What the Data for This Category Looks Like
Data sources for automated equipment yield rate data include local runtime logs from the device's built-in PLC collection module, and cloud settlement data synchronized by industrial IoT gateways. Data updates follow a fixed daily schedule, aggregating full-cycle operation data from the previous day, and synchronizing daily data for a single batch of devices in one batch request. Each data entry corresponds to one device, with fields including: unique device identifier, total cumulative runtime, energy consumption per unit output, number of qualified products, total daily revenue, and revenue rate per unit time. The corresponding units for each field are hours, kilowatt-hours per piece, pieces, CNY, and CNY per hour.
What Constraints These Characteristics Impose on Tool Calling and Plugins
The multi-source, dispersed nature of automated equipment yield rate data means tool calling must support two authentication modes: the device's local Modbus interface and the cloud industrial internet platform API. This avoids call interruptions caused by single-source dependency. The fixed daily update rhythm means plugin scheduled trigger configurations must match the data synchronization window. This prevents empty results from requests made before data generation. The multi-field and specific unit structure means the plugin's parameter parsing module must pre-set field and unit mapping rules. This avoids unit confusion or field identification errors from generic parsing. The batch single-batch device synchronization feature means tool calling must support passing batch device ID parameters. This reduces network overhead and response latency for single requests.
How to Configure Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
mcp_server_url | Device local API address / cloud industrial internet platform interface address | Matches the multi-source access requirements of automated equipment data, supports switching between local and cloud data sources |
auth_type | Choose one of ["device_local", "cloud_iot"] | Corresponds to two authentication modes for device-side and cloud environments, adapts to authentication logic for different data sources |
schedule_cron | 0 8 * * * (8 AM Beijing Time) | Matches the daily generation window of automated equipment yield rate data, ensures calls are initiated after data is generated |
batch_device_ids | Within 100 devices per batch | Avoids interface timeouts caused by overly long single request parameters, adapts to the feature of batch synchronization for single batches of devices |
parse_field_mapping | Configure mapping relationships according to the actual fields of equipment data | Matches the field structure of automated equipment data, ensures parsed fields meet downstream usage requirements |
request_timeout | 300 seconds | Adapts to network latency for pulling batch device data, avoids request interruptions caused by large data volumes |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: Calls return a
401 Unauthorizederror. Cause: Failure to distinguish between device local and cloud authentication methods, mixing keys and tokens from the two authentication modes. - Symptom: Yield rate data generated by the plugin has inconsistent units, such as identifying
CNY per hourasCNY. Cause: No unit mapping rules configured forparse_field_mapping, using a generic parsing module that causes field unit loss. - Symptom: Device ID fields cannot be recognized during MCP format calls. Cause: The MCP parameter template was not adjusted according to the field structure of automated equipment data, using a generic field template.
How to Confirm Configuration Is Complete
- Initiate a single test call, check if the returned fields match the structure of automated equipment yield rate data, and verify that field names and units conform to preset mapping rules.
- View tool call logs, confirm that the authentication request returns a
200 OKstatus code, with no authentication-related error messages. - Trigger a scheduled task, check that requests are initiated within the preset scheduling window, and that the returned data volume matches the preset number of batch devices.
- Adjust the field mapping configuration, verify that returned data units can be correctly identified and output, ensuring no unit confusion issues during downstream usage.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.