Automotive Motor QE Inspection SOP Agent

Problem

For automotive motor companies, QE inspection SOPs usually require engineers to collect data, flag anomalies, draft guidance, and mark human checkpoints. Manual workflows can suffer from inconsistent wording, missing fields, accidental reliance on external systems, and AI conclusions being mistaken for approved decisions. This skill turns the SOP into a runnable workflow: it reads built-in mock_data, executes scripts/run_demo.py, and generates demo_result.md, then reports processed inputs, findings, and next steps in a real business tone while stating that the AI only drafts the document and does not replace QE judgment.

How It Works

• Input: the user requests a QE inspection SOP in a real business tone.
• Data: uses built-in assets/mock_data/; it does not depend on real PLM, ERP, email, or CAD systems.
• Execution: runs scripts/run_demo.py in the current directory or a specified output directory.
• Output: reads demo_result.md, reports conclusions and next steps; if .xlsx exists, it can prompt the user to open Excel.

Boundaries

• Do not present mock results as production data.
• Do not claim connected customer systems.
• Do not skip human confirmation points.
• If real integration is required, customers must provide APIs, sample data, permissions, and a test environment.