uv-bootstrap-ml-knowledge-authoring

Scaffold new ML knowledge skills with predefined repository structure and naming conventions.

1|Updated Feb 6, 2026

Search Tags:#scaffolding #skill authoring #template generation #developer tooling #ml knowledge #repository convention

Ready to run

npx skills add https://github.com/uv-xiao/pkbllm --skill uv-bootstrap-ml-knowledge-authoring

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: uv-bootstrap-ml-knowledge-authoring
Source: https://github.com/uv-xiao/pkbllm/tree/main/bootstrap/ml-knowledge-authoring
Command: npx skills add https://github.com/uv-xiao/pkbllm --skill uv-bootstrap-ml-knowledge-authoring

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of creating and maintaining new Machine Learning domain knowledge skills within the pkbllm repository, ensuring consistency and adherence to established conventions.

Core Features & Use Cases

Scaffolds New Skills: Automatically generates the directory structure and a template SKILL.md for new ML skills.
Enforces Naming Conventions: Ensures all new skill names start with uv-.
Guides Taxonomy Placement: Directs new skills into one of the predefined ML categories.
Promotes House Style: Provides a checklist for essential SKILL.md sections and content quality.
Use Case: When you need to add a new skill for a novel ML model architecture, use this skill to quickly set up the necessary files and adhere to the repo's standards.

Quick Start

Use the uv-bootstrap-ml-knowledge-authoring skill to scaffold a new skill for FlashInfer kernels under the model-architecture category.

Frequently Asked Questions about uv-bootstrap-ml-knowledge-authoring

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I scaffold a new Machine Learning knowledge skill?▼

To scaffold a new Machine Learning knowledge skill, use this tool to automatically generate the predefined repository directory structure and a template SKILL.md file, ensuring consistent house style and taxonomy placement.

What naming conventions are enforced for ML skill authoring?▼

ML skill authoring enforces strict naming conventions where all new skill names must start with the uv- prefix, ensuring repository consistency and immediate identification across the machine learning knowledge base.

What predefined categories exist for ML knowledge repository skills?▼

Predefined categories for ML knowledge repository skills include model-architecture, training, distributed, serving, paper, kernel, and agents, directing new skills into a consistent taxonomy for organized domain knowledge.

Do I need Python to generate ML knowledge skill templates?▼

Yes, you need Python 3 and standard library access to execute the scripts that generate ML knowledge skill templates, enforcing repository conventions and scaffolding the directory structure.

What is the best way to ensure new ML skills adhere to house style?▼

The best way to ensure new ML skills adhere to house style is using a scaffolding tool that provides a checklist for essential SKILL.md sections and content quality guidelines during template generation.