spur-analyst

Analyze codebase metadata as a property graph using DuckDB and DuckPGQ.

2|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/getspur/spur --skill spur-analyst
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: spur-analyst
Source: https://github.com/getspur/spur/tree/main/.spur/skills/spur-analyst
Command: npx skills add https://github.com/getspur/spur --skill spur-analyst

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the limitation of single-symbol code exploration by providing a powerful SQL-based interface to query the entire codebase as a property graph, enabling complex analysis that standard tools cannot perform.

Core Features & Use Cases

  • Hotspot Detection: Identify high-risk code areas using blast radius and churn metrics.
  • Graph Algorithms: Execute path traversal, reachability analysis, and centrality metrics using DuckPGQ and Onager extensions.
  • Co-change Analysis: Discover implicit coupling between files by analyzing historical commit patterns.

Quick Start

Use the spur-analyst skill to identify the top 20 risk hotspots in the current repository by querying the blast radius view.

Frequently Asked Questions about spur-analyst

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify architectural hotspots and structural dependencies in a large codebase?

Architectural hotspot detection is performed by applying churn-weighted impact analysis and blast radius metrics to codebase metadata. This identifies high-risk code areas by evaluating structural dependencies and historical commit patterns across large-scale repositories.

Can I use SQL to query code relationships and perform graph analysis on my repository?

SQL-based graph analysis is supported using DuckDB with the DuckPGQ and Onager extensions. This provides a SQL interface to query the entire codebase as a property graph, enabling path traversal, reachability analysis, and centrality metrics.

What is the best way to discover implicit coupling between files during refactoring planning?

Implicit coupling discovery is achieved through co-change analysis. By analyzing historical commit patterns, you can find files that frequently change together, revealing hidden structural dependencies to guide your refactoring planning.

Does DuckDB support multi-hop call path discovery across large-scale repositories?

DuckDB supports multi-hop call path discovery through the DuckPGQ extension. It enables complex relational and graph-based analysis, allowing you to execute property graph traversals to map structural dependencies across large-scale repositories.

How do I calculate blast radius and churn metrics to find high-risk code areas?

Blast radius and churn metrics are calculated by performing complex relational analysis on codebase metadata. This graph-based approach identifies high-risk code areas by measuring the structural impact and historical change frequency of specific components.