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Use TiDB when an agent needs one transactional SQL store that can also hold embeddings and serve vector retrieval for RAG, memory, or app-context workflows.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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| name | Build SQL and vector retrieval context layers with TiDB |
| slug | build-sql-and-vector-retrieval-context-layers-with-tidb |
| description | Use TiDB when an agent needs one transactional SQL store that can also hold embeddings and serve vector retrieval for RAG, memory, or app-context workflows. |
| github_stars | 40235 |
| verification | listed |
| source | https://github.com/pingcap/tidb |
| author | PingCAP |
| publisher_type | organization |
| category | Data Extraction & Transformation |
| framework | Multi-Framework |
| tool_ecosystem | {"github_repo":"pingcap/tidb","github_stars":40235} |
Use TiDB when an agent needs one transactional SQL store that can also hold embeddings and serve vector retrieval for RAG, memory, or app-context workflows.
TiDB or TiDB Cloud, an embedding model, SQL client or application connector, source documents or application records
No source-backed install or usage instructions could be extracted automatically. Review the upstream project before running this skill in a sensitive workflow.
