Agents Overview

What a DataGen agent is made of, how a run works, and where people reach it

An agent is a folder of instructions that DataGen runs for you in the cloud. Its CLAUDE.md is the prompt; skills, slash commands and sub-agents sit next to it under .claude/. Every time the agent runs, DataGen starts a sandbox from the agent’s environment, loads its files, gives it the credentials, tools, knowledge and data you connected, and lets a harness drive the conversation.

What an agent is made of

An agent combines the three foundation components with the building blocks you attach to it.

Part	What it decides	Where you set it
Harness	The runtime that drives each turn (Claude Agent SDK by default, or Codex), its exact version, and an optional Anthropic-compatible gateway	Settings tab, Harness & model
Sandbox environment	The image, packages and resources each run’s sandbox starts from	Builder Config, or Settings tab
Vault	Which credentials the agent’s tools and code authenticate with	Builder Config, or Settings tab
Tools	The tool bundle (allowlist of default, MCP and custom tools in that vault), plus the DataGen MCP gateway and workspace data tools	Builder Config, Tools tab
Context	The knowledge bases connected to the agent, read-only or read & write	Builder Config, Data access tab
Data	Published analytic models the agent can query, and which raw workspace files it may read	Builder Config, Data access tab
Files	CLAUDE.md, .claude/skills/, .claude/commands/, .claude/agents/ and any scripts or reference files	Builder sandbox files, Files tab, or a GitHub repo

Anything you leave unset uses the workspace default: the default vault and tool bundle, the default sandbox environment, and the built-in harness with the system default model.

You can set up an agent without touching the foundation pages first. When you need a custom package, a different credential set or an LLM gateway, see Vault, Sandbox Environments and Harness.

Where an agent’s files live

An agent’s files come from one of two sources. The source decides how you edit them.

Workspace storage

Agents you create with Create New or Upload. Edit them in the Agent Builder, where every Publish creates a version you can roll back to.

GitHub repository

Agents you add with Connect repo. One repository is one agent; you edit by pushing to the repo, and DataGen reads the checkout on each run.

How a run works

1. Something triggers the agent

   A chat message, an Agent API call, an automation’s schedule or webhook, a message on a channel such as Slack or email, a public chat link, or another agent.

2. DataGen picks the model

   If the harness pins a provider model, that model always wins. Otherwise the first one set is used: the model named in the API call, the automation’s model, the agent’s default model, then the system default.

3. The sandbox starts

   The sandbox boots from the agent’s sandbox environment. The agent’s files are loaded, each connected knowledge base is mounted read-only at /mnt/context/contexts/<slug>/, and vault credentials are made available to tools and code.

4. The harness runs the turn

   The harness follows CLAUDE.md, loads skills as needed, and calls the tools in the agent’s tool bundle. Connected analytic models are queried with the datagen-data CLI.

5. The reply goes back

   The answer returns to where the run started: the chat, the API response, the Slack or Teams thread, the email reply, or the automation’s destinations. Every run is recorded in Agent Logs.

Configuration changes such as vault, tool bundle, model, connected context and data apply from the agent’s next turn. File changes go live when you publish them.

Enabled and disabled

An agent answers only while it is Enabled. Turning it off with the status pill on the agent page stops it everywhere: chat, API calls, public links, email, chat apps, rooms and automations. Test run in the builder keeps working, so you can keep building a disabled agent. Publishing from the builder enables the agent.

Who can do what

Workspace role	Can do
Admin, Builder	Create agents, change configuration, publish, enable or disable
Operator	Everything a Viewer can, plus Run now on automations
Viewer	Read the agent’s configuration, files and logs

Next

Build an agent

Create an agent in the Agent Builder, fork a template, or connect a GitHub repo

Give it tools

Vaults, tool bundles, MCP servers, custom tools and the DataGen MCP gateway