What the data for this category looks like
Data for coking coal due diligence reports covers public trading and operational data from domestic major producing area mines, northern transfer ports, and downstream steel industry chains. Different dimension data updates follow their respective trading cycles. Spot data syncs in real time with trading actions. Industry statistical data is released on a monthly cycle. Each single data document includes five modules: producing area listed price, index test values, regional inventory, cross-regional transportation costs, and downstream demand forecast. Fields include major producing area code, ash content, sulfur content, caking index, and colloidal layer thickness. Units are respectively producing area code, dry basis mass percentage, dry basis mass percentage, dimensionless, and millimeters.
What constraints these characteristics impose on tool calling and plugins
The multi-source and dispersed nature of coking coal data requires tool calling plugins to adapt to interface formats and authentication rules of different data sources. This prevents single calls from failing to cover all data dimensions. The update cycles of different data dimensions vary widely. Independent pull frequency parameters must be configured for different data modules to avoid invalid requests or data lag. Document modules are fixed but numerous. Plugins must support split parsing by module to prevent single documents from exceeding model context length limits. Field standardization needs are prominent. Some data sources have differing index names and units. Built-in field mapping rules must be included in the tool calling process to ensure consistency of extracted data.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
max_tool_calls | 3-5 times | Coking coal due diligence requires multiple rounds of pulling multi-source data; excessive iterations will increase overall time consumption |
data_fetch_interval | 600 seconds | The update cycle of coking coal spot data is moderate; this interval avoids invalid repeated requests |
context_split_length | 8000-12000 characters | Single coking coal due diligence report data documents are lengthy; splitting adapts to large language model context length limits |
param_validation_level | strict | Coking coal data has many fields and differing units; strict validation filters invalid data |
auto_field_mapping | Enabled | Different data sources have differing field names; automatic mapping reduces manual configuration workload |
hide_tool_output | Configured as needed | Some scenarios require retaining tool calling logs, while others require only displaying final results |
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 it is recommended to test on your own samples before finalizing.
Three common mistakes
- Phenomenon: Plugins are executed directly after extracting parameters via tool calling, with no user confirmation step. Cause: The
tool_call_confirm_before_execconfiguration item is not enabled; the manual confirmation process is disabled by default. - Phenomenon: Intermediate execution logs of tool calling cannot be hidden, and the final output includes redundant plugin calling details. Cause: The
hide_tool_outputparameter is not configured to enabled; the full tool calling process is displayed by default. - Phenomenon: Tool calling returns a
504 Gateway Timeouterror code, with excessively long single call duration. Cause: Themax_tool_callsanddata_fetch_intervalparameters are not adjusted according to the needs of coking coal multi-source data pulling, exceeding the system's single call time limit.
How to confirm configurations are set correctly
- Trigger a simulated call, check the tool calling logs to confirm that pull requests for each data source meet the configured interval and quantity requirements.
- Export the final output result, verify that the extracted coking coal data fields match the configured mapping rules, with no abnormal differences in names or units.
- Test enabling the
hide_tool_outputconfiguration, confirm that intermediate tool calling logs do not appear in the final user-visible output. - Simulate three consecutive calls, check the system returned status codes, confirm there are no abnormal situations such as timeouts or repeated requests.
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.