What the data for this category looks like
Aerospace equipment research reports primarily originate from securities firm defense and military industry research teams, publicly disclosed military industry announcements, and professional military industry information platforms. Update cycles include regular quarterly and annual industry review reports, as well as ad-hoc special reports issued after key events such as aircraft test flights, order placements, and policy announcements. Document structures typically include industry supply and demand data, core aircraft parameters, supplier cooperation information, and policy interpretation modules. Fields cover aircraft production capacity, order amounts, delivery cycles, and more. Units mostly adopt measurement standards combining industrial and financial metrics, such as units, ten thousand yuan, sets, and hours.
What constraints do these characteristics impose on tool calling and plugins?
The multi-source data sources of aerospace equipment research reports require tool calling to adapt to authentication rules of different interfaces. Some professional military industry information platforms require exclusive API keys for access. The fluctuating update frequency requires tools to support on-demand incremental pulling; fixed-cycle full synchronization will generate a large number of invalid calls. Documents contain both structured industrial parameters and unstructured policy interpretations. Tool calling needs to distinguish field types: normalize numerical fields and align industry terminology for text fields. Some sensitive data interfaces have call frequency limits, so current limiting rules need to be configured to prevent triggering risk control intercepts.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
mcp_tool_timeout | 300 seconds | Aerospace equipment research report analysis often involves multi-interface linkage and long-text parsing; 300 seconds can cover the complete process |
rag_recall_top_k | Top 8–12 entries | Research reports in this category contain multi-dimensional core data; 8-12 entries can cover three key types of information: aircraft, policies, and suppliers |
api_rate_limit | 10 calls per minute | Adapts to the call frequency limits of most military industry data sources, avoiding risk control intercepts |
tool_call_format | strict_json | Aerospace equipment research reports contain structured industrial parameters; strict JSON format ensures the completeness and readability of returned fields |
file_parse_chunk_size | 1000–1500 characters | Individual research reports have long content; this segment length balances context coherence and tool calling efficiency |
The parameter values provided on this page are general recommendations used as starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. Testing on internal samples is recommended before finalizing settings.
Three common mistakes
- When calling MCP tools, models deployed via Xinference return a 400 status code, but run normally when not calling tools. This occurs because exclusive authentication parameters for Xinference models are not added to the tool configuration, or the request body format does not match the tool calling template required by the model.
- When using the Claude4 model to call tools, SDK errors related to BedrockRuntime are returned. This occurs because the correct AWS region parameter is not configured, or the IAM role is not granted BedrockRuntime call permissions.
- The tool calling interface returns the
aiPointsNotEnougherror code. This occurs because the current account has insufficient AI call points to support the computing power required for tool calling.
How to confirm the configuration is complete
- Initiate a tool calling test to verify if returned results include core fields of aerospace equipment research reports, such as aircraft parameters and order information.
- Check tool calling logs to confirm the interface returns a 200 status code, with no 400, 403, or 500 level errors.
- Adjust tool calling parameters to validate that current limiting, timeout, and other configurations take effect. For example, manually trigger high-frequency calls to observe if current limiting intercepts are triggered.
- Compare manually extracted research report data with tool returned results to confirm the extraction accuracy of structured fields.
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.