loop-invariant-generator
Automatically generate and verify loop invariants for algorithm correctness proofs
Best use case
loop-invariant-generator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Automatically generate and verify loop invariants for algorithm correctness proofs
Teams using loop-invariant-generator 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/loop-invariant-generator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How loop-invariant-generator Compares
| Feature / Agent | loop-invariant-generator | 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?
Automatically generate and verify loop invariants for algorithm correctness proofs
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
# Loop Invariant Generator ## Purpose Provides expert guidance on generating and verifying loop invariants for algorithm correctness proofs using formal methods. ## Capabilities - Infer candidate loop invariants from code structure - Verify initialization, maintenance, and termination conditions - Generate formal proof templates - Handle nested loops and complex data structures - Export to theorem provers (Dafny, Why3) - Suggest invariant strengthening ## Usage Guidelines 1. **Code Analysis**: Analyze loop structure and identify key properties 2. **Candidate Generation**: Generate candidate invariants from code patterns 3. **Verification**: Check initialization, maintenance, termination 4. **Strengthening**: Refine invariants to prove desired properties 5. **Export**: Generate proof obligations for theorem provers ## Tools/Libraries - Dafny - Why3 - SMT solvers (Z3, CVC5) - Static analysis frameworks
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