Knowledge Base Indexer
Rebuilds and maintains the knowledge base shelf-index using incremental hash-based change detection.
The Knowledge Base Indexer skill automates the maintenance of your project's internal knowledge base by refreshing the shelf-index. It employs an efficient SHA-256 hash-based detection system to perform incremental updates, only re-processing files that have changed since the last index run. This tool is essential for ensuring that your AI assistant has an accurate and up-to-date map of your documentation, library files, and domain-specific guidance after making edits or adding new sources, all without loading unnecessary content into the session context.
Key Features
0139 GitHub stars
02Script-based execution to minimize session context usage
03Incremental hash-based indexing for rapid updates
04SHA-256 change detection to ensure data integrity
05Automatic configuration discovery via CLAUDE.md
06Force rebuild support using the --full argument
Use Cases
01Refreshing the knowledge base map after manual edits to library files
02Updating the index after ingesting new documentation or source files
03Resolving stale index errors reported by AI librarian agents