embedding-service
文本向量化（Embedding）基础服务。将自然语言转换为高维稠密向量，为语义搜索、聚类分析、推荐系统等下游任务提供核心数据支持。
npx skills add majiayu000/claude-skill-registry --skill embedding-service-lin-a1-skills-agent --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 将输入文本转换为高维向量表示，用于语义相似度计算、聚类分析等下游任务。 ## 调用方式 ```python from services.embedding_service.client import EmbeddingServiceClient client = EmbeddingServiceClient() # 单个文本向量化 vector = client.embed_query("人工智能") # -> list[float] # 多个文本向量化 texts = ["机器学习", "深度学习", "自然语言处理"] vectors = client.embed_documents(texts) # -> list[list[float]] ``` ## 返回格式 ```json { "object": "list", "data": [ { "object": "embedding", "index": 0, "embedding": [-0.031, -0.016, -0.007, ...] } ], "model": "Qwen/Qwen3-Embedding-0.6B" } ```
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What does the embedding-service skill do?
文本向量化（Embedding）基础服务。将自然语言转换为高维稠密向量，为语义搜索、聚类分析、推荐系统等下游任务提供核心数据支持。
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill embedding-service-lin-a1-skills-agent --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.