rerank-service
文档重排序服务（Reranker）。基于深度学习模型对检索候选结果进行细粒度相关性打分与重新排序，显著提升检索结果的精准度（Top-K 准确率）。
Profile →npx skills add majiayu000/claude-skill-registry --skill rerank-service-lin-a1-skills-agent-0ce0d629 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## 功能 根据查询语句对候选文档进行相关性评分和排序，提升检索准确性。 ## 调用方式 ```python from services.rerank_service.client import RerankServiceClient client = RerankServiceClient() query = "什么是机器学习？" documents = [ "机器学习是人工智能的一个分支，通过数据训练模型。", "今天天气很好，适合出去散步。", "深度学习是机器学习的子领域，使用神经网络。" ] # 完整重排序结果 result = client.rerank(query, documents, top_n=2) # 简化结果：(索引, 分数, 文档) 元组列表 ranked = client.rerank_documents(query, documents, top_n=2) # 只获取最相关的文档索引 indices = client.get_top_indices(query, documents, top_n=2) # -> [0, 2] ``` ## 返回格式 ```json { "id": "rerank-xxx", "model": "BAAI/bge-reranker-v2-m3", "results": [ { "index": 0, "document": {"text": "机器学习是人工智能的一个分支..."}, "relevance_score": 0.999 }, { "index": 2, "document": {"text": "深度学习是机器学习的子领域..."}, "relevance_score": 0.098 } ] } ```
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- 调用方式
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What does the rerank-service skill do?
文档重排序服务（Reranker）。基于深度学习模型对检索候选结果进行细粒度相关性打分与重新排序，显著提升检索结果的精准度（Top-K 准确率）。
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill rerank-service-lin-a1-skills-agent-0ce0d629 --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 majiayu000/claude-skill-registry, a repository with 534 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.