Document and Material Drafting for Administrative Penalty Case Handling: Tool Calling and Plugins

Document and Material Drafting for Administrative Penalty Case Handling: Tool Calling and Plugins

Reference only; verify against the target FastGPT release and deployment documentation.

What data for this category looks like

Law enforcement agencies’ daily documents for administrative penalty case handling include on-site inspection records, inquiry records, evidence lists, prior administrative penalty notification letters, hearing notification letters, penalty decisions, and service receipts. Data sources are administrative law enforcement case handling systems, law enforcement recorder footage, the National Enterprise Credit Information Publicity System, and departmental supervision databases. Update frequency is daily. Document structures correspond to different stages of the case handling process. Each document includes fixed fields such as law enforcement subject number, description of illegal facts, legal provision entries, and service address. Documents are archived in case handling order.

What constraints these characteristics impose on the "tool calling and plugins" workflow

Multi-source data updated daily requires tool calling to support parallel pulling of law enforcement data from different systems. It also requires checking data timeliness to avoid using expired information. Multiple law enforcement documents with fixed structures require tool calling to adapt to required fields for different documents. This prevents generating content that does not match case file formats. Errors in law enforcement case files can lead to penalty revocation, loss in administrative reconsideration proceedings, or failure in case file review. Therefore, tool calling must include built-in parameter verification, failure retry, and detailed log retention mechanisms. This ensures compliance and traceability of generated content.

How to set configurations

Configuration ItemRecommended SettingRationale
toolChoiceSpecify a fixed function listAdapt to the fixed generation logic of different law enforcement documents, reduce invalid model thinking
functionCallEnable required field verificationEnsure generated documents include all required fields specified for law enforcement case files
Maximum context length8000–12000 tokenCalibrated based on actual testing, adapts to loading requirements for multi-source law enforcement data
Retry count2–3 timesAddress temporary interface fluctuations, ensure call success rate
Log output levelFull detailed logsMeet traceability review requirements for law enforcement case files
Timeout duration600 secondsAdapts to time limits for pulling data from multiple sources
Single data pull limitTop 10 entriesAdapts to single loading scale for law enforcement data

Three common mistakes

  • Symptom: Tool calling nodes in the workflow cannot have connection lines added, and no connection circles appear in the interface. Cause: functionCall mode is not enabled, or the node is not bound to a valid MCP service.
  • Symptom: MCP auxiliary model generation tasks take too long. Cause: The range of selectable functions is not restricted via toolChoice, causing the model to iterate through too many candidate tools.
  • Symptom: HTTP tool calls cannot receive file input parameters. Cause: File upload support is not enabled in the tool configuration, and the correct file parameter type is not specified.

How to confirm correct configuration

  • Open the configuration interface of the tool calling node, confirm that toolChoice is bound to the generation function for the corresponding law enforcement document.
  • Run a test workflow, view the detailed logs of the MCP service, confirm that the call process is fully recorded.
  • Drag and drop node connection lines, confirm that connection points can be added normally in the interface.
  • Submit simulated law enforcement data as input parameters, check that the generated document includes all required fields.

The values provided here are common starting points, and should be evaluated against the reader’s own samples.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.