Sypha AI Docs
Advanced Usage

Autonomous Data Maintenance

Manage your task history and optimize disk utilization through automated maintenance logic.

Autonomous Data Maintenance

Sypha features an Auto-Cleanup engine designed to manage your historical task data automatically. This background maintenance logic optimizes disk space and ensures peak IDE performance by intelligently categorizing and purging obsolete task records based on age and importance.

[!WARNING] Permanence Alert: Task record pruning is a final operation; purged data cannot be restored.

System Overview

As you integrate Sypha into your daily workflow, the accumulated task data can impact system resources. Auto-Cleanup mitigates this by:

  • Executing automated pruning based on predefined retention windows.
  • Preserving critical records (such as favorited or starred tasks).
  • Orchestrating disk optimization without requiring manual developer intervention.

Data Retention Taxonomy

Task ClassificationStrategic CategoryPurge Protocol
FavoritedMissions marked for long-term retentionExempt from automated purging
CompletedFullfilled tasks (attempt_completion)30-day retention window
IncompleteAbandoned objectives or failed iterations7-day retention window
StandardGeneral interaction history30-day retention window

Management Controls

Configure your maintenance preferences via the Settings (Gear Icon) -> Auto-Cleanup dashboard.

  • Enable Maintenance: Toggle to activate the automated background cleanup engine.
  • Retention Strategy: Adjust the baseline windows for specific task categories to match your needs.
  • Manual Execution: Trigger an immediate cleanup cycle to reclaim disk space instantly.

Local Governance & Privacy

All maintenance operations are performed locally on your physical machine. Purged task data is not mirrored to any cloud infrastructure, ensuring your historical data remains within your private environment until it is deleted.

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