What Data for This Category Looks Like
Data for this category typically originates from Figma or Axure files, internal team design systems, user feedback, and usability test records. Daily deliverables include interactive prototypes, page flowcharts, component descriptions, and review records. Updates follow a weekly or per-version release cadence. Common data fields include prototype version numbers, page operation paths, interactive node rules, and review modification suggestions. No unified mandatory format exists, and fields adjust based on each team’s design specifications.
Constraints Imposed by These Characteristics on Scheduled Tasks and Automation
The update cadence for this category’s data follows weekly or per-version releases. Scheduled tasks must align with this cadence to avoid frequent triggers that consume the design team’s daily work resources. Design files from different sources have significant format differences. Automated workflows must adapt to parsing rules for multiple tools including Figma and Axure, to ensure files produced by different tools can be processed normally. No unified format exists for data fields, so flexible field mapping rules must be configured within tasks to adapt to each team’s design specifications. Exception remediation and review modification stages take considerable time. Automation must reserve retry capacity to avoid interrupting the overall release notes and operations report summary process due to a single failed task.
Configuration Guidelines
This configuration guide applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Task trigger timing | Every Friday at 18:00 | Aligns with the weekly or per-version update cadence of this category, and avoids interfering with daily design work |
| File parsing scope | Only sync Figma/Axure files updated in the last 7 days | Reduces unnecessary parsing volume, and adapts to the weekly update frequency |
| Failure retry count | 3 times | Covers temporary network fluctuations or file parsing exceptions, and avoids terminating the task directly after a single failure |
| Task timeout threshold | 3600 seconds | Adapts to the time required for batch parsing of multiple files, and avoids forced termination of long-running tasks |
| Exception notification trigger condition | Task failure or failure of any single file parsing | Notifies the design team promptly of exception scenarios, and avoids impacting subsequent research and development alignment |
| Log retention period | 30 days | Matches the archive cadence of review records, and facilitates subsequent issue troubleshooting |
Three Common Misconfigurations
- Symptom: Prototype files parsed after scheduled task execution are missing. Cause: The correct team shared design file path was not configured, and only files from the local temporary directory were synced, failing to cover all design resources.
- Symptom: Custom text understanding models cannot be added to the search library. Cause: Global model environment variable configuration was not completed, preventing the task stage from calling non-default model services.
- Symptom: Summary reports generated after task execution are automatically cleaned up early. Cause: The log retention period configuration was not adjusted, and the default retention duration is too short, resulting in expected logs being deleted.
How to Confirm Proper Configuration
- Manually trigger a scheduled task, check the task management page for a successful execution record, and confirm that the number of parsed files matches the current number of design resources owned by the team.
- Simulate a single file parsing exception, check whether the corresponding exception notification is received, and confirm that the notification channel configuration is active.
- View the global model configuration page, confirm that the added custom model is visible in the model selection list of the search library.
- Check the task log storage directory, confirm that task logs from the last 30 days are retained normally and have not been cleaned up early.
The values provided are common starting points and should be validated against samples from the actual deployment.
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.