmods" 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 | $0.00072 | $0.01368 |
| Opus 5 | $0.00036 | $0.00684 |
| Sonnet 5 | $0.00014 | $0.00274 |
| Haiku 4.5 | $0.00007 | $0.00137 |
Grade A, and why
study-plan-builder 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 8d 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.
What it actually says
目标
根据学习者的具体约束（目标、时间、基础），生成一个现实、具体、可执行的学习计划。
适用场景
- 准备某门课的期末考试
- 自学一门新的编程语言/数学分支
- 考研/高考复习规划
- 短期内需要补齐某个知识短板
Memory 系统
类型：分析记忆（不参与间隔复习）。
存储位置：memory/study-plan-builder/
存储内容：
- 有效的计划模板：哪些阶段划分/时间分配方案在哪些场景下效果好
- 常见过载陷阱：哪类计划经常被用户反馈"排太满"（用于后续自动修正）
读/写规则：
- 写入：每次计划生成后，如果用户在复盘反馈中表示"计划合理/完成了"，记录模板。
- 读取：下次遇到相似目标/时间约束时，参考已记录的有效模板。
- 管理：说"清除 study-plan-builder 记忆"删除。
输入判断
需要收集以下信息：
- 目标：学到什么程度？通过考试 / 能做项目 / 深刻理解？
- 当前基础：相关的前置知识掌握程度。
- 可用时间：每天/每周多少小时？持续多久？
- 资源：已有教材、网课、习题集？
- 约束：有没有硬性截止日期？
执行流程
信息收集 → 目标拆解 → 阶段划分 → 每日任务 → 资源匹配 → 检测标准 → 复盘机制
1. 目标拆解
把大目标拆成可检测的阶段性小目标。
例如："学完微积分" → 拆成 6 个小阶段：极限 → 导数 → 积分 → 微分方程 → 多变量 → 应用
2. 阶段划分
每个阶段分配时间。原则：
- 新学阶段预留 20% 缓冲时间
- 每个阶段之间有复习/检测点
- 不要排满——留白比填满好
3. 每日任务
每个任务包含：
- 学什么（具体知识点）
- 怎么学（看视频/读教材/做笔记）
- 练什么（具体习题）
- 检测方式（自测题/默写/做真题）
4. 资源匹配
推荐最适合的教材、网课、习题集。优先推荐免费资源。
5. 检测标准
每个阶段结束时的检测方式：
- 做一套真题
- 给别人讲一遍
- 默写关键公式和推导
- 做综合题
6. 复盘机制
每周复盘：
- 本周完成了什么？
- 哪部分比预期难？
- 下周计划需要调整吗？
输出格式
## 总览
- 目标：[具体目标]
- 时间：[总时长]
- 当前基础：[简述]
## 阶段划分
### 阶段 1：[名称]（[时间]）
- 目标：[可检测的目标]
- 每日任务：[具体任务列表]
- 核心资料：[教材/视频/习题]
- 检测方式：[怎么判断学成了]
### 阶段 2：...
## 每周复盘问题
1. 本周完成了计划的百分之多少？
2. 哪个知识点花的时间远超预期？
3. 下周需要调整什么？
常见误区
| 常见错误 | 为什么错 | 正确理解 |
|---|---|---|
| "计划排满 = 效率高" | 没有缓冲的计划遇到一次中断就全崩 | 每天留 20% 缓冲时间，每 3-4 天留半天弹性 |
| "学完=学会" | 把"看完了"当"掌握了"，没有检测标准 | 每个阶段设检测点：能做哪类题、能解释哪个概念 |
| "别人的计划直接套用" | 基础、时间、目标不同，计划不能照搬 | 计划模板可以借鉴，但需根据自诊断调整起点和节奏 |
反例：什么时候不要这样做
- 不要制定不可能完成的计划（如每天 8 小时持续一个月）
- 不要只列知识点不列练习
- 不要没有检测标准——"学完"不是目标,"能做什么"才是
- 不要忽略学习者的实际约束
- 不要一个模板套所有人
测试样例
输入：我想在两个月内自学完线性代数，目标是通过学校期末考。我现在只会矩阵乘法和行列式计算，每天大约能学 1.5 小时。教材是 Gilbert Strang 的 Introduction to Linear Algebra。
期望输出方向：
- 目标拆解：6-8 个阶段，对应教材章节
- 每周约 10 小时，8 周共 80 小时
- 阶段 1：向量空间与线性方程组（第 1 周）——具体到每天看哪几页、做哪几道习题
- 核心检测：每阶段结束做教材章末 3 道代表性题目
- 缓冲：第 7 周留白做综合复习
- 第 8 周做往年期末卷
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.
- 8d ago First seen · 138 lines · 72 tokens per session scan A 5fa0d888c335
study-plan-builder is a skill published in the GitHub repository hwl668/Scientific-learning-skills- (13 stars, last pushed 1mo ago), licensed MIT. It adds 72 tokens to every session and 1,368 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 2026-08-30.
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