An Agent component packages an autonomous runtime actor that receives a goal and independently determines how to accomplish it. Unlike a Skill (which provides knowledge) or a Command (which responds to a user trigger), an Agent is the primary decision-making unit — it can invoke tools, delegate to other agents, and maintain state across multiple steps within a session.Documentation Index
Fetch the complete documentation index at: https://agentvolumes.mintlify.app/llms.txt
Use this file to discover all available pages before exploring further.
When to use Agent
Use theagent type when your component:
- Takes a goal or task description and operates independently to complete it
- Needs to call tools, skills, or other agents as part of its execution
- Runs for multiple steps before returning a final result
- Maintains context across interactions within a session
Entrypoint format
Agent entrypoints can be either Markdown (.md) or YAML (.yaml). The Markdown format is most common and typically contains the agent’s system prompt, behavioral instructions, tool bindings, and any other configuration the runtime needs to instantiate the agent.
The portable validation minimum requires:
- The entrypoint file exists and is a regular file.
- The file extension is
.mdor.yaml. - YAML entrypoints must parse as valid YAML.
Declaring an agent in volume.toml
Add a [[components]] entry with type = "agent" and point entrypoint to your agent definition file.
Agent semantics
The Agent Volumes spec defines four behavioral properties for agents:- Goal-driven: An agent receives a goal or task and autonomously determines how to accomplish it.
- Tool and skill use: An agent can invoke tools, skills, and other agents during execution.
- Session state: An agent can maintain state across interactions within a session.
- Behavior configuration: An agent’s behavior is defined by its system prompt, available tools, and configured policies.
The spec defines packaging and distribution semantics, not execution semantics. How a runtime
instantiates and runs an agent — what model it uses, how it manages context windows, how it
orchestrates tool calls — is runtime-local behavior.
Optional fields
Two optional fields apply to all component types and are particularly useful for agents:| Field | Type | Description |
|---|---|---|
description | string | One-line description surfaced in registry search and tooling. |
providers | array of strings | External services the agent integrates with (e.g., ["arxiv", "github"]). |
permissions | table | Component-specific permission overrides. Can only narrow volume-level permissions. |