Overview
- Skill Key
- cinience/volcengine-ai-search-rag
- Author
- cinience
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/cinience/volcengine-ai-search-rag
- Latest Commit SHA
- 8fce79eb3a19f406d4fd0020eed84ae96eae4885
Official OpenClaw
rules
36%
volcengine-ai-search-rag
Retrieval and RAG workflow on Volcengine AI stack. Use when users need embedding search, document indexing, top-k retrieval, grounding prompts, or search relevance tuning.
Stars
0
Installs
0
Status
ACTIVE
Visibility
PUBLIC
安装方式
直接复制以下提示词，发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店，若未安装，请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店，然后安装 volcengine-ai-search-rag 技能。 若已安装，则直接安装 volcengine-ai-search-rag 技能。
Extracted Content
SKILL.md excerpt
# volcengine-ai-search-rag Implement retrieval-first answering with explicit indexing, retrieval, and grounding stages. ## Execution Checklist 1. Confirm corpus source and chunking strategy. 2. Generate embeddings and build/update index. 3. Retrieve top-k context with filters. 4. Build grounded answer with citations to retrieved chunks. ## Quality Rules - Separate retrieval prompt from generation prompt. - Keep chunk metadata (source, timestamp, id). - Return confidence and fallback path if no hits. ## References - `references/sources.md`
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