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lean-math-optimization

Route Lean 4 optimization and game theory proofs via centralized handoffs.

2|Updated May 26, 2026
Search Tags:#optimization#handoffs#lean4#reinforcement-learning#game-theory#proof-workflow
One-click install
npx skills add https://github.com/r-irbe/proof-skills --skill lean-math-optimization
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lean-math-optimization
Source: https://github.com/r-irbe/proof-skills/tree/main/skills/lean-math-optimization
Command: npx skills add https://github.com/r-irbe/proof-skills --skill lean-math-optimization

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Lean-proof and Mathlib4 workflows often suffer from fragmented guidance across optimization, game theory, RL, and decision theory proofs. This Skill provides a centralized routing and handoff model that structures these proofs and aligns them with repository references and template workflows.

Core Features & Use Cases

  • Centralized routing for Lean 4 optimization, game theory, RL theory, and decision-making proofs with clear handoffs to specialized helpers.
  • Access to a canonical encyclopaedia of concepts and patterns stored in references (e.g., lean4-math-optimization.md) to accelerate proof authoring and consistency.
  • On-demand templates and templates references for bootstrapping proofs, regressions, and audit-ready documentation.
  • Use Case: when formalizing a Bellman backup or a Nash-equilibrium argument, route through the appropriate handoffs and reference materials to ensure correctness and consistency.

Quick Start

Install this skill into your Lean-proof harness to begin routing optimization proofs to the appropriate handoffs.

Frequently Asked Questions about lean-math-optimization

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

FAQPage Schema
How do I structure Lean 4 optimization proofs with centralized routing?▼

You can formalize game theory and Nash-equilibrium arguments in Lean 4 by applying this Skill's centralized routing model, which routes proof logic through appropriate handoffs and reference materials to ensure correctness and consistency.

What is the best way to formalize Bellman backups in Lean 4 and Mathlib4?▼

The best way to formalize Bellman backups in Lean 4 and Mathlib4 is using this Skill's routing and handoff model, which structures reinforcement-learning theory proofs and dispatches them to specialized helpers for consistent authoring.

Can I use this routing model for decision theory and dynamic programming proofs in Mathlib4?▼

Yes, you can use this routing model for decision theory and dynamic programming proofs in Mathlib4, as it provides centralized dispatch contracts and an encyclopedia of references to accelerate proof authoring across these domains.

How do I bootstrap a proof workflow and ensure audit-ready documentation in Lean 4?▼

You bootstrap a proof workflow and ensure audit-ready documentation in Lean 4 by accessing this Skill's on-demand templates and references, which provide deterministic task components and contextual information for consistent formalization.

Does this Skill require specific dependencies to formalize optimization proofs in Lean 4?▼

This Skill requires no external dependencies to formalize optimization proofs in Lean 4, operating entirely through frontmatter-defined dispatch contracts, scripts, and an internal encyclopedia of references.

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