🧪 Skills
rag-query
Query the RAG knowledge base (Qdrant kb_main) by semantic search. Returns top-k chunks with text, doc_id, source, text_type, topic_tags.
v1.0.1
Description
name: rag-query description: Query the RAG knowledge base (Qdrant kb_main) by semantic search. Returns top-k chunks with text, doc_id, source, text_type, topic_tags. metadata: { "openclaw": { "emoji": "🔎", "requires": { "bins": ["node"], "env": ["QDRANT_URL", "EMBED_API_KEY"] }, "primaryEnv": "QDRANT_URL" } }
rag-query
Usage
# 最简单：位置参数作为查询
node skills/rag-query/scripts/query.mjs "渗透测试流程"
# 显式传参 + 控制 top-k 和 topic-tags
node skills/rag-query/scripts/query.mjs \
--query "TCP/IP 模型" \
--top-k 5 \
--topic-tags "net_basic,protocol"
Parameters
| Param | Required | Example | Description |
|---|---|---|---|
--query |
yes* | "渗透测试流程" |
查询字符串；也可以作为第一个位置参数 |
--top-k |
no | 5 |
返回片段数量，默认 5 |
--topic-tags |
no | "net_basic,protocol" |
逗号分隔标签，用于按 topic_tags 过滤 |
--collection |
no | "kb_main" |
Qdrant collection 名称，默认 kb_main |
输出为 JSON 数组，每个元素包含 text、doc_id、source、text_type、topic_tags 字段，可直接注入 Agent 上下文使用。
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