What are structural invariants?

Structural invariants are properties of a data structure that must always remain true for the program to function correctly, such as the number of squares in a grid or the symmetry of links in a graph.

How does this differ from standard unit testing?

While it is a form of testing, it focuses specifically on the 'shape' and 'internal logic' of data structures rather than just the output of a single function or method.

When should I use this skill?

Use this skill immediately after building complex data structures, verifying precomputed relationships, or ensuring that initialization logic has correctly populated your objects.

Is this suitable for performance-critical runtime code?

Generally no. These checks are best used during initialization or within test suites, as complex structural assertions can introduce overhead in high-frequency runtime loops.

Structural Invariant Testing

Name: Structural Invariant Testing
Author: jimmc414

byjimmc414

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Security & Testing

Validates complex data structures by enforcing size, relationship, and consistency constraints to ensure internal integrity.

The Structural Invariant Testing skill implements a rigorous validation pattern inspired by Peter Norvig's 'pytudes,' focusing on the verification of data structure integrity immediately following construction. It enables Claude to proactively test lengths, bidirectional relationships, and coverage constraints within code, ensuring that initialization logic is correct before execution. This approach is particularly valuable for complex algorithms, graph structures, and mathematical models where subtle initialization errors can lead to difficult-to-debug runtime issues.

Key Features

01Size and count validation for data structures

02Post-initialization integrity testing

03Coverage and key set constraint verification

04Bidirectional and symmetric relationship verification

05Universal check syntax using clean assertions

061 GitHub stars

Use Cases

01Ensuring corpus statistics and data loaders match expected counts

02Validating precomputed mathematical tables and constant sets

03Verifying graph connectivity and symmetry in network models

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jimmc414/claude-code-plugin-marketplace test-structural-invariants

For use in Claude.ai and ChatGPT

Download Skill