wiki-graphlisted

Use to build and analyse the knowledge wiki as a graph. Runs `scripts/wiki-to-graph.py` (from the research project template) to export an interactive self-contained graph.html (open in any browser, no install) plus graph.json / graph.graphml — and answers questions against the *live* wiki via deterministic query sub-commands (`neighbors`, `path`, `god-nodes`, `bridges`, `relations`, `search`, `stats`), grounded in the result — most-connected pages (god nodes), entities that bridge otherwise-unconnected sources, relation types and confidence (inferred vs grounded), clusters and weak spots. Triggers include "build/show me a knowledge graph", "map the wiki", "graph view of my research", "which entity connects or bridges my sources", "what are the most connected or central pages", "find surprising connections", "where are the gaps or weak links in the wiki", "export the wiki to Gephi/yEd". For frontmatter and wikilink validation use `wiki-lint`; for content and claim audit use `semantic-wiki-review`.
leiverkus/research-superpowers · ★ 0 · Code & Development · score 75

Install: claude install-skill leiverkus/research-superpowers

# Wiki Graph Make the implicit wiki graph explicit, then answer structure questions from it. This is the **structure-analysis** sibling of two other wiki skills: - `wiki-lint` — *is the wiki well-formed?* (frontmatter, broken links, orphans) - `semantic-wiki-review` — *are the claims sound and consistent?* (LLM content audit) - **`wiki-graph` — *what shape does the knowledge have?*** (hubs, bridges, clusters, confidence) The graph is computed deterministically by `scripts/wiki-to-graph.py`; this skill runs it and **interprets** the result. It never invents edges — every claim about the graph traces back to `graph.json`. **Announce at start:** "Using wiki-graph to build and analyse the knowledge graph." ## When to use - "Build / show me a knowledge graph", "map the wiki", "graph view of my research" - "Which entity bridges / connects my sources?" → bridges - "What are the main themes / sub-topics / clusters in my literature?" → communities - "What are the most central / connected pages?" → god nodes - "Find surprising connections" / "where are the weak links or gaps?" - "How many relations are inferred vs grounded?" → inference-rate - "Export the wiki to Gephi / yEd" → hand over `graph.graphml` - After a bulk ingest or a `wiki-lint` pass, to see how the structure changed **NOT for:** frontmatter/wikilink validation (use `wiki-lint`), contradiction/claim audit (use `semantic-wiki-review`), or drafting prose (use `drafting-manuscript`). ## Checklist 1. **Locate the scri