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Construire des couches de contexte SQL et de recherche vectorie…

Utilisez TiDB lorsqu'un agent a besoin d'un seul magasin SQL transactionnel pouvant également stocker des embeddings et effectuer une recherche vectorielle pour les workflows RAG, de mémoire ou de contexte applicatif.

Qu'est-ce que Construire des couches de contexte SQL et de recherche vectorie… ?

TiDB est une base de données SQL distribuée compatible MySQL qui prend en charge à la fois le traitement transactionnel et la recherche vectorielle. Cette compétence permet aux agents IA d'utiliser TiDB comme couche de contexte unifiée pour la génération augmentée par récupération (RAG), la mémoire persistante des agents, ou les workflows d'application nécessitant une combinaison de requêtes SQL structurées et de recherche sémantique par vecteurs. Avec TiDB, vous pouvez stocker des embeddings de documents ou de sessions directement dans la même base de données que vos données transactionnelles, évitant ainsi la complexité opérationnelle de synchroniser plusieurs magasins de données. La compétence s'applique à tout agent utilisant TiDB ou TiDB Cloud, et nécessite un modèle d'embedding, un client SQL ou un connecteur applicatif, ainsi que les documents sources ou enregistrements applicatifs appropriés. Elle est particulièrement utile pour les workflows où la cohérence transactionnelle et la recherche sémantique sont nécessaires simultanément, comme les chatbots contextuels, les systèmes de recommandation, ou les applications de mémoire à long terme pour agents.

Compatible avec~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/build-sql-and-vector-retrieval-context-layers-with-tidb
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Documentation

Construire des couches de contexte SQL et de recherche vectorielle avec TiDB

Utilisez TiDB lorsqu'un agent a besoin d'un seul magasin SQL transactionnel pouvant également stocker des embeddings et effectuer une recherche vectorielle pour les workflows RAG, de mémoire ou de contexte applicatif.

Prérequis

TiDB ou TiDB Cloud, un modèle d'embedding, un client SQL ou connecteur applicatif, des documents sources ou enregistrements applicatifs

Installation

Aucune instruction d'installation ou d'utilisation basée sur une source n'a pu être extraite automatiquement. Veuillez consulter le projet en amont avant d'exécuter cette compétence dans un workflow sensible.

Documentation

Source

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

Academic Paper Citation Network Mapper

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Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.

Add executable smoke tests for shell scripts and CLIs before ref

Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.

Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Add IDE-style semantic code navigation and symbol-safe refactors

Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.

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Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.

Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Address GitHub PR review comments from the current branch with g

Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.

Add runtime guardrails to TypeScript agents with VoltAgent

Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

Add temporal context memory to agent workflows with Zep

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

Adobe Firefly API Batch Image Generator

Calls Adobe Firefly

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