centrality

Score code symbols and files using centrality measures on call and file graphs.

1|Updated May 29, 2026
One-click install
npx skills add https://github.com/aimasteracc/mycelium --skill centrality
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: centrality
Source: https://github.com/aimasteracc/mycelium/tree/main/skills/centrality
Command: npx skills add https://github.com/aimasteracc/mycelium --skill centrality

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Centrality tools identify which code symbols and files matter most, enabling faster onboarding, maintenance, and risk assessment by surfacing key components.

Core Features & Use Cases

  • 14 ranking and scoring tools (rank_symbols, get_top_files, page_rank, betweenness_centrality, closeness_centrality, degree_centrality, neighbor_similarity, and more) to quantify importance at symbol and file levels.
  • Onboarding into unfamiliar codebases by surfacing top files and symbols to focus exploration and learning.
  • Bottleneck and hub detection to identify high-impact areas, guiding refactors and architectural decisions.

Quick Start

Rank the top files and symbols in this codebase to surface hotspots.

Frequently Asked Questions about centrality

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

FAQPage Schema
How do I identify the most important files and symbols in a codebase for onboarding?

Code centrality analysis detects high-impact areas and bottlenecks by scoring symbol importance across call graphs. It highlights architectural hubs and components with high traffic, guiding refactoring decisions and risk assessment.

What's the best way to rank code symbols by importance using a call graph?

You can quantify code importance using page rank, betweenness centrality, closeness centrality, degree centrality, and neighbor similarity. These 14 ranking tools compute and expose symbol and file level importance scores.

Do I need a graph representation to analyze code centrality and detect refactor hotspots?

Graph representation is a required prerequisite for centrality analysis. You must build a call graph or file graph of the codebase before applying ranking and scoring tools to surface hotspots and onboarding points.

Does code centrality analysis work for finding bottlenecks in large file graphs?

For large file graphs, centrality analysis exposes rankings with limit options to constrain output scope. This allows targeted bottleneck detection and hotspot surfacing without overwhelming results.

Why use centrality measures instead of manual code review for maintenance prioritization?

Centrality measures offer systematic bottleneck and hub detection across entire codebases. They identify high-impact areas for refactors and architectural decisions, replacing subjective manual review with data-driven rankings.