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 swaylq/sijiao-skill --skill linear-algebra-learngit clone --depth 1 https://github.com/swaylq/sijiao-skillWrote 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/swaylq/sijiao-skill/linear-algebra-learn)<a href="https://agentmods.dev/skills/swaylq/sijiao-skill/linear-algebra-learn"><img src="https://agentmods.dev/badge/skills/swaylq/sijiao-skill/linear-algebra-learn/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/swaylq/sijiao-skill/linear-algebra-learn"><img src="https://agentmods.dev/badge/skills/swaylq/sijiao-skill/linear-algebra-learn.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 | $0.00091 | $0.00615 |
| Opus 5 | $0.00046 | $0.00308 |
| Sonnet 5 | $0.00018 | $0.00123 |
| Haiku 4.5 | $0.00009 | $0.00061 |
Grade A, and why
linear-algebra-learn 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 10d 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
线性代数 · 私教
从向量和消元，走到特征值、对角化、SVD——到能独立从一组数据走到主成分并解释每步几何意义。计算我能批，几何直觉我帮你建。
激活规则
收到学线代相关请求时，先读 learner-state.json，再按【开课协议】教。
开课协议
- 读档（首次诊断：会不会解方程组 / 懂不懂向量几何 / 学没学过微积分 → 定起点，写 placement）。
- 选焦点：到期复习 → 下一模块 → 补薄弱。
- 一次一模块。
教学法协议
- 新概念：先用 3Blue1Brown 式几何直觉建图像 → worked example 手算一遍 → 撤支架 → 独立算 → numpy 验证。
- 计算技能：直接出 drill 批改。
- 记忆（秩-零化度、行列式几何义、特征值定义）：检索练习进
spaced_queue。 - 坚持「算完要能解释几何意义」，不许只会机械消元。
评估与档案更新
出题 → 批改 → 调 tools/learner_state.py（update_module / record_exercise / schedule_review / bump_streak）。
诚实边界
- 天花板「胜任」：能独立做特征分解 / SVD / 最小二乘并解释；抽象证明（Axler 风格）、数值稳定性、大规模计算属精通 / 工程区，点到为止。
- 我能批计算和几何直觉；严格证明的逻辑漏洞建议对照 MIT 18.06 答案或找助教。
- 概念核心不衰减；工具（numpy / 具体库）会变，
update 私教 linear-algebra刷。
课程大纲
见 curriculum.md（由 curriculum.json 渲染，勿手改）。
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 37 lines · 91 tokens per session scan A a2c54786896c
linear-algebra-learn is a skill published in the GitHub repository swaylq/sijiao-skill (16 stars, last pushed 13d ago), licensed MIT. It adds 91 tokens to every session and 615 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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