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Math Proof

Community
morankor
math-proof

Write rigorous, gap-free mathematical proofs for academic research. Use when asked to prove, derive, justify analytically, expand a proof sketch, check a theorem statement, or turn economic or game-theoretic reasoning into a complete proof with explicit algebra, signs, edge cases, and no hand-waving.

Overview

Publishermorankor
Repositorytheorist-toolbox
Skill namemath-proof
Stars
92
Forks
23
Bundled files
1
LicenseMIT
Links
  • 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.

  • 1 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 Math Proof AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/morankor/theorist-toolbox/tree/master/codex/.agents/skills/math-proof
  4. 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.
2

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/math-proof .claude/skills/math-proof
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Math Proof 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 Proof 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 Proof 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.

Math Proof

Write proofs suitable for a paper draft. The deliverable is a complete proof, not an outline. Every transition must be checkable by a skeptical reader without filling in missing algebra, sign arguments, or quantifier choices.

This skill adapts Moran Koren's Theorist Toolbox proof discipline for Codex. Preserve the core invariant: if a step is not proved, cited, or explicitly marked as conjectural, do not present it as established.

Workflow

  1. Parse the exact claim, hypotheses, domains, and conclusion.
  2. State the proof plan before proving: direct proof, contradiction, induction, fixed point, comparative statics, counterexample search, or case split.
  3. Define all notation before use. Give object types and parameter domains.
  4. Prove one numbered step at a time. Each step must open with what it will show.
  5. Show intermediate algebra. Do not jump from setup to simplified result.
  6. Sign every derivative, inequality, monotonicity claim, and limit claim at the line where it appears.
  7. Handle edge cases and boundary behavior explicitly.
  8. Separate proved results from conjectures, examples, and numerical evidence.
  9. End with a short intuition paragraph when useful, then close the proof with \square.

Proof Discipline

  • Use \triangleq for definitions and = for equalities.
  • Use display math for multi-term expressions, ratios, derivatives, thresholds, and relation chains.
  • Before algebra, say the goal: "It remains to show that ...".
  • When differentiating a ratio, compute numerator and denominator derivatives before applying the quotient rule.
  • When manipulating inequalities, state why the inequality direction is preserved or reversed.
  • If a threshold is integer-valued but differentiated as continuous, flag the relaxation and explain how discreteness affects the claim.
  • When invoking a theorem, instantiate it in the paper's notation. If the theorem is not standard, cite it precisely or prove the needed lemma.
  • Never prove the general case by checking examples. Examples are evidence, not proof.

Banned Moves

Do not use these phrases or their equivalents unless immediately followed by the missing argument:

  • clearly
  • obviously
  • it is easy to see
  • straightforward
  • by a similar argument
  • omitted for brevity
  • this dominates that
  • the sign is apparent

If the proof relies on a plausible but unproved claim, write it as a conjecture or open obligation. Do not camouflage it as intuition.

Output Format

Use Markdown with LaTeX math.

Recommended structure:

markdown
## Setup

Define primitives, notation, assumptions, and the exact claim.

## Proof

### Step 1: <goal of the step>

...

### Step 2: <goal of the step>

...

The intuition is ...

\(\square\)

If the requested proof cannot be completed, return:

  • the strongest partial result proved,
  • the exact unproved step or obstruction,
  • any counterexample or parameter region found,
  • what would be needed to close the gap.

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 Proof AI skill do?

Write rigorous, gap-free mathematical proofs for academic research. Use when asked to prove, derive, justify analytically, expand a proof sketch, check a theorem statement, or turn economic or game-theoretic reasoning into a complete proof with explicit algebra, signs, edge cases, and no hand-waving.

Why use Math Proof on TypingMind?

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

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

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 Proof?

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

Is the Math Proof 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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