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 agentmods add skills/mrsgsa/math-modeling-skill-dify/model-designernpx skills add MrSGSA/math-modeling-skill-dify --skill model-designergit clone --depth 1 https://github.com/MrSGSA/math-modeling-skill-difyWrote 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/mrsgsa/math-modeling-skill-dify/model-designer)<a href="https://agentmods.dev/skills/mrsgsa/math-modeling-skill-dify/model-designer"><img src="https://agentmods.dev/badge/skills/mrsgsa/math-modeling-skill-dify/model-designer.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 | $0.00030 | $0.00856 |
| Opus 5 | $0.00015 | $0.00428 |
| Sonnet 5 | $0.00006 | $0.00171 |
| Haiku 4.5 | $0.00003 | $0.00086 |
Grade A, and why
model-designer 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 6d 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
建模手
路径
ROLE_ROOT：本文件所在目录。SKILL_ROOT：ROLE_ROOT/../../..，只读。PROJECT_ROOT：用户项目目录，所有产物只写这里。
固定产物
PROJECT_ROOT/题目分析报告.mdPROJECT_ROOT/术语表格.md
只使用上述两个文件；合同内容作为分析报告的一部分。
执行顺序
- 读取题目与全部附件，建立问题、目标、约束、数据字段和输出要求清单。
- 数据驱动地检查来源与版本、行列完整性、缺失、重复、异常、量纲、时间与空间范围，并预先规划训练、调参、验证及组别/时间隔离，防止数据泄漏。
- 在理解题目后写出每个子问题应回答的结论类型，再按任务需要从可用的领域知识库、建模算法库、可追溯文献和相关案例评估候选模型；某类来源不可用时透明降级，不伪造检索结果，也不为凑数量强求案例。比赛启发模式允许从相似或可迁移案例提炼模型族、变量、约束、算法组合和验证方法，但须针对当前题目重新推导和验证；独立练习模式下，同题案例在主方案锁定前不得作为模型、参数、代码或答案来源。
- 为每个子问题选择最少且足以回答问题的模型体系，说明模型、算法、公式、参数、输入输出、验证方式和风险。只有新增模型在机制、假设、任务阶段或独立验证上提供不可替代的价值且能够真实实现时才保留；同一物理机制的不同近似或精度展开通常按一个模型族组织。
- 在查看拟合结果前，为所有影响核心结论的参数、决策变量、阈值和松弛量建立语义合同：定义、单位、允许域、依据、预期单调性/极限、可辨识来源及输出影响。无法给出领域依据时明确标为待验证，不得事后迎合最优值补写范围。读取
../../参数语义与约束审计.md。 - 使用
../../../tools/paper-search/SKILL.md搜索理论依据；引用必须可追溯。 - 写入两个固定产物并按
references/质检清单.md检查。
何时加载
| 情形 | 读取 |
|---|---|
| 开始分析 | references/工作流程.md |
| 设计模型组合 | references/建模设计理论.md |
| 需要常见问题模式 | references/常见模式.md |
| 需要具体算法 | ../../../references/算法索引.md，再按索引分段读取匹配的 ../../../references/algorithms/*.md |
| 交付前 | references/质检清单.md |
选择原则
- 模型必须覆盖题目约束、数据特征和评价目标。
- 避免直接套用常见简单模型；优先寻找与题目结构紧密相关、可验证且可实现的改进。
- 复杂度由问题需要决定，不把复杂度本身当作独立优点。
- 不因模型结论相似而机械删除，也不为展示数量堆叠同质模型；以独立证据价值决定去留。
若编程手反馈模型不可实现，基于具体报错和数据证据修订两个既有产物，不另建文件。
What ships with it
6 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.
- 6d ago First seen · 49 lines · 30 tokens per session scan A 8bfb29aeacef
model-designer is a skill published in the GitHub repository MrSGSA/math-modeling-skill-dify (4 stars, last pushed 1mo ago), licensed MIT. It adds 30 tokens to every session and 856 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
math-modeling-solver
数学建模竞赛解题全流程指导。覆盖国赛(CUMCM)和美赛(MCM/ICM)全部题型(A-F)，提供12种问题本质分析、95+场景模型决策矩阵、5本算法Cookbook、11本完整例题Playbook、22个Python+7个MATLAB可运行代码模板。与math-modeling-paper形成"解题→写作"配对。当用户提及建模思路、选什么模型、怎么建模、赛题求解、粘贴赛题文本、美赛/国赛题目分析、CVaR/NSGA-II/Monte Carlo/时间序列/ANOVA/灰色关联、网络流/图论/生态建模、模型命名/Memo/Letter/Our Work流程图时，使用此skill。.
math-modeling-paper
数学建模竞赛论文写作全流程指导。覆盖国赛(CUMCM)和美赛(MCM/ICM)，从论文结构规划、各章节撰写、模型检验、参考文献规范到最终格式检查。与math-modeling-solver形成"解题→写作"配对——可接收solver输出的论文草稿片段直接展开写作。当用户提及数学建模论文写作、建模比赛、国赛/美赛/电工杯/亚太杯/深圳杯/华为杯论文、CUMCM、MCM/ICM、数模论文结构、摘要写作、模型检验、灵敏度分析、latex建模模板、word建模排版、Memo/Letter写作、模型命名、Our Work流程图，或需要写/修改/优化/检查建模论文的任何部分时，都必须使用此 skill。.
ez-math-model
Use when solving CUMCM, MCM, ICM, or other mathematical modeling tasks that need contest problem intake, model selection, Python solving, figures, paper writing, quality audit, and packaged deliverables.
brainstorming
Use when EZmathmodel model selection is unclear after the modeling decision tree, the problem spans multiple domains, or modeler needs several candidate approaches before writing modelingplan.md.
scientific-slides
Use when the user explicitly asks EZmathmodel to create defense slides, academic presentation slides, Beamer slides, or PPT after the modeling paper has been packaged.
interpret-modeling-problems
根据原始赛题和附件，生成可回查证据的国赛及类似数学建模赛题解读，建立小问输入输出、约束与歧义、附件审计、模型蓝图、验证方案和论文交付接口。适用于选题比较、正式建模前的完整解读和已有解读复核；不用于在缺少原题时臆测题意，也不把候选模型伪装成已经验证的数值求解。.