Standard citation metrics treat all citations as equal, obscuring the social and structural pathways through which scholarly influence propagates. I introduce Citation-Constellation, a freely available no-code tool for citation network analysis with two complementary bibliometric scores that decompose a researcher's citation profile by network proximity between citing and cited authors. BARON (Boundary-Anchored Research Outreach Network score) is a strict binary metric counting only citations from outside the detected collaborative network. HEROCON (Holistic Equilibrated Research Outreach CONstellation score) applies graduated weights assigning partial credit to in-group citations based on relationship proximity. The gap between scores serves as a diagnostic of inner-circle dependence. An extended abstract with full details appears in the paper. The tool implements this through a phased architecture: (1) self-citation analysis, (2) co-authorship graph traversal, (3) temporal institutional affiliation matching via ROR, and (4) AI-agent-driven venue governance extraction using a local LLM. Phases 1-3 are fully operational; Phase 4 is under development. Key design choices include ORCID-validated author identity resolution, an UNKNOWN classification for citations with insufficient metadata, and comprehensive audit trails documenting every classification decision. A no-code web interface enables researchers to compute scores without programming, installation, or registration. I present these scores as structural diagnostics, not quality indicators. BARON and HEROCON describe where in the social graph citations originate. They should not be used for hiring, promotion, or funding decisions. HEROCON weights are experimental and require empirical calibration.

翻译：传统的引文指标将所有引用等量齐观，从而模糊了学术影响力在社会与结构层面上的传播路径。本文介绍了引用星丛（Citation-Constellation），一款免费、无需编码的引文网络分析工具，它通过两个互补的文献计量评分，根据引用者与被引用者之间的网络邻近性，来分解研究人员的引文特征。BARON评分是一种严格的二元指标，仅统计来自已检测协作网络之外的引用。HEROCON评分则采用渐进式权重，根据关系邻近性对组内引用给予部分权重。两个评分之间的差距可作为“内部圈子依赖”的诊断指标。包含完整细节的扩展摘要见正文。该工具通过一个分阶段架构实现：（1）自引分析，（2）合著图遍历，（3）基于ROR的时域机构隶属关系匹配，以及（4）利用本地LLM通过AI代理驱动的场所治理信息提取。阶段1至3已全面运行；阶段4仍在开发中。关键设计选择包括ORCID验证的作者身份解析、针对元数据不足的引用设置“未知”分类，以及记录每项分类决策的全面审计追踪。一个无需编码的网页界面使研究人员无需编程、安装或注册即可计算评分。我将这些评分作为结构性诊断工具而非质量指标加以介绍。BARON与HEROCON描述了引用在社会关系图中的起源位置。它们不应被用于招聘、晋升或资助决策。HEROCON权重尚处于实验阶段，需要经验性校准。