When To Use It
- Production equipment, facility, after-sales, or field-service issues need to be registered quickly.
- Users describe a fault in natural language, and an Assistant should extract equipment, location, fault type, urgency, and initial diagnosis.
- Candidate data such as device types, fault categories, departments, roles, parts, and locations needs to be imported for normalized Assistant use.
- Maintenance supervisors need to supplement, confirm, reject, or close work orders from a review desk.
Plugin URL
Marketplace: Smart MaintenanceWhat The App Adds
| Type | Name | Purpose |
|---|---|---|
| Workbench view | Smart Maintenance Workbench | Import service data, submit repair reports, and review maintenance work orders. |
| Assistant template | Smart Maintenance Assistant | Generate draft work orders, query work orders, and prepare supplement drafts. |
| Assistant tools | Smart Maintenance Tools | Save AI-generated work orders, import service data, read catalog candidates, query work orders, and prepare supplement drafts. |
Recommended Roles
| Role | Main Responsibility |
|---|---|
| Intake user | Submit repair descriptions and let the Assistant create draft work orders. |
| Maintenance supervisor | Review fields, supplement details, confirm processing, or reject and close work orders. |
| Service-data admin | Import customers, projects, locations, devices, departments, roles, and parts. |
System Architecture
Smart Maintenance separates natural-language reports, candidate service data, AI-generated work orders, and human review actions. Assistant tools save draft data and query information, while Workbench view actions own all governed human state transitions.Processing Flow
The first version centers on an “AI-generated draft work order + human governance loop”. Imported service data improves field normalization. If fields are incomplete, the Assistant records completeness tips or supplement drafts instead of inventing missing facts.Recommended Flow
1. Import candidate service data
Upload a service-data file in Workbench, prepare a draft payload, then let the Assistant callsmart_maintenance_import_service_data to persist it. The catalog helps normalize device types, locations, departments, roles, parts, and fault categories.
If no service data has been imported, the App falls back to a built-in mock catalog for demos and early validation.
2. Generate a reviewable work order
Open Smart Maintenance Assistant and describe the issue, for example:smart_maintenance_save_generated_work_order to save a draft work order. When fields are incomplete, it should record completeness tips instead of inventing device numbers, contacts, occurrence time, or location.
3. Review in Workbench
Open Smart Maintenance Workbench to review work-order details. Users can edit title, equipment, location, fault category, urgency, description, AI diagnosis, and suggested actions. Confirm processing, mark processed, and reject/close actions are Workbench-only actions, not Agent tools. This prevents the Assistant from claiming that a job has been dispatched, repaired, or closed.4. Supplement and query work orders
When users provide additional information, the Assistant can callsmart_maintenance_prepare_supplement_draft to save a supplement draft. Reviewers can then apply and save it manually in Workbench. For list and detail queries, the Assistant can use smart_maintenance_search_work_orders and smart_maintenance_get_work_order_detail.
Tool Boundaries
| Tool | Purpose |
|---|---|
smart_maintenance_save_generated_work_order | Save a draft maintenance work order from a natural-language report. |
smart_maintenance_import_service_data | Persist a candidate service-data snapshot. |
smart_maintenance_get_catalog | Read candidate devices, faults, locations, departments, roles, and parts. |
smart_maintenance_search_work_orders | Search work orders by status, keyword, device type, and urgency. |
smart_maintenance_get_work_order_detail | Read one work order and its operation log. |
smart_maintenance_prepare_supplement_draft | Prepare an AI supplement draft from user-provided details. |
Data Quality
- AI diagnosis is preliminary and should keep a field-verification tone.
- Missing fields should be recorded in
completenessTips, not guessed. - One report should usually create one work order; multi-device or multi-fault descriptions should be marked as multiple issues.
- Confirmation, closure, and processing results require human action in Workbench.
- Operation logs should preserve AI creation, manual edits, supplements, confirmation, completion, and rejection events.