How does this differ from standard language type checking?

This skill specifically validates the composition of multi-step navigation paths, catching structural mismatches between data layers that standard compilers might only see at runtime.

Can it handle polymorphic or generic data structures?

Yes, it features a polymorphic inference engine that computes the most general type possible for a path, ensuring compatibility across various enumerable or indexed types.

Does using type validation impact application performance?

No. All type inference and validation occur during the path expansion and caching phase. Once validated, the operations run at native speeds with zero additional overhead.

What happens if a type mismatch is detected?

The skill provides a clear error message identifying exactly which step in the navigation path failed, the expected type, the actual type received, and a suggestion for a fix.

Type Inference & Validation

Name: Type Inference & Validation
Author: plurigrid

byplurigrid

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开发者工具

Enforces static type safety for navigation paths to prevent runtime structural errors through compile-time validation.

This skill provides a robust static type inference system for Navigator paths, ensuring that structural compositions are validated before execution or caching. By mapping input types to specific output signatures, it identifies incompatible operations—such as applying vector enumeration to dictionaries—at compile time. It serves as a critical safety layer that eliminates structural impossibilities, allowing developers to catch errors early in the development cycle. This skill integrates seamlessly with topological filtering to guarantee that data navigation is both mathematically sound and type-safe, significantly reducing debugging effort and runtime failures in complex data pipelines.

主要功能

01Refinement types for predicate-based value validation (e.g., Int to EvenInt)

02Static type refinement pipeline for complex navigation paths

03Polymorphic inference for generalized data structure compatibility

04Detailed compile-time error reporting with automated suggestions

05Zero-cost runtime overhead via pre-cached type signatures

067 GitHub stars

使用场景

01Preventing runtime IndexErrors and TypeErrors in complex nested data pipelines

02Ensuring type consistency in polymorphic data processing across different container types

03Validating deeply nested JSON, Dict, or S-Expression traversals statically

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi type-inference-validation

For use in Claude.ai and ChatGPT

Download Skill