How does this skill use CPMpy?

It translates software logic—such as dependency graphs or resource limits—into CPMpy models to solve for feasibility or detect logical conflicts.

Can it detect circular dependencies?

Yes, it can model module relationships and verify if a valid topological ordering exists, identifying cycles that would break the system build.

How does it integrate with Recursive Language Models (RLM)?

In RLM workflows, this skill acts as a safety gate at deeper reasoning levels to verify proposed changes against system constraints before they are finalized.

What is the Constraint Verification skill?

It is a specialized Claude Code capability that uses constraint programming to verify that code changes adhere to defined logical rules and system invariants.

Is it useful for automated testing?

Absolutely; it can generate specific input values that satisfy complex path constraints, helping developers achieve higher test coverage for edge cases.

Constraint Verification

Name: Constraint Verification
Author: rand

byrand

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安全与测试

Verifies code invariants and complex logic constraints using constraint programming to ensure system stability and correctness.

关于

The Constraint Verification skill empowers Claude Code with the ability to perform rigorous logical analysis on software systems. By leveraging the CPMpy library, it allows Claude to model dependencies, resource bounds, type compatibility, and state machines as constraint satisfaction problems. This is particularly useful for verifying that proposed code changes do not violate architectural invariants or resource limits, providing a formal layer of safety during automated refactoring, complex system design, or scheduling tasks.

主要功能

Type compatibility modeling for complex subtype relationships
Integration with Recursive Language Models (RLM) for depth-based safety verification
Resource bound checking for scheduling and capacity feasibility
State machine validation to ensure valid transition paths
Automated dependency graph verification to detect circular references
9 GitHub stars

使用场景

Generating test inputs that satisfy complex path constraints for edge-case coverage
Ensuring task schedules fit within hardware or resource constraints in systems programming
Verifying that a refactor does not introduce circular dependencies in a modular architecture

关于

主要功能

Type compatibility modeling for complex subtype relationships
Integration with Recursive Language Models (RLM) for depth-based safety verification
Resource bound checking for scheduling and capacity feasibility
State machine validation to ensure valid transition paths
Automated dependency graph verification to detect circular references
9 GitHub stars

使用场景

Generating test inputs that satisfy complex path constraints for edge-case coverage
Ensuring task schedules fit within hardware or resource constraints in systems programming
Verifying that a refactor does not introduce circular dependencies in a modular architecture