About theory-to-toy-cases
Theory to Toy Cases is a skill for testing an abstract idea through small, concrete examples before applying it to a larger problem. It structures cases to reveal boundaries, failures, and misleading results while distinguishing what they can and cannot establish.
Key features
- 01Restate claims as minimal setups
- 02Create 2–5 contrasting cases
- 03Build small simulations or examples
- 04Compare predictions with outcomes
- 05Identify limits of toy cases
Use cases
- 01Checking assumptions in a research idea
- 02Exploring boundary and failure conditions
- 03Using a small example before scaling analysis
Install
Copy the command and run it in a terminal.
$
npx skills add https:/After installing, type/theory-to-toy-casesin Claude Code to confirm it loaded.
Details
From the project READMETheory to Toy Cases
Make the idea concrete before scaling it up.
Workflow
- Restate the abstract claim in the smallest possible setting.
- 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
- If useful, write a tiny simulation or symbolic example.
- Compare predicted behavior vs actual behavior.
- 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
Comments
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