对 X 与 LinkedIn 社交图谱进行加权排序,发现暖介绍路径、桥接联系人与网络缺口。
复制安装指令,让 AI 自动完成配置 · 推荐新手
请帮我安装 askskill 上的 "social-graph-ranker" 技能: 1. 下载 https://raw.githubusercontent.com/affaan-m/ECC/main/skills/social-graph-ranker/SKILL.md 2. 保存为 ~/.claude/skills/social-graph-ranker/SKILL.md 3. 装好后重载技能,告诉我可以用了
请基于我在 X 和 LinkedIn 的联系人数据,构建加权社交图谱,并为我与目标公司 CTO 之间的暖介绍路径排序。综合考虑互动频率、关系强度、共同联系人质量和最近活跃度,输出前 5 条最可信路径及原因。
按优先级排序的暖介绍路径列表,包含每条路径的桥接人、评分依据与推荐顺序。
分析我的 X 和 LinkedIn 网络,找出最能连接不同圈层的桥接联系人。请根据跨社群连接度、影响力、互动稳定性和引荐成功潜力进行评分,并列出前 10 名及适合联系的场景。
一份桥接联系人排名清单,说明他们连接哪些圈层、为何重要以及适用引荐场景。
请检查我在 X 和 LinkedIn 上的人脉结构,识别对招聘 AI 基础设施岗位最关键但目前覆盖不足的网络缺口。按行业、职能、资历层级和地域输出缺口评分,并建议优先补强的连接方向。
网络缺口分析报告,包含高优先级薄弱区域、缺口评分与补强建议。
Canonical weighted graph-ranking layer for network-aware outreach.
Use this when the user needs to:
lead-intelligence or connections-optimizerChoose this skill when the user primarily wants the ranking engine:
Do not use this by itself when the user really wants:
lead-intelligenceconnections-optimizerCollect or infer:
Given:
T = weighted target setM = your current mutuals / direct connectionsd(m, t) = shortest hop distance from mutual m to target tw(t) = target weight from signal scoringBase bridge score:
B(m) = Σ_{t ∈ T} w(t) · λ^(d(m,t) - 1)
Where:
λ is the decay factor, usually 0.5Second-order expansion:
B_ext(m) = B(m) + α · Σ_{m' ∈ N(m) \\ M} Σ_{t ∈ T} w(t) · λ^(d(m',t))
Where:
N(m) \\ M is the set of people the mutual knows that you do notα discounts second-order reach, usually 0.3Response-adjusted final ranking:
R(m) = B_ext(m) · (1 + β · engagement(m))
Where:
engagement(m) is normalized responsiveness or relationship strengthβ is the engagement bonus, usually 0.2Interpretation:
R(m) and direct bridge paths -> warm intro asksR(m) and one-hop bridge paths -> conditional intro asksR(m) or no viable bridge -> direct outreach or follow-gap fillWeight targets before graph traversal with whatever matters for the current priority set:
Weight mutuals after traversal with:
R(m).SOCIAL GRAPH RANKING
====================
Priority Set:
Platforms:
Decay Model:
Top Bridges
- mutual / connection
base_score:
extended_score:
best_targets:
path_summary:
recommended_action:
Conditional Paths
- mutual / connection
reason:
extra hop cost:
No Warm Path
- target
recommendation: direct outreach / fill graph gap
lead-intelligence uses this ranking model inside the broader target-discovery and outreach pipelineconnections-optimizer uses the same bridge logic when deciding who to keep, prune, or addbrand-voice should run before drafting any intro request or direct outreachx-api provides X graph access and optional execution paths为 Quarkus 项目执行发布前验证闭环,涵盖构建、测试、扫描与差异审查。
连接 Semrank,在对话中生成 SEO 简报并分析内容语义覆盖情况。