What the Data for This Category Looks Like
Cosmetics research report data mainly comes from industry association public statistics, brand official quarterly financial reports, offline and online sampling data from third-party consumer research institutions, and sales monitoring data from e-commerce platforms. Update frequency varies by data source type: brand financial reports are updated quarterly, industry monitoring reports are released monthly, and e-commerce sales data can be synced daily. A single research report usually includes modules such as product ingredient details, sales share data across channels, consumer profile tags, and compliance test results. Fields include recommended retail price per unit (unit: yuan/item), monthly sales volume (unit: items), core ingredient content (unit: mg/g), consumer age distribution range, and number of qualified compliance test batches, among others.
Constraints Imposed by These Characteristics on Tool Calling and Plugins
The multi-source heterogeneous data feature of cosmetics research reports requires tool calling to support connection to multiple data source APIs, including industry association APIs, brand financial report APIs, and e-commerce monitoring APIs. Differences in update frequencies across data sources require tools to have configurable custom pull cycle parameters to adapt to quarterly, monthly, and daily synchronization needs. The multi-module structure and multi-unit fields of research reports require tool calling to support splitting and recalling by document modules, as well as configuring field mapping rules to unify units and field names across different data sources and avoid format conflicts during retrieval. The processing requirements for long-text research reports require tools to support adjusting the context recall length threshold to adapt to the large-capacity content of single research reports.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Adapts to the average length of a single cosmetics research report, prevents long text from being truncated |
recallTopK | Top 8–12 results | Cosmetics research reports have many detailed segmentation dimensions. A sufficient number of relevant fragments must be recalled to cover modules such as ingredients, sales, and compliance |
similarityThreshold | 0.72–0.85 | Balances relevance and recall coverage for research report content, avoids missing valid information in detailed modules |
fieldMappingConfig | Preset mapping rules per data source | Unifies field names and units across different report sources, for example, unifying "monthly sales volume" to a standardized field name |
syncSchedule | Configured per data source type | Configure 0 0 2 * * 1 for brand financial reports (quarterly), and 0 0 * * * for e-commerce monitoring data (daily) |
toolApiTimeout | 600 seconds | Adapts to the time consumption of multi-source data pulling, prevents single calls from timing out and interrupting |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: Calling the FastGPT application API returns results with no contextual relevance, only single isolated retrieval results. Cause: The
maxContextparameter is not configured, or its value is smaller than the average length of a single research report, causing the context window to fail to cover associated content. - Symptom: MCP tool calls return a
401 Unauthorizederror, or fail to read preset global token variables in the workflow. Cause: Global variable transfer permissions for the MCP tool are not enabled, and workflow global parameters are not bound in the tool configuration. - Symptom: Calling the associated knowledge base API returns "no relevant content", but corresponding cosmetics research reports exist in the knowledge base. Cause: Cross-team knowledge base access permissions are not configured, or the correct knowledge base ID is not specified during tool calling.
How to Verify Proper Configuration
- Initiate a test call, check if the returned results include multiple module contents of cosmetics research reports, and verify that contextual association works correctly.
- View tool call logs, confirm that the MCP tool successfully obtained global token variables from the workflow, with no permission errors.
- Check cross-team knowledge base access configurations, confirm that team permissions between the application and knowledge base have been enabled, allowing normal retrieval of corresponding content during calls.
- Verify that multi-source data pull tasks are executed according to the preset cycle, with no timeout or failure logs.
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.