alethic-solve

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

2|Updated Feb 12, 2026

Search Tags:#verification #ai agent #mathematics #reasoning #proof #theorem

Ready to run

npx skills add https://github.com/hyperion-git/alethic --skill alethic-solve

💬 Prompt for ChatGPT / Claude Chat▼

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.