Co Math Init

Community

morankor

co-math-init

Initialize a disciplined AI co-mathematician research project for Codex. Use when starting a math or economic theory investigation that needs goals.md, paper.tex, workstreams, decisions, reviewer approvals, strict no-hand-waving proof tracking, Lean/code workstreams, or a durable co-math project scaffold.

Overview

Publisher	morankor
Repository	`theorist-toolbox`
Skill name	`co-math-init`
Stars	92
Forks	23
Bundled files	2
License	MIT
Links	Skill source Repository

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.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by morankor on GitHub. Read the source before you install it.

Installation

Install the Co Math Init 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/morankor/theorist-toolbox/tree/master/codex/.agents/skills/co-math-init
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/morankor/theorist-toolbox/tree/master/codex/.agents/skills/co-math-init

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

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/morankor/theorist-toolbox.git /tmp/theorist-toolbox
mkdir -p .claude/skills
cp -r /tmp/theorist-toolbox/codex/.agents/skills/co-math-init .claude/skills/co-math-init

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

Use it in TypingMind

Enable Co Math Init 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 Co Math Init 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 Co Math Init 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.

Co-Math Init

Create a local research project modeled on the Theorist Toolbox co-math workflow. The project keeps a living paper.tex, explicit goals, append-only decisions, workstream reports, reviewer approvals, failed explorations, and open proof obligations.

Strict mode is the default. In strict mode, every proof gap must be marked with \unproven{...} until reviewed or machine-checked.

Inputs

Gather or infer:

project name: lowercase kebab-case,
research question: one or two sentences,
parent directory: default to the current working directory,
strict mode: default true; only set false if the user explicitly asks for pragmatic mode.

If the project name is missing, derive a short kebab-case name from the research question. If the research question is missing, ask for it.

Create The Project

Run the bundled script from the skill directory:

bash
python3 scripts/init_co_math_project.py \
  --name <project-name> \
  --question "<research question>" \
  --parent <parent-directory>

For pragmatic mode:

bash
python3 scripts/init_co_math_project.py \
  --name <project-name> \
  --question "<research question>" \
  --parent <parent-directory> \
  --pragmatic

The script creates:

text
paper.tex
goals.md
decisions.md
README.md
AGENTS.md
co-math-config.json
workstreams/.gitkeep
references/.gitkeep
failed-explorations/.gitkeep
.co-math/approvals/.gitkeep
.co-math/workstream-registry.json

After Initialization

Tell the user:

the absolute path of the created project,
goals.md is where the research question and sub-goals are refined,
no workstream should start until goals are approved,
paper.tex is the living paper,
workstreams/ will hold one directory per proof, literature, code, Lean, or readability task,
.co-math/approvals/ is the reviewer gate,
failed-explorations/ is intentionally durable and should not be cleaned away.

If the package's Codex custom agents are installed, suggest starting with the co-math-project-coordinator agent. If not, Codex can still run the workflow manually using the project files and the role profiles in this package.

What Not To Do

Do not start proving immediately during initialization.
Do not mark goals approved on behalf of the user.
Do not disable strict mode unless the user explicitly asks.
Do not remove \unproven{} obligations to make the paper look cleaner.

Bundled files

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

agents/openai.yaml1 KB
scripts/init_co_math_project.py10 KB

Frequently asked questions

What does the Co Math Init AI skill do?

Why use Co Math Init on TypingMind?

Because you install it once and use it with any model. Co Math Init 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 Co Math Init in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/morankor/theorist-toolbox/tree/master/codex/.agents/skills/co-math-init. 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 Co Math Init?

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 Co Math Init?

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

Is the Co Math Init AI skill free?

Yes. It is published on GitHub by morankor 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

Co-Math Init

Inputs

Create The Project

After Initialization

What Not To Do

Bundled files

Frequently asked questions

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