What the Data for This Category Looks Like
Data for general equipment research reports comes from domestic top securities firms' machinery equipment industry research teams and public industry reports from the China General Machinery Industry Association. Update frequencies include monthly tracking reports, quarterly in-depth research reports, and real-time reports for sudden policy events. Document structures typically include overall industry supply and demand data, segment capacity utilization rates, key enterprise operating indicators, and core product technical parameters. Fields include equipment output (unit: units/sets), revenue scale (unit: ten thousand yuan), year-on-year growth rate (unit: %), equipment operating efficiency (unit: %), and other structured information. Some in-depth reports also include technical parameter details for specific models.
What Constraints Do These Characteristics Impose on Tool Calling and Plugins?
General equipment research reports have numerous structured fields with clear units, requiring strict verification of unit matching between parameters and fields during tool calling to avoid invalid parsed results. Multiple update types require plugins to support both full pull and incremental pull modes to meet timeliness requirements of different retrieval scenarios. Single in-depth research reports are lengthy, averaging 8000-10000 characters, so tool calling must support segmented parsing and context splicing to prevent exceeding the model's context window. Additionally, core analysis dimensions are relatively fixed, so tools must support specifying returned fields to reduce redundant data transmission and model processing overhead.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MCP_SERVICE_TIMEOUT | 180 seconds | Average time to parse and extract data from general equipment in-depth research reports is approximately 120-150 seconds, with sufficient buffer time to accommodate adjustments for the 4.9.6 version's default 90-second timeout threshold |
RESEARCH_REPORT_FIELD_FILTER | Output, Revenue, Capacity Utilization Rate, Unit | Core analysis dimensions of general equipment research reports are the fields listed above; filtering non-essential fields reduces data transmission overhead |
RECALL_TOP_N | Top 8 entries | Single general equipment research report has high information density; too many recalled results will exceed the general model's context window |
PARSE_DOC_MAX_LENGTH | 12000 characters | Average length of general equipment in-depth research reports is approximately 8000-10000 characters; reserving reasonable truncation space avoids content loss |
MCP_PARAM_TYPE_AUTO_DETECT | Enabled | Parameters in general equipment research reports include multiple types such as numerical values, percentages, and units; automatic detection prevents parameter parsing errors caused by fixed string type |
INCREMENTAL_UPDATE_SWITCH | Enabled | General equipment industry data has diverse update frequencies; incremental pull reduces repeated calculations and resource usage |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and testing on local samples prior to finalization is recommended.
Three Common Misconfigurations
- Calling the MCP service with a timeout longer than 90 seconds returns the
MC | 是否停止输出的 api 接口可供调用 | chat:LLM_model_response_emptyerror. The cause is failing to adjust theMCP_SERVICE_TIMEOUTconfiguration item, using the default 90-second timeout threshold which cannot accommodate the long time required for general equipment research report parsing. - Numeric fields in retrieval results are empty or formatted incorrectly. The cause is failing to enable the
MCP_PARAM_TYPE_AUTO_DETECTconfiguration, with tool calling parameters forcibly fixed to thestringtype, which cannot correctly parse structured fields such as numerical values and percentages. - Recalled research report results contain a large amount of non-core information or exceed the model's context window. The cause is failing to configure the
RECALL_TOP_NandPARSE_DOC_MAX_LENGTHparameters, using the default excessive number of recalled entries and failing to truncate long documents, resulting in the model being unable to effectively process input content.
How to Confirm Proper Configuration
- View MCP service runtime logs to confirm call duration does not trigger timeout errors, and adjust
MCP_SERVICE_TIMEOUTbased on actual parsing duration. - Initiate a single test call to verify returned parameter types match actual fields, confirming
MCP_PARAM_TYPE_AUTO_DETECTis enabled. - Retrieve research reports for a specified general equipment segment, verify returned fields include preset core analysis dimensions, confirming
RESEARCH_REPORT_FIELD_FILTERis configured correctly. - Test long document parsing scenarios to verify returned content is properly truncated, confirming
PARSE_DOC_MAX_LENGTHadapts to current document length.
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.