Best use case
smt-solver-interface is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Interface with SMT solvers for verification and synthesis
Teams using smt-solver-interface 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/smt-solver-interface/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How smt-solver-interface Compares
| Feature / Agent | smt-solver-interface | 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?
Interface with SMT solvers for verification and synthesis
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
# SMT Solver Interface ## Purpose Provides expert guidance on using SMT solvers for automated reasoning, verification, and program synthesis. ## Capabilities - Z3 query generation - CVC5 interface - Theory selection guidance - Model extraction - Unsat core analysis - Incremental solving ## Usage Guidelines 1. **Encoding**: Encode problem in SMT-LIB format 2. **Theory Selection**: Choose appropriate theories 3. **Solving**: Run SMT solver 4. **Model Extraction**: Extract satisfying assignments 5. **Debugging**: Analyze unsat cores for debugging ## Tools/Libraries - Z3 - CVC5 - Boolector - Yices
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