What the Data for This Category Looks Like
Data comes from public pharmaceutical and biotechnology sector market interfaces and industry monitoring databases provided by stock exchanges. Data is updated per trading day, with a full daily dataset generated after market close each trading day. Standard documents are categorized by entity, and include fields such as report date, entity code, entity name, previous day’s benchmark price, same-day closing price, same-day trading volume, turnover rate, API segment change range, chemical formulation segment change range, and more. Price-related fields use yuan as the unit. Trading volume uses shares as the unit. All change range fields are dimensionless values without percentage annotations.
Constraints Imposed by These Characteristics on Conversation Logging and Auditing
Daily fixed-timing updated datasets include multi-dimensional segmented fields. Conversation logs must fully record the scope of called entities, time intervals, and selected segmented tracks to ensure complete calling context can be traced during audits. Since data is only generated on trading days, audit processes must verify that the date of calling requests falls within valid trading days to avoid returning unexpected empty datasets. There are a large number of chemical pharmaceutical-related entities. Logs for batch calls must independently mark the context identifier of each call to prevent log confusion in concurrent scenarios. At the same time, the units of various price and trading volume fields are fixed. Audits must verify that the units of returned fields match preset rules to avoid numerical calculation deviations.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
log_context_max_size | 2000–3000 characters | Chemical pharmaceutical datasets include multiple segmented fields. Full logs must accommodate calling parameters and returned results to avoid truncating key information required for audits |
audit_trigger_interval | 60 seconds | Daily market data is updated within one hour after market close. Verifying call times in logs every 60 seconds allows timely identification of abnormal requests on non-trading days |
mcp_concurrent_limit | 5 requests/second | Community feedback shows that concurrent calls at 2-3 requests per second easily lead to empty returns. Setting 5 requests/second balances call efficiency and stability |
hook_timeout | 30 seconds | Feishu Webhook message pushes require sufficient response time to avoid missing log records due to timeouts |
tool_call_log_visibility | full | Audits require complete retention of tool call request parameters and returned results. Full mode covers all content required for audits |
workflow_loop_max_count | 100 | Covers batch processing needs for most chemical pharmaceutical listed companies, avoiding log abnormalities caused by overload of loop nodes |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Symptom: When concurrent call volume exceeds the threshold, the MCP tool returns
none, and no corresponding call record appears in the logs. Cause: No reasonablemcp_concurrent_limitparameter is set. Concurrent requests exceed the system processing threshold, causing some calls to be discarded. - Symptom: After the loop node splices text, the tool call module continuously outputs redundant running records, occupying log storage space. Cause:
tool_call_log_visibilityis not configured to a mode adapted to audit requirements. The default setting retains overly detailed running logs. - Symptom: After calling the MCP tool, the call termination node cannot be triggered. The log shows a
connection_timeoutstatus code. Cause: No reasonablehook_timeoutparameter is set. The Feishu Webhook response time exceeds the preset threshold, causing the node to fail to establish a normal connection.
How to Confirm the Configuration Is Complete
- Initiate calls that match the expected business concurrency volume. Check whether logs fully record the entity, time, and returned results of each call. Confirm that the
log_context_max_sizevalue can accommodate complete log content. - Initiate a call on a non-trading day. Check whether the audit system marks the request as invalid. Confirm that the
audit_trigger_intervalconfiguration can verify the trading day range. - Trigger a workflow that includes loop nodes and text splicing. Check whether the tool call module only retains necessary running records. Confirm that the
tool_call_log_visibilityconfiguration meets audit requirements. - Call the MCP tool and wait for a response time adapted to the business. Check whether the call termination node can be triggered normally. Confirm that the
hook_timeoutvalue matches the actual response scenario.
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.