# Theory To Toy Cases

> Turn abstract math or ML ideas into minimal examples, counterexamples, sanity checks, and tiny simulations. Use for theorem intuition, debugging derivations, constructing stress tests, converting a research idea into small checkable cases, or when a concept is too abstract or a claim needs intuition or falsification.

- Skill: `jurgendn/theory-to-toy-cases` (Agent Skill)
- Install (CLI): `npx skillmds@latest add jurgendn/theory-to-toy-cases`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jurgendn/theory-to-toy-cases/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: jurgendn (https://skillmd.com/u/jurgendn)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/jurgendn/theory-to-toy-cases

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# Theory to Toy Cases

Make the idea concrete before scaling it up.

## Workflow

1. Restate the abstract claim in the smallest possible setting.
2. Build 2-5 minimal cases:
   - a friendly case where the idea should work
   - a boundary case
   - a failure case
   - a misleading case that appears to work for the wrong reason
3. If useful, write a tiny simulation or symbolic example.
4. Compare predicted behavior vs actual behavior.
5. Extract what the toy case teaches about the full problem.

## Good toy cases

Prefer cases that are:
- low-dimensional
- analytically tractable
- numerically checkable
- likely to expose hidden assumptions

## Rules

- Do not use toy cases as proof.
- Say what scales and what does not.
- If a toy case fails, treat that as signal, not annoyance.

## Output shape

Return:
- Abstract idea
- Minimal setup
- Cases
- What each case shows
- Implication for the full research question
- What the toy cases cannot establish