Memory Keeper

About

Replaces passive context staleness warnings with an active maintenance system that detects when synchronization is necessary to keep development context fresh. By continuously monitoring Git history, task completion status in planning files, and test execution events, it automatically diagnoses what has changed and suggests updates to critical memory files like active_context.md. This skill includes advanced logic for detecting constitutional violations, quality gate failures, and cross-project drift, ensuring that the AI's understanding of the project state never diverges from the actual codebase or project requirements.

Key Features

• Automated execution of memory sync operations including progress tracking and lessons-learned capture.
• Detection and documentation of constitutional violations and quality gate failures.
• Proactive detection of task completions, phase transitions, and significant code changes.
• Automated staleness monitoring with tiered urgency levels based on context age.
• 1 GitHub stars
• Cross-project drift monitoring to maintain consistency when switching between repositories.

Use Cases

• Synchronizing project progress and implementation patterns after completing major development milestones.
• Automatically documenting remediation steps and blockers when security or quality standards are violated.
• Ensuring project state is fully captured and updated when transitioning between different work directories.