Which programming languages are supported?

The skill supports over 8 languages, including Rust (contracts crate), TypeScript (Zod), Python (icontract), Java, Kotlin, and C++ (GSL/Boost).

How does it help with debugging contract violations?

The skill includes a remediation phase that helps diagnose whether a violation is a Precondition (caller's fault), Postcondition (callee's fault), or Invariant (state management issue).

Does this skill provide static or runtime verification?

Both. It follows a verification hierarchy that prioritizes static assertions at compile-time but provides runtime contracts when static verification is not possible.

What is Design-by-Contract (DbC)?

Design-by-Contract is a programming methodology that uses formal specifications (contracts) to define component behavior through preconditions, postconditions, and invariants.

Design-by-Contract (DbC) Development

Name: Design-by-Contract (DbC) Development
Author: Microck

byMicrock

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Security & Testing

Implements formal contract verification and remediation across multiple programming languages to ensure code correctness and reliability.

About

This skill empowers developers to apply Design-by-Contract (DbC) principles within their Claude Code environment. It provides a structured four-phase workflow—Plan, Create, Verify, and Remediate—to define and enforce preconditions, postconditions, and invariants. By automating contract generation for over 8 languages (including Rust, TypeScript, and Python) and integrating with verification hierarchies, it helps bridge the gap between formal specifications and production-ready implementation, making it indispensable for safety-critical systems, complex state management, and robust API boundaries.

Key Features

Structured Plan-Create-Verify-Remediate workflow
81 GitHub stars
Multi-level verification hierarchy (Static vs. Runtime)
Targeted remediation strategies for contract violations
Automated contract annotation generation for 8+ languages
Support for preconditions, postconditions, and invariants

Use Cases

Formalizing component behavior documentation through executable code
Maintaining object state consistency in complex business logic
Securing public API boundaries with robust input validation

About

Key Features

Structured Plan-Create-Verify-Remediate workflow
81 GitHub stars
Multi-level verification hierarchy (Static vs. Runtime)
Targeted remediation strategies for contract violations
Automated contract annotation generation for 8+ languages
Support for preconditions, postconditions, and invariants

Use Cases

Formalizing component behavior documentation through executable code
Maintaining object state consistency in complex business logic
Securing public API boundaries with robust input validation