shopfloor-ai

Orchestrate ShopFloor AI onboarding from shop-reference creation to SME management.

Updated Jun 2, 2026
One-click install
npx skills add https://github.com/tot3lis/ShopFloor-AI --skill shopfloor-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: shopfloor-ai
Source: https://github.com/tot3lis/ShopFloor-AI/tree/main/.agents/skills/shopfloor-ai
Command: npx skills add https://github.com/tot3lis/ShopFloor-AI --skill shopfloor-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

ShopFloor AI orchestration unifies messy shop data and onboarding steps into a single public-facing orchestrator, coordinating the end-to-end workflow from shop context generation to SME shells and knowledge packs. It ensures consistency across onboarding stages and routes ready-state questions to the SME Manager by default, without bypassing the core Layer 1-4 stack.

Core Features & Use Cases

  • End-to-end orchestration of the ShopFloor AI onboarding flow from raw inputs to finalised shop-reference, SME shells, and knowledge packs.
  • Shop context construction from attached routers, machine lists, work orders, travelers, and operation files to build a shop-specific reference.
  • SME lifecycle management by coordinating SME Generator and SME Knowledge Builder and producing the necessary outputs for SME routing.
  • Question-mode readiness enabling the SME Manager to answer shop questions once all outputs exist.
  • Input-source agnostic workflow that uses provided shop data (inputs/attachments) while ignoring non-shop public docs unless supplied.

Quick Start

Say "run shopfloor-ai" with your attached inputs to start the full onboarding flow.

Frequently Asked Questions about shopfloor-ai

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

FAQPage Schema
How do I build shop context from messy manufacturing data like routers and travelers?

Shop context creation processes attached routers, machine lists, work orders, and travelers to construct a unified shop-specific reference. This onboarding orchestration unifies messy shop data into structured context for downstream knowledge generation.

How do I generate SME knowledge packs from unstructured shop floor operation files?

Generating SME knowledge packs from operation files requires running the SME Generator and SME Knowledge Builder stages. This orchestration transforms raw shop floor data into structured SME shells and knowledge packs for query routing.

What is the best way to automate manufacturing onboarding from raw work orders to a ready-for-questions state?

Automating manufacturing onboarding from work orders to a ready-for-questions state requires an end-to-end orchestration workflow. It coordinates ShopContext, SME Generator, and SME Knowledge Builder stages to produce outputs enabling SME Manager question routing.

Can I use pasted data and non-shop public documents for shop floor onboarding?

You can use pasted data for shop floor onboarding since the workflow accepts pasted data alongside attached files. However, it specifically ignores non-shop public documents unless you explicitly supply them as attached inputs.

Does shop floor onboarding orchestration bypass the core Layer 1-4 stack?

Shop floor onboarding orchestration does not bypass the core Layer 1-4 stack. It coordinates the workflow from shop context generation to SME knowledge packs, ensuring consistency while routing ready-state questions to the SME Manager by default.