Tool Calling and Plugins for Industrial Park Research Report

What the Data for This Category Looks Like

Industrial park research report data mainly comes from public disclosure documents of park management committees, internal operation monthly reports of park operators, and special reports from third-party industry research institutions. The data update rhythm varies: public data from management committees is updated quarterly, operator monthly reports are updated monthly, and third-party special reports are released quarterly or semi-annually. Document structures typically include park location parameters, industry distribution of settled enterprises, land and building leasing data, and policy support items. Fields include "mu-average tax revenue" (unit: ten thousand yuan/mu), "leased construction area" (unit: square meters), "number of settled enterprises", and other items. The length of individual documents varies widely; it is recommended to determine based on statistics or actual measurement of the reader's own samples.

Constraints Imposed on Tool Calling and Plugins by These Characteristics

Data for industrial park research reports comes from scattered sources, has varying update rhythms, and individual documents are relatively long. These characteristics create multiple constraints for tool calling and plugins. Multi-source data requires calling multiple interfaces including park management committee disclosures, operator monthly reports, and third-party research. Implement parallel calling logic for multiple tools. Different data sources have different update cycles. Set a matching cache duration for each tool to avoid expired or redundant data. Individual documents are relatively long. Limit the context interception range during tool calling to prevent exceeding the model's context window. Fields include specific units. Add unit verification logic to tool return results to ensure unified data formatting.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`maxToolCalls`	`3–5 times`	Industrial park research reports require calling up to 3 core data source types; excessive calls will increase response latency
`toolTimeout`	`120–180 seconds`	Individual documents for industrial park research reports are relatively long, so tool call parsing requires more time to avoid timeout interruptions
`retrieveTopK`	`Top 8–12 items`	Industrial park research reports include multi-dimensional data fields, so a sufficient number of relevant fragments must be retrieved to cover different data dimensions
`allowedSources`	`["park disclosure API", "operator monthly report API", "third-party research API"]`	Industrial park research report data comes from three core channels, so legitimate call sources must be limited
`cacheTtlPerSource`	`Set per data source: park disclosure API 604800 seconds, operator API 86400 seconds`	Different data sources have different update rhythms; matching corresponding cache durations reduces invalid calls
`responseFieldCheck`	`["mu-average tax revenue", "leased construction area"]`	Industrial park research reports have specific unit fields, so return results must be verified to include specified fields and their units

The parameter values provided on this page are common recommendations for establishing configuration starting points. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis, and it is recommended to perform actual testing on the reader's own samples before finalizing settings.

Three Common Configuration Mistakes

Issue: Tool calls return an Invalid JSON error, and logs contain a Bad control character prompt. Cause: Documents in industrial park research reports contain unescaped control characters such as line breaks and tabs, and no escaping processing was performed on returned content before tool calling.
Issue: Tool calls return empty results with no valid data returned. Cause: No API key or interface permissions for the corresponding data source were configured, or the recall threshold was set too high, resulting in no matching fragments.
Issue: Tool call count exceeds expectations, and response latency is too high. Cause: The maxToolCalls parameter value was not limited, or cache duration was set too short, resulting in repeated calls to multiple data sources.

How to Verify Proper Configuration

Initiate a single query related to industrial park research reports, check the tool call log, and confirm that the called data sources match the configured allowedSources.
Check the tool return results, and confirm that they include the fields and their corresponding units specified in the configured responseFieldCheck.
View the cache statistics panel, and confirm that the cache duration for different data sources complies with the configured cacheTtlPerSource rules.
Simulate multiple identical queries, and confirm that the tool call count does not exceed the configured maxToolCalls value.

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.