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Analyzes X/Twitter follower/following networks using graph algorithms like PageRank, betweenness, community detection, and influencers to find clusters, bridges, and segments. Use for audience or competitor network structure insights.
How this skill is triggered — by the user, by Claude, or both
Slash command
/xactions:graph-analysisThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
API-powered network graph analysis for X/Twitter follower relationships.
API-powered network graph analysis for X/Twitter follower relationships.
| Goal | Route | Method |
|---|---|---|
| Build a network graph | POST /api/graph/build | REST API |
| Get graph data | GET /api/graph/:id | REST API |
| Run graph algorithms | POST /api/graph/:id/analyze | REST API |
| Export graph | GET /api/graph/:id/export | REST API |
| Visualize graph | GET /api/graph/:id/visualize | REST API |
POST /api/graph/build
Authorization: Bearer <token>
Content-Type: application/json
{
"username": "nichxbt",
"depth": 1, // 1 = direct followers, 2 = followers of followers
"maxNodes": 500 // Limit graph size
}
POST /api/graph/:id/analyze
Authorization: Bearer <token>
Content-Type: application/json
{
"algorithm": "pagerank" // "pagerank" | "betweenness" | "community" | "influencers"
}
| Algorithm | Description |
|---|---|
pagerank | Rank nodes by influence (like Google's PageRank) |
betweenness | Find bridge accounts connecting different clusters |
community | Detect communities/clusters within the network |
influencers | Identify top influencers by degree centrality |
| Goal | Approach |
|---|---|
| Find bridge accounts for cross-audience reach | algorithm: "betweenness" |
| Identify communities in your follower base | algorithm: "community" |
| Find most influential followers | algorithm: "influencers" |
| Rank followers by network influence | algorithm: "pagerank" |
depth: 2 creates much larger graphs — use maxNodes to limitnpx claudepluginhub nirholas/xactionsApplies network analysis to determine how structure shapes outcomes across centrality, contagion, weak ties, and network effects. Routes to the right sub-skill based on your situation.
Creates, manipulates, and analyzes complex networks and graphs using Python. Covers shortest paths, centrality, community detection, PageRank, graph I/O, and visualization.
Creates, analyzes, and visualizes complex networks and graphs in Python. Use for graph algorithms, centrality, community detection, and network generation.