What the data for this category looks like
Daily documents for this category include growth experiment plans, user segmentation tables, outreach copy, and retention analysis reports. Data sources are user behavior logs, push systems, experiment platforms, and CRM systems. Update frequency is daily or weekly. Document fields include user ID, outreach time, experiment group, retention rate, and others. Units include person-times, days, pieces, and more. Data formats vary across different sources. The data must be integrated for analysis and operations. The focus is mainly on operational actions within the platform’s user lifecycle.
How these characteristics create constraints for context and token handling
Multi-source data with inconsistent formats exists for this category. Context splicing requires integrating multiple types of data. This places requirements on parameter fault tolerance and escaping rules. Data updates occur daily or weekly. The context refresh cycle must match this rhythm. Otherwise, data lag will occur. Daily documents include analysis content integrated from multiple sources. The token usage of a single context is high. The total context length and token proportion of referenced segments must be controlled reasonably. This avoids exceeding model limits. Core links such as user segmentation and outreach rhythm design rely on precise context matching. The recall scope must focus on core dimensions. This prevents irrelevant data from occupying token resources.
How to set the configurations
The following configurations are formulated based on the logic of FastGPT v4.17.0.
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Daily documents for this category include multi-source integrated retention analysis reports and user segmentation tables. The integrated data volume for a single context is large |
quoteMaxToken | 3000–5000 token | The core information of outreach copy and experiment plans accounts for a limited proportion. The token usage of referenced segments must be controlled |
| Context refresh cycle | Updated daily | The data update frequency for this category is daily or weekly. Daily refresh matches the latest user behavior and experiment data |
| Number of recalled context entries | Top 3–5 entries | Core dimensions for user segmentation and outreach rhythm design are concentrated. Excessive recall will unnecessarily occupy token resources |
Three common mistakes
- Invalid JSON format error: The tool call node returns an error prompt related to Bad control character. The cause is failure to preprocess line breaks and special symbols in multi-source data. Splicing the context creates an invalid JSON structure.
- Context length exceeded error: The model returns a prompt that the context exceeds limits. The cause is failure to adjust the
maxContextparameter based on the category’s data characteristics. The default configuration cannot support multi-source integrated analysis documents. - Inconsistent workflow context: User segmentation data called in different links varies. The cause is failure to configure the context refresh according to the data update cycle. This leads to cached data not being synchronized with the latest information.
How to confirm the configuration is correct
- View the context splicing log. Confirm that special characters in multi-source data have been escaped. No invalid JSON fragments are present.
- Test calls related to retention analysis report context. Confirm that the model can load complete data normally. No context exceeded errors occur.
- Compare user segmentation data across different workflow links. Confirm that data consistency meets business expectations.
- Check the values of parameters such as
maxContextandquoteMaxToken. Confirm that they match the actual token usage of the category’s data.
The values provided are common starting points. They 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 2026-10-19.