What the data for this category looks like
This category serves data governance teams, security consultants, and legal compliance staff. Core data sources include data asset inventory results, database metadata, business system descriptions, and regulatory documents. Daily output documents include data catalogs, classification and grading rules, critical data identification tables, and review minutes. Update frequency is quarterly or whenever a system is changed. The data covers all business data assets except personal information. Core processing steps involve data asset sorting, sensitive field identification, and grading rule review. Errors may lead to critical data being overlooked, permission policy mistakes, or failed compliance rectification.
What constraints these characteristics impose on the "tool calling and plugins" workflow
The diversity of data sources requires tool calling to adapt to multiple formats such as structured metadata and document-style rules. Plugins must support pulling and parsing from multiple data sources. The non-real-time update frequency and change-triggered nature require tool calling to support configurable scheduled synchronization or manual trigger modes, to avoid unnecessary calls. The complexity of document structures means tools must have the ability to parse classification and grading rules and match sensitive fields. The functionCall parameter must be validated strictly against document formats. The specific coverage scope requires tool calling to only target non-personal information data assets. Filter rules must be clearly defined in configuration to avoid confusion across categories.
How to Configure
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Meets automatic matching requirements for multiple data sources such as data catalogs and database metadata |
functionCall | Enabled | Meets structured parameter validation requirements for classification and grading rules |
| Tool call timeout threshold | 600 seconds | Handles large-volume data pulls from data asset inventories, to avoid mid-process interruptions |
| Tool call frequency limit | 1 time per 10 minutes | Matches synchronization rhythm for quarterly updates or system changes, to reduce unnecessary requests |
| Number of results returned | Top 3 | Focuses on core critical data identification tables and grading rule content, to avoid information overload |
| Single data pull limit | 1000 MB | Adapts to typical document sizes for business system descriptions and data catalogs |
| MCP service configuration | Fill in the actual deployed MCP service address and port | Supports custom code and database tool call links |
Three Common Configuration Mistakes
- Symptom: Returns a 400 status code with no response body when calling the MySQL database tool. Cause: Data source connection parameters for tool calling are not configured correctly, causing metadata pull requests to not comply with data catalog validation rules.
- Symptom: Returns AggregateError Code: ETIMEDOUT when calling a custom code tool. Cause: The tool call timeout threshold is set too short, failing to complete full data pulls for data asset inventories.
- Symptom: Cannot trigger tool calling when using the QwQ-32B model. Cause: This model does not adapt to the standard format of the
functionCallparameter. Switch to a model configuration that supports function calling.
How to Verify Successful Configuration
- Run a tool calling test to confirm that target data sources such as database metadata and classification and grading rules can be pulled successfully.
- Submit a simulated code change review request to verify that the tool can output corresponding data security classification and grading verification results.
- Check the FastGPT v4.17.0 system logs to confirm that preset error types such as 400 status code with no response body and ETIMEDOUT are not present.
- Trigger a post-change synchronization task to verify that the tool can update data asset information according to the configured frequency.
The values provided are common starting points and should be measured 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 2026-10-19.