Math Literature

Community

capwitf

math-literature

Use when 高教社杯/CUMCM mathematical modeling papers need lightweight literature search, citation verification, method/background references, standards or policy sources, Chinese-English source routing, DOI/BibTeX checks, or claim-to-citation mapping without fabricated sources.

Overview

Publisher	capwitf
Repository	`My-MathModeling-skills`
Skill name	`math-literature`
Stars	57
Forks	1
Bundled files	5
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
5 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by capwitf on GitHub. Read the source before you install it.

Installation

Install the Math Literature AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/capwitf/My-MathModeling-skills/tree/main/math-literature
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/capwitf/My-MathModeling-skills.git /tmp/My-MathModeling-skills
mkdir -p .claude/skills
cp -r /tmp/My-MathModeling-skills/math-literature .claude/skills/math-literature

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Math Literature in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Math Literature on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Math Literature is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Contest Literature

Purpose

Plan lightweight source work, verify citations, map claims to references, and prevent fabricated or over-broad literature support in contest papers.

This skill is for citation and source verification in 高教社杯/CUMCM work. If the user needs literature to generate solution ideas or compare candidate model routes, return the source gap and route-search need to math-hub; do not reverse-cite a finished model.

国一候选门槛：引用工作应服务题目贴合、建模洞察、证据可信、可复现、边界清楚；这是提交质量门槛，不承诺获奖。

For a citation-backed paper_ready claim, final gate, or cross-module handoff, apply the current math-hub evidence rules. Local source triage can stay lightweight.

Source Routing

Official rules, policies, standards, datasets, and parameters require primary or authoritative sources.
Method background can use credible papers, textbooks, or official documentation.
Ordinary contest background can use compact verified notes when it does not carry a parameter, baseline, policy, or method-validity claim.
If current facts, policies, standards, prices, or public figures may have changed, verify online from primary sources.

Workflow

State the claim needing support.
Decide source tier and search language.
Search or inspect provided sources.
Verify metadata, DOI/BibTeX, publisher, date, and source status when relevant.
Record in literature_search_log.csv and reference_registry.csv when the source supports paper claims.
Create claim_citation_map.csv rows for parameter, standard, policy, baseline, public-data, or method-validity claims.
Return unresolved source gaps to math-hub.

A verified source supports only the point it actually says. Do not widen the paper claim to sound stronger.

Keyword match alone is never bibliography-ready. A reference needs paper location, exact supported point, support boundary, and verified metadata before it can support final prose.

When a request is really "help me find ideas before modeling" rather than "verify this claim/source", return the active subquestion, evidence need, and current source gaps to math-hub for route selection.

Output Contract

Return:

search plan or verified sources;
source tier and support boundary;
literature_search_log.csv, reference_registry.csv, or claim_citation_map.csv rows when needed;
citation wording or BibTeX/DOI fixes;
unresolved gaps and route.

Return to hub: math-hub.

Red Lines

不要编造论文、DOI、作者、期刊、标准或政策原文。
Do not cite search snippets as verified sources.
Do not use an unverified citation for a paper-ready claim.
Do not let a source support broader wording than it justifies.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Math Literature AI skill do?

Why use Math Literature on TypingMind?

Because you install it once and use it with any model. Math Literature is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Math Literature in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/capwitf/My-MathModeling-skills/tree/main/math-literature. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Math Literature?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Math Literature?

As many as you like. As long as a model supports skills, you can use Math Literature with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Math Literature AI skill free?

Yes. It is published on GitHub by capwitf under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Contest Literature

Purpose

Source Routing

Workflow

Output Contract

Red Lines

Bundled files

Frequently asked questions

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