social-graph-ranker

Provide a weighted target list and your connection graph, then the skill computes a bridge score for each mutual based on weighted paths and hop distance. Results are ranked by a response-adjusted score and grouped into warm intro asks, conditional paths, and gaps.

Each mutual's base score sums target weights multiplied by a decay factor raised to the hop distance minus one, so direct paths count fully and each extra hop halves the contribution. A second-order expansion adds discounted value from connections of your mutuals.

Yes, the model accepts graphs from X, LinkedIn, or both platforms combined. You supply the connection data and weighting priorities, and the same traversal and scoring logic applies regardless of source platform.

This skill is the standalone graph-ranking engine only. Use lead-intelligence for full lead generation and outbound sequencing, and connections-optimizer for pruning and growing your network; both build on this ranking model.

Skip it when you need complete outbound sequencing or network maintenance rather than ranking math. It also adds little value if you have no existing mutual connections, since there are no warm paths to score.