What the data for this category looks like
Commercial real estate yield-related data primarily comes from commercial property operation ledgers, business district lease transaction filing systems, and third-party commercial real estate data aggregation platforms. Data updates follow a set rhythm: monthly updates for rent and operation cost details, quarterly updates for overall net operating yield calculation results. Each data document uses a structured table format. Each row corresponds to one independent commercial real estate project, and includes fields such as project unique identifier, project location, rentable area, actual occupancy rate, average monthly rent income, annual operating cost, net operating income during the accounting period, and net operating yield. The unit of rentable area is square meters. The unit of average monthly rent income is yuan per square meter per month. The units of annual operating cost and net operating income are ten thousand yuan. Net operating yield is a proportional value.
What constraints do these characteristics impose on "tool calling and plugins"?
The multi-source and scattered nature of commercial real estate data requires tool calling to configure multi-API aggregation logic. This avoids obtaining only one-dimensional data in a single call. The monthly and quarterly update rhythm requires the tool trigger cycle to match the data update frequency. This prevents frequent calls that cause interface rate limiting or invalid requests. Fields include multiple types of units and linked calculation logic. Plugins must include built-in unit verification and field linkage rules. This prevents calculation errors caused by inconsistent units or missing fields. The strong binding of project unique identifiers requires that tool calling parameters must carry the project ID. This avoids mixing data from different projects. At the same time, the accounting logic of commercial real estate data relies on multi-field linkage. The order and completeness of tool calling parameters must strictly match the structure requirements of the data document. Otherwise, the yield calculation result will be distorted.
How to set the configurations
| Configuration Item | Recommended Value | Basis for This Value |
|---|---|---|
timeout | 300 seconds | Commercial real estate data interfaces usually aggregate multi-source information, so response times are relatively long |
retryCount | 2 times | Some third-party commercial real estate data interfaces have temporary fluctuations; a small number of retries can improve call success rates |
paramSchema | Configure project ID and accounting period as required verification items | Commercial real estate project data must be bound to a unique identifier and accounting period to avoid data mixing |
apiAuthType | API_KEY authentication | Most commercial real estate data interfaces use key authentication to ensure data security |
mergeMode | Merge after deduplicating by project ID | Duplicate project entries may exist during multi-source data aggregation, so a unified deduplication rule is required |
scheduleCron | 0 0 2 1 */3 * | Commercial real estate yield data is updated quarterly. This expression matches triggering at 2 AM on the first working day of each quarter |
The parameter values provided on this page are all conventional recommendations, used as a starting point for determining configurations. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing the configuration.
Three common mistakes
- Issue: Calling the
apiCollectioninterface returns theInvalid URL, code: 500error. Cause: No valid commercial real estate data interface domain name is configured, or the interface address has a spelling error that causes parsing failure. - Issue: Returns the
400 <400> InternalError.Algo.InvalidParameter: Multimodal file size iserror. Cause: The uploaded commercial real estate operation data file exceeds the maximum size supported by the tool node, or the file contains unparsed multimedia content. - Issue: The output of the tool calling module in the workflow cannot be canceled, causing unnecessary content to be returned. Cause: The output passthrough option is not turned off in the tool node settings, or no output field filtering rules are configured.
How to confirm the configuration is complete
- Manually trigger a tool call, check that the returned fields include the necessary identifiers and yield data for commercial real estate projects, and that the field units conform to preset rules.
- Check the scheduled trigger configuration, confirm that the trigger cycle matches the update rhythm of commercial real estate data. Workflow logs can be viewed to verify whether the trigger executes on time.
- Upload a test commercial real estate data file, check that the parameter verification rules block invalid input, such as non-numeric rent data.
- View the output configuration of the tool node, confirm that only the fields that need to be returned are retained, and no redundant content is passed through.
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.