social-graph-ranker
Weighted social-graph ranking for warm intro discovery, bridge scoring, and network gap analysis across X and LinkedIn. Use when the user wants the reusable graph-ranking engine itself, not the broader outreach or network-maintenance workflow layered on top of it.
npx skills add mturac/everything-openai-codex --skill social-graph-ranker --agent codex
Same command for any agent — swap --agent for claude-code, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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` ## When To Use This Standalone Choose this skill when the user primarily wants the ranking engine: - "who in my network is best positioned to introduce me?" - "rank my mutuals by who can get me to these people" - "map my graph against this ICP" - "show me the bridge math" Do not use this by itself when the user really wants: - full lead generation and outbound sequencing -> use `lead-intelligence` - pruning, rebalancing, and growing the network -> use `connections-optimizer` ## Inputs Collect or infer: - target people, companies, or ICP definition - the user's current graph on X, LinkedIn, or both - weighting priorities such as role, industry, geography, and responsiveness - traversal depth and decay tolerance ## Core Model Given: - `T` = weighted t
- When To Use This Standalone
- Inputs
- Core Model
- Scoring Signals
- Workflow
- Output Shape
- Related Skills
What does the social-graph-ranker skill do?
Weighted social-graph ranking for warm intro discovery, bridge scoring, and network gap analysis across X and LinkedIn. Use when the user wants the reusable graph-ranking engine itself, not the broader outreach or network-maintenance workflow layered on top of it.
How do I install it?
Run `npx skills add mturac/everything-openai-codex --skill social-graph-ranker --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mturac/everything-openai-codex, a repository with 84 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.