How does this help with type safety?

It implements refinement typing, allowing the system to prove and track specific properties (like 'EvenPositiveInt') rather than just basic types like 'Int'.

Does it support complex logical operations?

Yes, it uses a constraint lattice to handle conjunctions (AND), disjunctions (OR), and negations (NOT) using Conjunctive Normal Form (CNF).

What happens if constraints are contradictory?

The skill utilizes the 3-MATCH solver to detect unsatisfiable constraints (UNSAT) and will reject invalid compositions with specific error handling.

Is this skill compatible with Julia?

Yes, the implementation patterns and syntax are designed for Julia-based navigator systems and integrated type inference engines.

What is constraint generalization?

It is the process of synthesizing new, proven constraints that hold true when multiple data navigation paths are combined, ensuring logical invariants are preserved during composition.

Constraint Generalization Logic

Name: Constraint Generalization Logic
Author: plurigrid

byplurigrid

•

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Synthesizes and propagates formal constraints across complex data navigation paths using refinement typing.

Constraint Generalization is a sophisticated skill designed for developers working with complex data structures and formal verification. By leveraging constraint logic programming and abstract interpretation, it enables the automatic synthesis of new constraints when composing data navigators. Instead of losing information during path composition, this skill maintains a constraint lattice, ensuring that properties like type safety, value ranges, and mathematical invariants are proven and propagated throughout the entire processing pipeline. It integrates with the 3-MATCH solver to validate satisfiability and generate formal proof certificates, moving beyond simple validation to active constraint generation.

主な機能

01Refinement typing for enhanced compile-time and run-time safety

02Abstract interpretation to weaken or generalize specific constraints

03Automatic constraint propagation across composed navigation paths

04Satisfiability checking via integrated 3-MATCH logic

057 GitHub stars

06Formal proof certificate generation for constraint validation

ユースケース

01Building self-validating data pipelines that maintain mathematical invariants

02Generating formal proofs for data transformation logic in high-assurance software systems

03Developing complex filtering systems where multi-stage constraints must be proven satisfiable

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi constraint-generalization

For use in Claude.ai and ChatGPT

Download Skill