Knowledge Base Maintenance
Audits and maintains the health of your personal AI knowledge base by identifying stale, unreferenced, or oversized artifacts.
The Knowledge Base Maintenance skill provides a robust health-check utility for the claude-code-hermit environment, ensuring that your AI assistant's data remains optimized and relevant. By scanning both raw and compiled directories, the skill identifies stale files, missing metadata, and artifacts that exceed size limits, providing a comprehensive read-only report with actionable advice. This tool is essential for users who want to prevent context bloat and ensure their personal AI has access to clean, well-structured information without the risk of accidental data modification.
Key Features
01Automated linting of raw and compiled knowledge artifacts
02Validation of file types and schema compliance
03Identification of oversized artifacts to prevent context bloat
0461 GitHub stars
05Detection of stale or unreferenced knowledge files
06Read-only reporting with specific, actionable improvement advice
Use Cases
01Auditing the health of a growing personal knowledge repository
02Troubleshooting broken references or missing types in documentation
03Optimizing AI assistant performance by identifying redundant or bloated data