Tool Calling and Plugins for Thermal Coal Intelligent Due

What the Data for This Category Looks Like

Thermal coal intelligent due diligence report data primarily comes from publicly available statistics from the National Energy Administration, coastal port spot trading platforms, futures exchange delivery data, and monthly supply and demand analysis from industry associations. Data update schedules follow three cadences: real-time spot prices (updated daily), weekly port inventory and transportation indexes, and monthly production capacity and downstream demand ledgers. The document structure includes fields such as production area pithead prices, port free overside prices, railway transportation rates, key power plant inventory days, and policy regulation directions. Price units are yuan per ton, inventory units are ten thousand tons, and transportation rate units are yuan per ton·kilometer. Some real-time data is returned in JSON format via API interfaces. Monthly industry reports are mostly structured PDF tables.

What Constraints These Characteristics Impose on the Tool Calling and Plugins Workflow

Real-time updated spot prices require tool calling to support high-frequency interface pulls, to prevent data lag from expired caching. Weekly and monthly bulk data require pagination pulling plugins, to adapt to multi-interface polling logic. The multi-field, multi-unit structure requires plugins to have built-in unified unit conversion rules, to avoid unit conflicts across data sources. Unstructured text from policy updates requires plugins to integrate text classification tools, to extract core regulatory clauses. Interface authentication methods vary across data sources. Some port platforms require dedicated API keys, so plugins must support multiple authentication configuration items. Operational data from downstream key power plants is sensitive industry information, so plugins must include data desensitization rules, to prevent leakage of core enterprise operational details.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`tool_call_interval`	`10–30 seconds`	Thermal coal spot prices are updated daily. High-frequency calls do not need to be lower than 10 seconds, to avoid triggering interface rate limits
`max_tool_calls_per_round`	`8–12 times`	Due diligence reports need to pull four core data types: port inventory, production area prices, transportation costs, and downstream demand. A maximum of 2 retries per category keeps total calls under 12
`tool_response_visibility`	`Only visible in logs`	Due diligence reports need to output structured conclusions. Tool calling processes do not need to be shown to end users, to avoid redundant information
`plugin_auto_approve`	`Enabled`	Multi-data source plugin calls do not require manual approval, to ensure report generation efficiency
`tool_timeout`	`600 seconds`	PDF parsing and data extraction for monthly supply and demand reports require longer processing times, to avoid timeout interruptions
`enable_tool_stream`	`Disabled`	Tool calling results must be fully returned before being integrated into the due diligence report. Streamed output will cause chaotic content splicing

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 case-by-case analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Mistakes

Phenomenon: Tool calling run logs are directly displayed in the main body of the due diligence report without filtering. Cause: The tool_response_visibility configuration was not set to Only visible in logs, causing plugin execution records to be written to the final output.
Phenomenon: After multiple rounds of tool calls, the output of the subsequent variable includes the full result of the previous variable. Cause: No context filtering rules were set for context_window_for_tool, and the conversation context did not clear intermediate tool calling results, causing content overlap during variable splicing.
Phenomenon: When calling an MCP-type thermal coal data plugin, 401 Unauthorized or 504 Gateway Timeout errors occur. Cause: No dedicated API key was configured for port spot platform authentication, and tool_timeout was not adjusted to adapt to interface response times, causing connection establishment failures.

How to Confirm Proper Configuration

Initiate a simulated call, check the backend log panel, confirm that tool calling run records only appear in logs and not in the final generated due diligence report main body.
Call plugins from two different data sources, compare the variable content in the final output, confirm that the subsequent variable does not include the full result of the previous call.
Test the connection request for the MCP plugin, check the returned status code, confirm that there are no 401 Unauthorized or 504 Gateway Timeout errors.
After disabling the enable_tool_stream configuration, check whether the tool calling return result is complete structured data, with no fragmented segments from segmented output.

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.