alethic-solve

Generate, verify, and revise mathematical proofs with independent validation.

2|Updated Feb 12, 2026
One-click install
npx skills add https://github.com/hyperion-git/alethic --skill alethic-solve
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: alethic-solve
Source: https://github.com/hyperion-git/alethic/tree/main/skills/alethic-solve
Command: npx skills add https://github.com/hyperion-git/alethic --skill alethic-solve

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill tackles complex mathematical problems by employing a sophisticated Generate-Verify-Revise loop, ensuring rigorous and verifiable solutions.

Core Features & Use Cases

  • Automated Mathematical Proofs: Generates proofs for mathematical statements.
  • Decoupled Verification: Employs an independent verifier to prevent confidence inflation, ensuring high confidence in results.
  • Use Case: Solve challenging problems like "Prove sqrt(2) is irrational" or "Prove the Cayley-Hamilton theorem" with a high degree of certainty.

Quick Start

Use the alethic-solve skill to prove that the square root of 2 is irrational.

Frequently Asked Questions about alethic-solve

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

FAQPage Schema
How do I generate rigorous mathematical proofs for complex theorems?

To generate rigorous mathematical proofs, this Skill uses a Generate-Verify-Revise loop with decoupled verification. It produces step-by-step logical deductions for complex mathematical statements and independently validates them to ensure high confidence in the derived proof.

Can I customize the iteration count and confidence thresholds for mathematical reasoning?

Yes, you can customize mathematical reasoning parameters. The Skill supports customizable iteration counts, revision limits, and confidence thresholds, allowing you to tailor the step-by-step logical deduction and independent validation process for your specific mathematical problems.

How does decoupled verification prevent confidence inflation in automated theorem proving?

Decoupled verification prevents confidence inflation in automated theorem proving by employing an independent verifier separate from the generation phase. This ensures rigorous validation of mathematical statements and step-by-step logical deductions, maintaining high confidence in the final proofs.

What kind of mathematical problems can be solved with step-by-step logical deduction?

Step-by-step logical deduction can solve challenging mathematical problems requiring rigorous proofs and derivations, such as proving the square root of 2 is irrational or proving the Cayley-Hamilton theorem with a high degree of certainty.

Does this mathematical problem solver require any external dependencies or references?

No external dependencies are required for this mathematical problem solver. It operates independently to execute its Generate-Verify-Revise loop, relying solely on its internal reasoning components and references to validate mathematical statements and ensure rigorous proofs.

Why use a Generate-Verify-Revise loop instead of standard mathematical solvers?

A Generate-Verify-Revise loop ensures rigorous and verifiable solutions for complex mathematical problems. Unlike standard solvers, it decouples verification to prevent confidence inflation, iteratively revising step-by-step logical deductions until mathematical statements are independently validated.