categorical-meta-prompting
CommunityCategory-driven prompts with verifiable laws.
Software Engineering#meta-prompting#prompt-engineering#monad#functor#category-theory#comonad#compositional
Authormanutej
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides a mathematically rigorous framework to design deterministic, composable meta-prompting pipelines using category-theory concepts such as Functor, Monad, and Comonad, along with 0-1 quality tracking.
Core Features & Use Cases
- Formalizes prompt routing, iterative refinement, and context extraction across prompts.
- Provides Python-based skeletons implementing F, M, W, and [0,1]-enriched quality with practical integration patterns.
- Use cases include building reliable AI agents, scalable prompt ecosystems, and measurable quality control in prompt-driven workflows.
Quick Start
Install or run the Python skeleton in your environment, then adapt the F/M/W constructs to your prompts and integration points.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: categorical-meta-prompting Download link: https://github.com/manutej/categorical-meta-prompting/archive/main.zip#categorical-meta-prompting Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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