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predicate-logic

This skill performs logic tasks including quantifier analysis and resolution proofs using Z3.

Install

mkdir -p .claude/skills/predicate-logic && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/2325" && unzip -o skill.zip -d .claude/skills/predicate-logic && rm skill.zip

Installs to .claude/skills/predicate-logic

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Problem-solving strategies for predicate logic in mathematical logic
68 charsno explicit “when” trigger
Advanced

Key capabilities

  • Perform quantifier analysis for universal and existential logic
  • Convert formulas to prenex normal form
  • Execute Skolemization for resolution proofs
  • Construct countermodels for invalid arguments

How it works

It uses Z3 and SymPy scripts to automate logical operations, including quantifier manipulation and resolution-based proof generation.

Inputs & outputs

You give it
z3_solve.py prove 'formula'
You get back
Proof verification or countermodel construction

When to use predicate-logic

  • Prove a logical implication using Z3
  • Convert a formula to prenex normal form
  • Find a countermodel for a formula

About this skill

Predicate Logic

When to Use

Use this skill when working on predicate-logic problems in mathematical logic.

Decision Tree

  1. Quantifier Analysis

    • Identify: ForAll (universal), Exists (existential)
    • Scope of quantifiers and free/bound variables
    • z3_solve.py prove "ForAll([x], P(x)) implies P(a)"
  2. Prenex Normal Form

    • Move all quantifiers to front
    • Standardize variables to avoid capture
    • sympy_compute.py simplify "prenex(formula)"
  3. Skolemization (for Exists)

    • Replace existential quantifiers with Skolem functions
    • Exists x. P(x) -> P(c) or P(f(y)) depending on scope
    • Needed for resolution-based proofs
  4. Resolution Proof

    • Convert to CNF, negate conclusion
    • Apply resolution rule until empty clause or saturation
    • z3_solve.py prove "resolution_valid"
  5. Model Theory

    • Construct countermodel to refute invalid argument
    • Finite model for finite domain
    • z3_solve.py model "Exists([x], P(x) & Not(Q(x)))"

Tool Commands

Z3_Forall

uv run python -m runtime.harness scripts/z3_solve.py prove "ForAll([x], Implies(P(x), Q(x)))"

Z3_Exists

uv run python -m runtime.harness scripts/z3_solve.py sat "Exists([x], And(P(x), Not(Q(x))))"

Z3_Universal_Instantiation

uv run python -m runtime.harness scripts/z3_solve.py prove "Implies(ForAll([x], P(x)), P(a))"

Z3_Model

uv run python -m runtime.harness scripts/z3_solve.py model "Exists([x], P(x))"

Cognitive Tools Reference

See .claude/skills/math-mode/SKILL.md for full tool documentation.

When not to use it

  • For non-mathematical logic problems

Prerequisites

BashRead access

Limitations

  • Limited to predicate logic scope
  • Requires specific script invocation patterns

How it compares

It automates complex logical derivations and model checking that would otherwise require manual truth table or natural deduction construction.

Compared to similar skills

predicate-logic side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
predicate-logic (this skill)27moReviewAdvanced
literature-review5592moReviewAdvanced
openalex-database487moReviewIntermediate
scientific-critical-thinking187moReviewAdvanced

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