Best use case
proof-theory is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Problem-solving strategies for proof theory in mathematical logic
Teams using proof-theory should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/proof-theory/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How proof-theory Compares
| Feature / Agent | proof-theory | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Problem-solving strategies for proof theory in mathematical logic
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Proof Theory ## When to Use Use this skill when working on proof-theory problems in mathematical logic. ## Decision Tree 1. **Proof Strategy Selection** - Direct proof: assume premises, derive conclusion - Proof by contradiction: assume negation, derive false - Proof by cases: split on disjunction - Induction: base case + inductive step 2. **Structural Induction** - Define well-founded ordering on structures - Base: prove for minimal elements - Step: assume for smaller, prove for current - `z3_solve.py prove "induction_principle"` 3. **Cut Elimination** - Gentzen's Hauptsatz: cuts can be eliminated - Subformula property: only subformulas appear - Useful for proof normalization 4. **Completeness/Soundness Check** - Soundness: if provable then valid - Completeness: if valid then provable - `z3_solve.py prove "soundness_theorem"` 5. **Proof Verification** - Check each step follows from rules - Verify dependencies are satisfied - `math_scratchpad.py verify "proof_steps"` ## Tool Commands ### Z3_Induction_Base ```bash uv run python -m runtime.harness scripts/cc_math/z3_solve.py prove "P(0)" ``` ### Z3_Induction_Step ```bash uv run python -m runtime.harness scripts/cc_math/z3_solve.py prove "ForAll([n], Implies(P(n), P(n+1)))" ``` ### Z3_Soundness ```bash uv run python -m runtime.harness scripts/cc_math/z3_solve.py prove "Implies(derivable(phi), valid(phi))" ``` ### Math_Verify ```bash uv run python -m runtime.harness scripts/cc_math/math_scratchpad.py verify "proof_structure" ``` ## Cognitive Tools Reference See `.claude/skills/math-mode/SKILL.md` for full tool documentation.
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