Does this skill support interactive proof solving?

Yes, it supports interactive development through typed holes and integrates with the ProofGeneral interaction mode.

What is the primary purpose of Narya Hatchery?

Narya Hatchery is a proof assistant implementation used for working with higher-dimensional observational type theory and formal verification.

Can I use Narya for coinductive programming?

Yes, Narya supports both inductive datatypes and coinductive codatatypes with matching and comatching case trees.

What are 'Bridge Types' in Narya?

Bridge types in Narya generalize equality and satisfy parametricity, allowing for higher-dimensional structural reasoning within the type theory.

How is Narya installed?

Narya is typically built from source using OCaml's dune build system after cloning the repository from GitHub.

Narya Hatchery

Name: Narya Hatchery
Author: plurigrid

byplurigrid

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Developer Tools

Implements a higher-dimensional observational type theory proof assistant for formal verification and complex mathematical modeling.

Narya Hatchery is a specialized skill designed to interface with the Narya proof assistant, a system built on multi-modal, multi-directional, and higher-dimensional type theory. It provides developers and researchers with the tools to work with observational-style theories, utilizing bridge types to satisfy parametricity and generalized equality. With features like normalization-by-evaluation, mixfix notation support, and ProofGeneral interaction, it simplifies the process of developing formal proofs and managing inductive or coinductive datatypes in a mathematically rigorous environment.

Key Features

01Interactive proof development via typed holes and ProofGeneral integration

02Higher-dimensional observational type theory with bridge and identity types

03Normalization-by-evaluation (NbE) algorithm for efficient typechecking

042 GitHub stars

05Support for user-definable mixfix notations and matching case trees

06Multi-modal integration for separate compilation and chromatic gamut learning

Use Cases

01Developing and testing new inductive and coinductive datatypes

02Formally verifying complex software contracts and mathematical theorems

03Implementing higher-dimensional parametricity models in type theory

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi narya-hatchery

For use in Claude.ai and ChatGPT

Download Skill