ReddRadar
Agent skill
topics
Explore topic distribution in the paper library using BERTopic clustering. Build/rebuild topic models, view topic overview, list papers in a topic, merge similar topics, and generate HTML visualizations. Use when the user asks about research themes, topic distribution, or wants to discover cross-domain connections.
Install this agent skill to your Project
npx add-skill https://github.com/ZimoLiao/scholaraio/tree/main/.claude/skills/topics
SKILL.md
主题探索
探索论文库的主题分布，发现跨领域关联。基于 BERTopic 聚类。
执行逻辑
-
判断用户意图：
- "建模"、"重建主题" → 构建/重建
- "合并主题"、"压缩到N个" → 智能合并
- "可视化"、"画图" → 生成 HTML
- 查看某主题详情 → 主题查询
- 查看 outlier → topic -1
- 默认展示概览
-
执行命令：
构建/重建主题模型：
scholaraio topics --build
scholaraio topics --rebuild [--min-topic-size N] [--nr-topics N]
手动合并指定主题（格式: 逗号分隔同组ID，+分隔不同组）：
scholaraio topics --merge "1,6,14+3,5"
算法合并到 N 个主题：
scholaraio topics --reduce <N>
查看主题概览：
scholaraio topics
查看指定主题的论文：
scholaraio topics --topic <ID> [--top N]
生成 HTML 可视化（6 张图表）：
scholaraio topics --viz
- 智能合并流程（当用户要求合并/压缩主题时）：
a. 先执行
topics获取所有主题概览 b. 分析每个主题的关键词，判断哪些主题在学术上属于同一研究方向 c. 生成合并方案 d. 用--merge执行合并
示例
用户说："帮我看看库里的主题分布"
→ 执行 topics
用户说："主题2里有哪些论文"
→ 执行 topics --topic 2
用户说："帮我把相似的主题合并一下"
→ 先 topics 查看概览，分析关键词，再 topics --merge "1,6,14+3,5"
用户说："给我画个主题分布图"
→ 执行 topics --viz
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