obsidian-graph-auditor

name	obsidian-graph-auditor
description	Audit Obsidian vault, score second brain, and grade PKM graph health on an 8-dimension Grade-A rubric. Pure Python CLI, read-only, no GPT or API keys. Measures link density, orphan rate, near-orphan rate, connected-2plus share, top-hub edge-share, top-hub:next ratio, Louvain modularity, and frontmatter-wikilink adoption against expert-cited thresholds (kepano, Matuschak, Ahrens, Konik, Paranyushkin, Milo). Use when the user asks any of: audit my obsidian vault, score my obsidian, is my obsidian healthy, is my second brain healthy, score my pkm graph, obsidian vault review, obsidian graph analysis, measure my obsidian, find orphans in my obsidian vault, obsidian orphans, cross-linking review, obsidian graph health check, grade my pkm, obsidian vault quality, obsidian scorecard, zettelkasten audit, second brain audit, why is my vault rotting, pkm metrics, atomic notes review. Works on any markdown vault using wikilinks (Obsidian, Logseq, Foam, Quartz).
license	MIT
author	Dhiraj Singh Pawar (build-with-dhiraj)
homepage	https://github.com/build-with-dhiraj/obsidian-graph-auditor
version	0.1.0

Obsidian Graph Auditor

Score an Obsidian vault on the 8-dimension Grade-A rubric. Read-only. Pure Python. No GPT, no API keys.

When to use this skill

Trigger this skill whenever the user wants to:

1. Audit a vault. "audit my obsidian vault", "is my obsidian healthy", "is my second brain healthy"
2. Find orphans. "find orphans in my vault", "obsidian orphans", "show me unconnected notes"
3. Diagnose a mega-hub. "is my vault a force-star?", "top-hub edge-share", "vault concentration"
4. Grade community structure. "Louvain modularity", "community detection", "are my clusters siloed?"
5. Establish a CI gate. Use --baseline to fail CI when a vault regresses.
6. Compare before/after. Run twice across a refactor to prove improvement.
7. Decide what to fix first. The rubric's worst dimension is the highest-leverage fix.

What it measures (the 8 dimensions)

#	Dimension	Healthy range	Why
1	Link density (edges/note)	4-10	network-science consensus, kepano "Properties as links"
2	Orphan rate (deg 0)	< 10%	Konik PKM-as-graph
3	Near-orphan rate (deg 1)	< 15%	derived complement of orphan threshold
4	Connected ≥2 share	> 75%	derived, most notes should be actually integrated
5	Top-hub edge-share	< 5%	power-law avoidance, Milo motifs
6	Top-hub : next-hub ratio	< 2.0	healthy power-law tail
7	Louvain modularity	0.4-0.65	Newman / Paranyushkin (InfraNodus)
8	Frontmatter-wikilink adoption	> 80%	kepano typed-metadata convention

A vault is Grade A only if every dimension grades A. The worst dimension is the overall grade, by design, so you always see the highest-leverage fix.

How to run

After installation (see ## Install below):