second-brain-graph

# Analyse the graph The graph is the search space every answer is drawn from. Its shape decides whether retrieval reaches the relevant material in a few hops or reaches nothing. ## Core rule Report shape and what it means, never fix anything. This skill is read-only. ## Workflow 1. **Run the scripts** rather than reading files: `scripts/vault_stats.py` for counts and degree, `scripts/link_check.py` for orphans and breaks, `scripts/graph_export.py` when deeper analysis is wanted. 2. **Compute the four metrics:** orphan rate, average degree, component count, stale-page rate. 3. **Identify hubs** (pages that have swallowed the graph) and **bridges** (pages connecting otherwise separate clusters). 4. **Name the clusters.** These are what the vault is actually about, which is reliably different from what the user would say it is about. 5. **Say what each number means** for answering questions, not just the value. ## Output format ``` Pages <n> | links <n> | avg degree <n> Orphan rate <n>% (healthy under 5) Components <n> (main holds <n>%) Stale concepts <n>% (untouched 90+ days) Hubs: <pages with outsized degree, and whether to split them> Bridges: <pages connecting clusters, and what breaks if they are wrong> Clusters: <what the vault is actually about> What this means: <two or three sentences> ``` ## Calibration Never report page count or word count as a health signal. Both rise whether the vault is improving or not. A single reading says little. If the user has recorded previous numbers, compare against them; if not, suggest recording these.