Tool Calling and Plugins for Coal Chemical Marketing Content

What data for this category looks like

Data related to coal chemical marketing for the financial industry comes primarily from four sources: internal enterprise marketing material libraries, industry supply and demand reports released by the China Coal Industry Association, official price disclosure platforms of upstream coal producing areas, and coal chemical customer profile data from financial institutions.

Data update rhythms fall into three categories:

Product specification parameter data is updated monthly
Industry analysis report data is updated quarterly
Marketing materials are updated anytime to align with activity adjustments

Document structures include product specification tables, marketing script packages, and delivery effect ledgers. Most fields include calorific value (unit MJ/kg), ash content (percentage), and product price (unit yuan/ton). Some documents contain long text of thousands of words covering industry trend analysis.

What constraints these characteristics impose on tool calling and plugins

Differences in update rhythms across multiple data sources require tool calling to differentiate between scheduled pull and real-time call trigger logic. This avoids repeated pulling of outdated data, and ensures compliance with financial industry data regulatory requirements.

Diverse field units require automatic unit alignment during tool calling. Without this alignment, product parameters in marketing content will be confused, undermining the professionalism of financial marketing.

Long text industry analysis documents consume large model context windows. Segment processing must be completed before tool calling to avoid exceeding model limits.

Coal chemical product parameters are the core basis for financial marketing content. Tool calling must accurately match product fields. Incorrect matching will cause marketing scripts to not align with actual product parameters, harming customer trust.

How to set configurations

Configuration Item	Recommended Value	Rationale
`tool_call_timeout`	`120 seconds`	Coal chemical industry report documents are typically long. A standard 60-second timeout is insufficient to complete data pulling and parsing
`field_mapping_rule`	`Map product fields: calorific value → MJ/kg, price → yuan/ton`	Coal chemical marketing content requires unified units to avoid conflicts across data sources, and meet the professionalism requirements of financial marketing
`data_source_refresh_interval`	`Monthly (product parameters), real-time (marketing materials)`	Product parameters are updated monthly, and marketing materials need to take effect immediately when adjusted for activities. This aligns with compliance requirements for financial industry data updates
`image_url_display_trigger`	`Trigger display only when the URL returns a 200 status code`	Resolves community-reported issues with images not displaying. Validate URL validity before calling for display, to comply with compliance requirements for financial marketing content display
`mcp_service_address`	`Compliant MCP service address deployed within the enterprise`	Local MCP services require correct access paths to avoid cross-domain or permission issues, and adapt to internal network security rules of financial institutions
`max_context_tokens`	`8000–12000`	Coal chemical industry analysis documents typically contain long text. This range adapts to large model context windows, and meets long text processing requirements for financial marketing content

The parameter values provided on this page are all common recommendations, used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing values.

Three common configuration errors

A 403 Forbidden error is returned when calling a local MCP service. The cause is that the access domain name of the MCP service was not added to FastGPT's allowed_cors_domains configuration. This causes cross-domain requests to be blocked, which does not meet the network security requirements of financial institutions.
The image address field in marketing materials returned by tool calling is empty. The cause is that URL validity verification for image_url_display_trigger was not configured. Invalid URLs are filtered out, and the field is not populated correctly. This corresponds to the community-reported issue of images not displaying.
A context window exceeded error occurs during tool calling. The cause is that the segment length of long text documents was not limited. Directly passing a complete industry report exceeds the large model context window, which affects the generation efficiency of financial marketing content.

How to confirm configurations are properly set

Initiate a tool calling test, check whether the returned results contain correct coal chemical product parameters and units, and verify that field mapping takes effect.
Pass a test image URL, check whether the image displays normally, and verify that the image_url_display_trigger configuration takes effect.
Call a locally deployed MCP service, check whether data can be pulled normally, and confirm that the mcp_service_address configuration is correct.
Pass a long text industry analysis document, check whether tool calling completes normally without context overflow errors.

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.