spurpower-spur-analyst

You can analyze code dependencies using SQL by querying a DuckDB instance that represents your repository as a property graph. This allows you to execute multi-table JOINs and graph path traversals to map call chains and dependency impacts.

The best way to detect architectural hotspots is by querying blast radius and churn metrics in a graph database. This approach identifies high-risk code areas by analyzing commit history and temporal edges through SQL path queries.

You track file evolution and co-change history by performing temporal analysis on commit data within a DuckDB instance. This exposes temporal edges and commit history as SQL tables, allowing time-series churn queries across symbols.

Yes, you need a pre-built graph artifact to run graph path traversal queries. The analysis requires this artifact to expose symbol nodes, temporal edges, and commit history as a DuckDB instance for SQL querying.

Yes, you can use DuckDB with DuckPGU and Onager extensions for code exploration. These extensions enable multi-table JOINs and graph path traversal directly against the repository's property graph artifact.

You use a property graph for code impact analysis because it overcomes the limitations of single-symbol exploration. It provides a SQL interface to query the entire codebase, enabling complex dependency chain mapping and blast radius calculation.