How do I install the Zeabur RAG Search skill?

Run npx skillmds@latest add zeabur/zeabur-rag-search in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Zeabur RAG Search safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Zeabur RAG Search?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Zeabur RAG Search free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Zeabur RAG Search?

zeabur (@zeabur) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Zeabur RAG Search by zeabur — Agent Skill

Name: Zeabur RAG Search
Author: zeabur

Zeabur RAG Search

Search the RAG knowledge base via hybrid search (semantic + BM25). Use whenever answering technical questions that may be covered in your knowledge base — even if the user doesn't explicitly ask you to search. Also use when you need to verify claims or find up-to-date information.

zeabur Updated Sep 17, 2026

File contents

RAG Search

Search your knowledge base using hybrid retrieval (semantic + BM25 keyword).

Base URL: $ZEABUR_RAG_URL Auth: Authorization: Bearer $RAG_API_KEY

API

curl -s -X POST "$ZEABUR_RAG_URL/api/query" \
  -H "Authorization: Bearer $RAG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query": "your question", "mode": "hybrid", "rag": false, "top_k": 5, "client": "claude-code"}'

Parameter	Default	Description
`query`	required	Search query (supports multilingual)
`mode`	`"hybrid"`	`"hybrid"`, `"semantic"`, or keyword-only `"bm25"`
`top_k`	`5`	Number of chunks to return
`rag`	`false`	If `true`, also returns LLM-generated `answer` string
`keyword_weight`	`0.25`	BM25 weight in hybrid mode
`semantic_weight`	`0.75`	Semantic weight in hybrid mode
`rerank`	`false`	If `true`, use an LLM to reorder a wider candidate pool
`rerank_pool_size`	`30`	Candidate count considered when reranking
`decay`	`180`	Temporal decay half-life in days (0 = off)
`stream`	`false`	Stream the RAG answer (NDJSON)
`sources`	key permissions	Optional source list, intersected with the API key's read permissions
`client`	`"api"`	Caller identifier for analytics (e.g. `"claude-code"`, `"web-ui"`, `"mcp"`)

Always pass client: "claude-code" when calling from Claude Code so queries are trackable in the dashboard.

Response includes chunks[] (each with id, title, answer, tags, similarity (relevance score), source, verified) and signal_id for linking feedback. Score scales differ between BM25, hybrid RRF, and semantic modes, so do not compare values across modes.

Tips

Use rag: false when you only need raw chunks to read yourself — it's faster and cheaper.
Set rag: true only when you want the service to generate a summarized answer.
The signal_id in the response can be passed to the feedback API to rate result quality.

---name: zeabur-rag-searchdescription: Search the RAG knowledge base via hybrid search (semantic + BM25). Use whenever answering technical questions that may be covered in your knowledge base — even if the user doesn't explicitly ask you to search. Also use when you need to verify claims or find up-to-date information.---# RAG SearchSearch your knowledge base using hybrid retrieval (semantic + BM25 keyword).Base URL: `$ZEABUR_RAG_URL`Auth: `Authorization: Bearer $RAG_API_KEY`## API```bashcurl -s -X POST "$ZEABUR_RAG_URL/api/query" \ -H "Authorization: Bearer $RAG_API_KEY" \ -H "Content-Type: application/json" \ -d '{"query": "your question", "mode": "hybrid", "rag": false, "top_k": 5, "client": "claude-code"}'```| Parameter | Default | Description ||-----------|---------|-------------|| `query` | required | Search query (supports multilingual) || `mode` | `"hybrid"` | `"hybrid"`, `"semantic"`, or keyword-only `"bm25"` || `top_k` | `5` | Number of chunks to return || `rag` | `false` | If `true`, also returns LLM-generated `answer` string || `keyword_weight` | `0.25` | BM25 weight in hybrid mode || `semantic_weight` | `0.75` | Semantic weight in hybrid mode || `rerank` | `false` | If `true`, use an LLM to reorder a wider candidate pool || `rerank_pool_size` | `30` | Candidate count considered when reranking || `decay` | `180` | Temporal decay half-life in days (0 = off) || `stream` | `false` | Stream the RAG answer (NDJSON) || `sources` | key permissions | Optional source list, intersected with the API key's read permissions || `client` | `"api"` | Caller identifier for analytics (e.g. `"claude-code"`, `"web-ui"`, `"mcp"`) |**Always pass `client: "claude-code"` when calling from Claude Code** so queries are trackable in the dashboard.Response includes `chunks[]` (each with `id`, `title`, `answer`, `tags`, `similarity` (relevance score), `source`, `verified`) and `signal_id` for linking feedback. Score scales differ between BM25, hybrid RRF, and semantic modes, so do not compare values across modes.## Tips- Use `rag: false` when you only need raw chunks to read yourself — it's faster and cheaper.- Set `rag: true` only when you want the service to generate a summarized answer.- The `signal_id` in the response can be passed to the feedback API to rate result quality.

Frequently asked questions