Social Graph Ranker

A weighted graph-ranking engine that tells you which of your LinkedIn or X connections can best introduce you to specific targets. It calculates bridge scores using exponential decay across hops, expands second-order paths for high-value mutuals, and factors in engagement history. You get tiered lists: warm intro candidates, conditional paths, and gaps where you need direct outreach. The math is clean and the workflow is narrow. Use this when you want the ranking layer itself, not the full outbound pipeline that lead-intelligence wraps around it or the pruning logic in connections-optimizer. It's the core pathfinding piece pulled out so you can run it standalone when all you need is "who should I ask to make this introduction."

skills.sh installs: 5.4K
GitHub stars: 300.3K
last updated: Aug 21, 2026

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Install

$ npx -y skills add affaan-m/ecc --skill social-graph-ranker --agent claude-code

Installs into .claude/skills of the current project.

Files

Social Graph Ranker

Canonical weighted graph-ranking layer for network-aware outreach.

Use this when the user needs to:

rank existing mutuals or connections by intro value
map warm paths to a target list
measure bridge value across first- and second-order connections
decide which targets deserve warm intros versus direct cold outreach
understand the graph math independently from lead-intelligence or connections-optimizer