What data for this category looks like
Data for this category comes from product digital models and GD&T. It also draws from process routes, coordinate measuring machine data, on-site trial feedback, and metrology systems. Daily documents include fixture requirement documents, positioning benchmark plans, fixture drawings, gauge operation manuals, acceptance reports, calibration records, and change histories. Data updates run on a schedule tied to project progress, product changes, or periodic calibrations. Available fields include GD&T tolerance values, coordinate measuring machine measurement results, calibration cycles, and other relevant metrics. Supported units include millimeters, micrometers, days, and more.
What constraints these characteristics impose for tool calling and plugin use
Data for this category is mostly tied to project-level precision documents and measurement results. Tool calling must bind to project context to avoid mixing data across projects. Documents include CAD drawings and numeric content. Tools must support parsing multiple data formats. Update triggers tie to project progress and changes. Tools must support dynamic loading of the latest calibration records and change histories. Fields include high-precision tolerance values. Tool return results must strictly match required units and precision standards. This prevents deviations that disrupt equipment inspection and maintenance judgments.
How to set configurations
| Configuration Item | Recommended Setup | Rationale |
|---|---|---|
| Workflow/API tool selection | Set to auto, with trigger thresholds tied to equipment inspection and fixture calibration keywords | Accurately matches the business scenarios of this category's equipment inspection and maintenance, reduces invalid tool calls, and aligns with FastGPT v4.17.0 version rules |
| Workflow/API function-call configuration | Enable and limit calls to equipment data query and calibration record retrieval tools | Focuses on core business tools for this category, avoids unnecessary plugins consuming context resources |
| Conversation result filtering rules | Hide tool call process content, only retain final Q&A results | Aligns with user requirements for only displaying AI conversation output |
| File upload limits | Single upload no larger than 200 MB, supports CAD drawings and CSV format data | Matches the size and format characteristics of this category's daily fixture documents |
| MCP display configuration | Render parameters based on actual measurement calibration, bind HTML content display thresholds | Adapts to the display requirements for HTML charts generated by pyecharts returned by tools |
Three common configuration mistakes
- Scenario: Tool call logs and parameters are fully output, and the configuration to retain only final Q&A results does not take effect. Cause: Conversation result filtering rules are not correctly configured, or the filtering rules are not bound to this category's equipment inspection scenario keywords.
- Scenario: Format errors trigger when uploading fixture drawings or coordinate measuring machine data. Cause: File upload limits are not configured to support CAD drawings and CSV formats, or single upload size exceeds the set threshold.
- Scenario: MCP host cannot display line chart HTML content returned by tools. Cause: MCP display HTML rendering thresholds are not configured based on category document characteristics, or the content format generated by pyecharts is not correctly bound.
How to confirm correct configuration
- Initiate a question related to equipment maintenance that includes "fixture inspection" or "calibration records", confirm only Q&A results are output, with no tool call process logs.
- Upload CAD format fixture drawings and coordinate measuring machine data CSV files, confirm successful upload with no format errors.
- Trigger tool calls to generate a line chart, confirm the MCP host can normally display the returned HTML content.
- When calling a specified API interface, confirm the parameters bound to the configuration items align with platform requirements.
The values given are common starting points, and should be measured against the reader's own samples.