mcm-model-typeset

mcm-model-typeset is a skill for Claude Code, Codex from LiXiang106991/MathModelAgent. It costs 65 tokens per session (1,479 once invoked), scanned A, original, MIT.

A set of writing and formatting rules for the model-building and solution section of a Chinese mathematical modelling paper. It defines section structure, equation explanations, constraints, and model summaries without changing the supplied numbers or formulas.

In plain words
What is it for?
Use it when writing, rewriting, or formatting the model establishment and solution section of a modelling paper.
Why use it?
It keeps similar modelling sections consistent and avoids inventing symbols, values, or assumptions while formatting the paper.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when writing, rewriting, or formatting the model establishment and solution section of a modelling paper.

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Install with agentmods
npx agentmods add skills/lixiang106991/mathmodelagent/mcm-model-typeset
Install

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.

Any agent
npx skills add LiXiang106991/MathModelAgent --skill mcm-model-typeset
Clone the repo
git clone --depth 1 https://github.com/LiXiang106991/MathModelAgent

Made for: Claude Code, Codex.

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.

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README.md
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Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,479 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00065 $0.01479
Opus 5 $0.00032 $0.00740
Sonnet 5 $0.00013 $0.00296
Haiku 4.5 $0.00006 $0.00148

Measured today against content hash 7d31a0438842, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-20, from the pricing page.

Security

Grade A, and why

mcm-model-typeset 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 today.

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.

mcm-model-typeset-SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

优化类建模章节排版规范

本 skill 只规定章节结构与句式。全部公式内容、符号含义、数值一律 来自用户提供的材料;禁止自行发明符号、口径或修改任何数字。

M1 五段式章节骨架

每个问题固定为:

\subsection{问题X模型的建立与求解}
\subsubsection{决策变量的确定}
\subsubsection{目标函数}        % 标题措辞可随材料调整
\subsubsection{约束条件}
\subsubsection{模型汇总}
\subsubsection{求解}            % 可选
  • 标题为 4–10 字名词短语,不带句号;
  • 多问题时其余问题沿用同构骨架,编号递增。

M2 符号定义三段式

每个新公式按「引入句 → 公式 → 符号说明」三段式:

  1. 引入句:一句话交代本段定义什么,以",设:"或冒号收尾;
  2. 公式:equation 环境,右侧编号;
  3. 符号说明段:以"其中,"开头,各符号解释用分号连排, 末项以句号收尾;每项格式:符号 表示 含义(单位);
    • 指标取值范围(年、编号等)写在符号说明段内,不独立成段;
    • 禁止改用表格或 bullet 列表;
    • 符号在首次出现处解释,后文直接使用不再解释。 若一个公式说明完后需要引出下一个公式,用过渡句 ("再考虑…,有:"),不打断三段式节奏。

M3 约束块固定句式

约束条件小节内,每条约束一个段落块:

\textbf{约束n:名称}
一句引入(交代业务/物理动机)。
\[ 公式 \]
其中,…(符号解释;若有近似或线性化,在此追加一句理由)。
  • 约束编号 n 全章连续(约束1、约束2…),与公式编号独立计数;
  • 名称 4–8 字名词短语,不加句号;
  • 使用了 sgn、取整等非光滑近似的约束,理由必须写在"其中"段, 禁止只放脚注。

M4 集合划分列表

凡"将某集合划分",固定两步:

  1. 总起句:"为了更好地描述约束条件,本文对××集合进行了更细致的 划分。将××集合划分为 n 类如下:"
  2. 编号列表,每行:1. D = {i|i = 1, 2, …, m} 表示××的××;
    • 花括号+竖线条件式枚举;
    • 行末分号,末行句号;
    • 划分须完备且互斥;材料未说明完备性时停下来向用户确认, 禁止自行补齐。

M5 模型汇总大括号

"模型汇总"小节固定结构:

  1. 引导句:"本文建立了以××为目标的××优化模型如下:"
  2. 单个公式环境内用 \left\{\begin{array}{l} … \end{array}\right. 实现巨型左大括号(禁止用 cases,其强制 text style); 多行等式对齐用嵌套 aligned
  3. 括号内部自上而下:
    • 首行:目标函数(max/min W = …);
    • 之后:s.t. 对齐后逐行列全部约束(引用前文公式,不重新 推导),每行一个约束,并列条件用 \quad 分隔;
    • 末尾若干行:集中列出本问题全部集合定义(与 M4 内容一致, 逐行排版);
  4. 整个大括号块只占一个公式编号,内部各行禁止单独编号;
  5. 约束过多超页宽时允许拆成上下两个大括号块,两块合计仍只占 一个编号;禁止缩小字号硬塞。

M6 公式编号与交叉引用

  • 编号全文连续,不按节重置;
  • 正文引用一律 \eqref{eq:xxx},禁止手写编号数字;
  • 汇总大括号的编号即该问题模型的总编号,摘要与结果分析引用 模型时统一引用该编号。

硬性禁令

  1. 禁止修改任何数值、参数、口径——发现疑似问题停下报告,不许"顺手修正";
  2. 禁止把"其中"符号说明改成三线表或列表;
  3. 禁止约束编号与公式编号混用同一计数器;
  4. 禁止在大括号内重新解释符号(解释只出现在前文对应公式处);
  5. 每写完一节自检:M2 三段式是否完整、M6 编号是否连续,不合格不进入下一节。

三个使用提醒

与数字校验流程解耦:这个 skill 只管“装订”。加载它之后不要再让同一个会话改数字、核口径——一次一个 skill、一个任务,否则它会分心,你之前的权威数字表也多一分被误动的风险。

M5 是技术难点:skill 里已强制 \left{\begin{array}{l} 写法并禁用 cases;若实测某行约束太长溢出页宽,让它改用 optidef 宏包,而不是缩字号。

M4 的完备性检查是它唯一被允许“停下来问你”的地方——如果它没问就默认集合划分没问题,值得在收到交付时反问一句“四个子集的并集是否覆盖全部 54 块地”,防它沉默跳过。

Read the full file on GitHub · 86 lines

Changes

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.

  1. today First seen · 86 lines · 65 tokens per session scan A 7d31a0438842

Subscribe to this mod's changes

mcm-model-typeset is a skill published in the GitHub repository LiXiang106991/MathModelAgent (23 stars, last pushed yesterday), licensed MIT. It adds 65 tokens to every session and 1,479 once invoked, about $0.0003 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 2026-09-20.

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