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agent

Skill

Add an AI agent / chatbot / RAG backend on Convex with @convex-dev/agent (durable threads, messages, tools, vector search). TRIGGER when the user wants an AI assistant/chatbot/agent or 'chat with my docs' feature. Keeps the LLM key in Convex env.

0Machine Learning

Install

git clone https://github.com/get-convex/convex-backend-skill.git ~/.claude/skills/agent

What is agent?

Add an AI agent / chatbot / RAG backend on Convex with @convex-dev/agent (durable threads, messages, tools, vector search). TRIGGER when the user wants an AI assistant/chatbot/agent or 'chat with my docs' feature. Keeps the LLM key in Convex env.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~62 tokens of context used while enabled, before you invoke anything

Documentation

README · ~1 min read

Add an AI agent / RAG backend

Install @convex-dev/agent for durable threads, message history, tool-calls, and vector search/RAG — the backend for an in-app AI agent.

Steps

  1. Install @convex-dev/agent + add to convex.config.ts.
  2. Define the agent (model, tools, instructions); store the LLM key via the env micro power.
  3. Create threads + stream messages; persist history in Convex.
  4. For RAG: embed docs into a vector index and retrieve in the tool.

Rules

  • Keep the LLM API key in Convex env (use the env micro power), never client-side.
  • Run model calls in actions ('use node' if the SDK needs it).
  • Persist threads/messages in Convex for durability + reactivity.

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