What the Data for This Category Looks Like
Consumer electronics financial report data primarily comes from publicly disclosed documents of domestic and overseas stock exchanges, and official investor relations pages of listed companies. Quarterly reports are updated within 30 days after the end of each quarter. Annual reports are updated by April 30 of the following year. Document structure includes modules such as consolidated financial statements, segment-wise operating data, and R&D expenditure details. Fields cover revenue, shipment volume, gross margin, R&D expense ratio, and more. Common units are RMB 100 million, 10,000 units, and percentage.
Constraints Imposed on Tool Calling and Plugins
Consumer electronics financial reports have multi-source and structured differences. Tool calling plugins must support parsing publicly disclosed documents in PDF and HTML formats, while adapting to both Chinese and English document structures. Financial reports are updated frequently. Plugin configuration uses a scheduled pull task cycle that matches the disclosure rhythm. This avoids pulling outdated, unupdated data. Some reports include segment-wise operating data fields. Tool calling parameters support filtering by specific categories such as smartphones, laptops, and others. This prevents returning full-category aggregated data. Individual financial report documents can be lengthy. Plugins adapt to large-text segment parsing. This avoids call timeouts caused by excessive content.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
mcp_tool_timeout | 120 seconds | The structured parsing and data pulling process for individual consumer electronics financial report documents takes a long time. 120 seconds covers execution requirements for most conventional scenarios |
parse_file_max_length | 8000–12000 characters | The single-segment text length of segment-wise operating data in consumer electronics financial reports falls within this range. Segment parsing prevents core content from being truncated |
mcp_filter_fields | ["revenue", "shipment_volume", "gross_margin", "R&D_expense_ratio"] | Covers core requirements for consumer electronics financial report analysis. Filtering non-essential fields reduces call data volume and processing pressure |
rag_recall_top_k | Top 3 entries | Structured data in consumer electronics financial reports has strong relevance. A small number of highly relevant recalls can support accurate analysis, avoiding interference from redundant information |
plugin_call_retry_times | 2 times | Consumer electronics financial report data pulling may fail due to exchange server fluctuations. Retries can improve call success rates |
model_context_window | 32768 tokens | The total text length of consumer electronics annual financial reports is large. A 32768-token window can fully carry parsed structured data and prompt words |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Mistakes
- Symptom: The MCP tool node returns empty values or unresponsive fields after the workflow runs. Cause: The
mcp_tool_timeoutparameter is not configured, or the value is set too short, causing the call to terminate before consumer electronics financial report parsing is complete. - Symptom: Content returned after a knowledge base call does not match consumer electronics financial report analysis questions. For example, smartphone shipment data is mistakenly replaced with revenue from other categories. Cause: The
rag_recall_top_kvalue is too large, recalling financial report data from non-target categories, or themcp_filter_fieldsparameter is not configured to filter non-target fields. - Symptom: A locally deployed model returns a 400 Bad Request error code when calling the MCP tool. Cause: The tool call request format is not configured according to model requirements, or the locally deployed model version does not adapt to the tool call protocol.
How to Confirm Proper Configuration
- Run a test workflow to trigger an MCP tool call, and check if the returned JSON structure includes preset fields such as revenue and shipment volume to confirm that the field filtering configuration is effective.
- Manually adjust the
mcp_tool_timeoutparameter, compare tool call results under different values, and confirm that the timeout setting matches the financial report parsing time for the current scenario. - Input a financial report analysis question for a specific category into the knowledge base, verify that the returned content only includes operating data for that category, and confirm that the recall and filtering configurations are effective.
- Check the workflow logs to confirm that the MCP tool call returns a status code of 200, with no
ETIMEDOUTor parameter verification failure prompts.
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.