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math-paper

math-paper is a skill for Claude Code, Codex from OrinVoss/dsh-math-team. It costs 95 tokens per session (5,756 once invoked), scanned A, original, MIT.

A role guide for writing and checking mathematical modelling papers, including evidence gathering, source verification, and final review. It is designed for teams that coordinate work through separate repository folders.

In plain words
What is it for?
Use it to collect results from collaborating team members, build an evidence outline, verify references, write a Word or LaTeX paper, and perform a final quality review.
Why use it?
It helps turn modelling results into a paper without inventing evidence, while checking that claims, figures, results, and citations can be traced to real sources or team deliverables.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

not rated 7repo changed 1mo ago A scan 95 tokens original MIT

Good fit Use it to collect results from collaborating team members, build an evidence outline, verify references, write a Word or LaTeX paper, and perform a final quality review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/orinvoss/dsh-math-team/math-paper
View source ↗ OrinVoss/dsh-math-team
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 OrinVoss/dsh-math-team --skill math-paper
Clone the repo
git clone --depth 1 https://github.com/OrinVoss/dsh-math-team

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.

agentmods badge for math-paper

README.md
[![agentmods](https://agentmods.dev/badge/skills/orinvoss/dsh-math-team/math-paper/github.svg)](https://agentmods.dev/skills/orinvoss/dsh-math-team/math-paper)
Your own site
<a href="https://agentmods.dev/skills/orinvoss/dsh-math-team/math-paper"><img src="https://agentmods.dev/badge/skills/orinvoss/dsh-math-team/math-paper/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.

agentmods 80×15 button for math-paper

Your own site · 80×15
<a href="https://agentmods.dev/skills/orinvoss/dsh-math-team/math-paper"><img src="https://agentmods.dev/badge/skills/orinvoss/dsh-math-team/math-paper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,756 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 $0.00095 $0.05756
Opus 5.5 $0.00038 $0.02302
Sonnet 5.5 $0.00019 $0.01151
Haiku 4.5 $0.00010 $0.00576

Measured 1mo ago against content hash 5a4d7759f399, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

math-paper 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 1mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/read_pdf.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

presets/paper/skills/math-paper/SKILL.md · 197 lines

How it starts

The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.

论文岗（团队数学建模）

你是团队中负责「论文」的 agent。团队通过同一个 Gitee 仓库的三个独立子文件夹协同：member-a/、member-b/（两名建模+编程成员交付物）、member-c/（你的工作区）。本 skill 约定你的职责、流程与门禁。

团队协同模型（强制）

  • 你的工作区 = Gitee 仓库根下的 member-c/ 文件夹。
  • git pull 拉取建模+编程成员的交付物（member-a/、member-b/ 下的题目分析报告、术语表格、results/、figures/）。
  • 只读写 member-c/；git add 限定在自身文件夹内；绝不改写他人文件夹。
  • 成稿后 git add member-c && git commit && git push。

拉取他人交付物

# 若 Gitee 走代理/报 schannel 错，先执行：
git config http.sslBackend openssl
git config http.proxy http://127.0.0.1:10808    # 仅当需要代理

git clone <gitee-repo-url>   # 首次
git pull                     # 之后每次开始工作前拉取最新

模型分工方案（按能力选型，不绑定具体型号）

按能力互补分工，不指定具体模型——按你环境中实际可用的模型，依据下表配置（模型名不要硬编码，换部署后重新探测）：

角色 能力要求 怎么选
主模型 世界知识广、判断敏锐、语言/写作强 选你环境里知识面/推理最强的模型，负责论文写作、证据检索与核验、知识判断、口径把握（本岗位的主要工作）
编程/脚本 代码能力强 选编程能力最强的模型（可与主模型不同）；写脚本、编译/转换（LaTeX→PDF、DOCX 校验等）时用 workflow 派它做子代理执行
审查（≥2 个不同模型各审一遍） 与产出方不同厂商 / 不同能力侧重 至少挑两个不同模型各独立审一遍：一个偏知识/逻辑/引用/口径，一个偏代码/复现/格式实现；两份结论都要记录
识图 支持图像输入、成本可控 优先经济型视觉模型（见「识图子代理」小节）

怎么探测：用 llm 服务的 listProviders() / resolveModelInfo() 列出本环境可用模型及能力，再按上表挑选。某角色找不到合适模型时如实标注受限。

本环境已验证示例（仅供参考，非强制）：主模型 Kimi K3 · 编程 DeepSeek V4.1 Flash · 审查 Kimi K3-256K + DeepSeek V4.1 Flash 双模型各审一遍 · 识图 Kimi K2.7 Code（kimi-coding/kimi-for-coding）。可用任何满足上表能力的模型替代。

  • ⚠️ 子代理模型白名单：本环境的子代理只能用 subagent-model-selection.allowedModels 中列出的模型（当前为 deepseek-official/deepseek-flash、kimi-coding/k3-256k、kimi-coding/kimi-for-coding）。派发子代理时若指定白名单外的模型会失败；请从白名单中按能力挑选，或让使用者把目标模型加入白名单。

我的职责

第零步：读题目与官方模板（PDF 用双通道）

论文岗也要读 PDF：题目文件、官方论文模板/格式规范、建模岗交付的 PDF 等。PDF 一律用「双通道读取 + 对齐」（与建模岗同一方法、同一脚本）：

uv run --with pypdf --with pymupdf python <SKILL_ROOT>/scripts/read_pdf.py <文件.pdf> <PROJECT_ROOT>/pdf提取 150
  • 文本通道：read 读生成的 .txt——检索、复制、逐字核对官方格式条款；
  • 图像通道：read_image 逐页看 page_NN.png——模板的版式、页眉页脚、摘要页样式、参考文献格式等，图像最接近原貌；
  • 对齐核对（强制）：两通道交叉核对；不一致或明显缺漏时以图像通道为准，并把差异记入 评审记录.md（例如"官方模板要求 X 在文本提取中缺失，已按第 N 页图像确认"）。

Read the full file on GitHub · 197 lines

Files

What ships with it

13 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.

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. 1mo ago Changed · +45 lines 5a4d7759f399
  2. 2mo ago First seen · 152 lines · 95 tokens per session scan A 07bd24096dd7

Subscribe to this mod's changes

math-paper is a skill published in the GitHub repository OrinVoss/dsh-math-team (7 stars, last pushed 1mo ago), licensed MIT. It adds 95 tokens to every session and 5,756 once invoked, about $0.0004 per session on Opus 5.5. 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.

Claude CodeScientificWriting and docsagent-presetsagent-skillsai-codingcodexdsh-plugin
Related

math-paper compared with skills from other repositories

math-paper next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
math-paperOrinVoss/dsh-math-teamSkill71mo agoMITA95Claude Code, Codex
mathodology-evidence-searchsweetcornna/mathodologySkill320yesterdayMITA24Claude Code, Codex
mathodology-workbenchsweetcornna/mathodologySkill320yesterdayMITA42Claude Code, Codex
semantic-scholar-deepCodeAlive-AI/ai-driven-developmentSkill167yesterdayMITA163Claude Code
fortranMindrally/skillsSkill29729d agoApache-2.0A95Claude Code
mathodology-agent-pipelinesweetcornna/mathodologySkill320yesterdayMITA24Claude Code, Codex
juliaMindrally/skillsSkill29729d agoApache-2.0A22Claude Code