# 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.

- Skill: `modbender/volcengine-ai-search-rag` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds add modbender/volcengine-ai-search-rag`
- Raw SKILL.md: https://api.skillmd.com/api/skills/modbender/volcengine-ai-search-rag/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: modbender (https://skillmd.com/u/modbender)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/modbender/volcengine-ai-search-rag

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# 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`