pigeonhole-argument

Generate pigeonhole-based existence proofs for n+1 items in n categories.

3|Updated Feb 9, 2026
One-click install
npx skills add https://github.com/0bserver07/bourbaki --skill pigeonhole-argument
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pigeonhole-argument
Source: https://github.com/0bserver07/bourbaki/tree/main/src/skills/pigeonhole-argument
Command: npx skills add https://github.com/0bserver07/bourbaki --skill pigeonhole-argument

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Prove existence in mathematical problems by applying the pigeonhole principle: if n+1 items are placed into n holes, some hole contains at least two items.

Core Features & Use Cases

  • Formalization: identifies items (pigeons) and categories (holes) and constructs a mapping from items to categories.
  • Use cases: prove duplicates in attribute sets (e.g., hair counts), mutual relationships in groups, or divisibility properties via modular reasoning; adaptable to varying n.
  • Lean-based formalization path: supports machine-checked proofs and verification when needed.

Quick Start

Provide a problem statement with more items than categories and I will generate a pigeonhole-based existence proof.

Frequently Asked Questions about pigeonhole-argument

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prove existence using the pigeonhole principle in combinatorics?

The pigeonhole principle proves existence by placing n+1 items into n categories, which guarantees a collision. This skill identifies your items and categories, then constructs a formal mapping to verify that at least two items must share a category.

Can I generate a Lean formalization for a pigeonhole principle proof?

Yes, this skill provides a Lean-friendly formalization path for pigeonhole arguments. It translates combinatorial counting and mapping strategies into machine-checked proof logic, ensuring your existence proof is verifiable in the Lean prover.

What types of mathematical problems can I solve with pigeonhole arguments?

You can solve problems like finding duplicates in attribute sets, proving mutual relationships in groups, or establishing divisibility properties via modular reasoning. The approach adapts to various n and k settings where items exceed available categories.

What is the best way to structure a pigeonhole proof for varying n and k settings?

The best way is to specify a clear mapping strategy from items to categories and apply combinatorial counting. This skill adapts to varying n and k settings by identifying items as pigeons and categories as holes to guarantee a collision.

Do I need prior formalization experience to use this for mathematical proofs?

No prior formalization experience is strictly required to generate the logical argument, but leveraging the Lean-based formalization path for machine-checked verification works best if you have basic familiarity with the Lean prover and combinatorial counting.