predicate-logic

Convert predicate logic formulas to prenex normal form and run Z3 proofs.

3.9k|296|Updated Dec 23, 2025
One-click install
npx skills add https://github.com/parcadei/Continuous-Claude-v3 --skill predicate-logic-parcadei
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: predicate-logic
Source: https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/math/mathematical-logic/predicate-logic
Command: npx skills add https://github.com/parcadei/Continuous-Claude-v3 --skill predicate-logic-parcadei

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires z3_solve.py, sympy_compute.py, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides strategies and tools for solving problems within the domain of predicate logic in mathematical logic, automating complex reasoning tasks.

Core Features & Use Cases

  • Quantifier Analysis: Identifies and analyzes universal (ForAll) and existential (Exists) quantifiers and their scopes.
  • Normal Form Conversion: Assists in converting formulas to Prenex Normal Form and Skolemization.
  • Proof Strategies: Guides through resolution proofs and model theory for refutation.
  • Use Case: When faced with a complex mathematical statement involving quantifiers, use this skill to break it down, convert it to a standard form, and attempt a formal proof or construct a counterexample.

Quick Start

Use the predicate-logic skill to prove the statement 'ForAll([x], P(x)) implies P(a)'.

Frequently Asked Questions about predicate-logic

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

FAQPage Schema
How do I convert predicate logic formulas to prenex normal form and skolemize them?

To convert predicate logic formulas to prenex normal form and skolemize them, use this Skill to systematically identify quantifier scopes and apply normal form conversion strategies for automated theorem proving preparation.

Can I use the Z3 solver to automate resolution proofs and refutation for mathematical logic statements?

Yes, you can use the Z3 solver integration to automate resolution proofs and refutation tasks, enabling systematic validation and counterexample construction for mathematical logic statements involving quantifiers.

What's the best way to analyze universal and existential quantifiers and their scopes in formal proofs?

The best way to analyze universal and existential quantifiers in formal proofs is to apply systematic quantifier analysis techniques that identify variable scopes and support model theory construction for refutation.

Does this approach work for constructing counterexamples in model theory when a formal proof fails?

Yes, this approach supports model theory construction to build counterexamples when automated theorem proving or resolution refutation fails to validate a predicate logic statement.

Do I need to understand formal methods to solve predicate logic problems using automated tools?

You need foundational knowledge of formal methods and mathematical logic to effectively break down complex statements, convert them to standard forms, and interpret automated theorem proving or refutation results.

Why does skolemization fail when processing nested quantifiers in predicate logic expressions?

Skolemization can fail when processing nested quantifiers if quantifier scopes are incorrectly identified, making prenex normal form conversion invalid and preventing proper automated theorem proving with the Z3 solver.