What the data for this category looks like
Core data for this category is generated around employee security training and phishing drills. Daily documents include training slides, drill plans, phishing email templates, and drill result reports. Data sources are primarily employee contact lists, email gateways, internal training platforms, and user click statistics. Update frequency is usually quarterly or annually. Core document fields include drill audience scope, email delivery records, quiz data, rectification feedback, and more. Common units are number of people, number of sends, and statistical cycles. The most time-consuming operational steps focus on audience filtering, template design, and result review. Data changes must align with the overall training cycle rhythm. This page is written based on FastGPT v4.17.0.
What constraints these characteristics impose on the tool calling and plugins workflow
The data traits of this category create multiple constraints for the tool calling and plugins workflow. Data sources are scattered and update cycles are long. Tools must support connecting to multiple data sources including employee contact lists, email gateways, and training platforms, and adapt to non-real-time batch pull logic. Daily document formats vary. Plugins must support parsing unstructured content such as training slides, phishing email templates, and drill reports, and cannot rely on fixed structured data formats. The drill audience filtering and result review steps are time-consuming. Tools must pre-set grouping rules and automatically generate review assistance content to reduce manual operations. Data involves employee security behavior. Tool calling must strictly limit permission scope to avoid sensitive data leaks.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapts to automatic tool triggering in batch drill scenarios to reduce manual operation costs |
functionCall | Calibrated based on actual testing | For phishing email template generation and drill report generation scenarios, force enable function calling to ensure format compliance |
| Tool call timeout threshold | 600 seconds | Matches the quarterly data update rhythm of this category to avoid task interruption caused by multi-source data pull delays |
| Data source binding scope | Employee contact lists, email gateways, training platforms | Matches the core data sources of this category to ensure tools can obtain accurate audience and delivery data |
| Result output format | Markdown structured document | Adapts to the drill result report standards of this category for subsequent review and audit use |
Three common mistakes
- Chart tool outputs empty after being called. Cause: Core data sources of this category are not bound (such as click statistics data from the training platform), so the tool cannot obtain valid drawing data.
- Tool call returns a 400 error. Cause: Parameters are not passed in accordance with the document format requirements of this category, for example, fields of phishing email templates are missing or the format does not meet preset rules.
- Only some large models support tool calling. Cause:
functionCallforced mode is not configured, and some models cannot recognize non-standard tool calling formats, resulting in call failure.
How to confirm the configuration is correct
- Trigger a test drill for a small audience, check whether the tool automatically pulls the preset data sources and generates corresponding content.
- View the tool call log to confirm that parameters are passed in accordance with the document format requirements of this category, with no missing fields.
- Verify that the result output matches the drill report standards of this category, with format and fields meeting preset rules.
- Check the permission configuration to ensure that the tool can only access data sources allowed by this category, with no unauthorized calls.
The values given 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.