diagram-indexer

To find which file contains a specific node in Mermaid diagrams, you can incrementally index your documentation to build a direct file-to-node mapping. This allows you to quickly query and locate the exact file where a given diagram node appears.

Yes, you can index Obsidian Canvas files without extra parsing libraries by using a zero-dependency parsing approach. The indexer processes Canvas files natively, while Mermaid blocks are extracted via simple parsing without requiring additional software packages.

You incrementally index diagram changes by running the indexer on a target directory, which only processes files that have changed. This updates the existing index efficiently without scanning the entire repository, saving time on large documentation sets.

The best way to locate diagram elements across large software engineering documentation is to use an incremental indexing tool that builds a node-level mapping. This targets extensive diagram workflows by tracking changes and enabling quick queries for specific elements.

Yes, this diagram indexing approach works with both Mermaid and Obsidian Canvas formats. It extracts Mermaid blocks using simple parsing and processes Canvas files with zero dependencies, building a unified file-to-node mapping for both.

You should use incremental indexing instead of a full scan because it only processes changed files, updating the index efficiently. This avoids the overhead of scanning the entire repository every time a diagram is modified, which is critical for large spec document sets.