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.