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28 changes: 28 additions & 0 deletions docs/content/modeling/agents/overview.mdx
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---
id: overview
title: 'Authorization for Agents'
slug: /modeling/agents
sidebar_position: 0
description: Authorization patterns for AI agents and automated processes
---

import { CardGrid, DocumentationNotice, IntroCard, ProductName, ProductNameFormat } from '@components/Docs';

<DocumentationNotice />

This section presents authorization patterns for AI agents and automated processes using <ProductName format={ProductNameFormat.LongForm}/>.

<IntroCard
title="When to use"
description="The content in this section is useful if you are building AI agents or automated systems that need fine-grained, scoped permissions to perform actions on behalf of users."
/>

<CardGrid
middle={[
{
title: 'Task-Based Authorization',
description: 'Grant agents access to perform specific actions only when necessary, without granting permanent permissions.',
to: 'agents/task-based-authorization',
},
]}
/>
334 changes: 334 additions & 0 deletions docs/content/modeling/agents/task-based-authorization.mdx
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---
title: Task-Based Authorization
description: Modeling task-based authorization for agents
sidebar_position: 1
slug: /modeling/agents/task-based-authorization
---

import {
CheckRequestViewer,
DocumentationNotice,
ProductName,
ProductNameFormat,
RelatedSection,
} from '@components/Docs';

# Modeling Task-Based Authorization for Agents

<DocumentationNotice />

Agents need credentials to interact with APIs. These can be user or service credentials, for internal or third-party systems. In most cases, those permissions grant agents broad access to the system, as the authorization services that issue credentials for those APIs do not support granting fine-grained permissions. Consent prompts and service credentials are too coarse.

Task-Based Authorization grants agents access to perform specific actions only when necessary, without permanent permissions. Agents start with zero permissions and receive only what a given task requires. For example, rather than allowing an agent to create tickets across all projects, you authorize it to "Create a ticket on project X" — scoping permissions to a specific context.

This guide shows how to model task-based authorization in <ProductName format={ProductNameFormat.ShortForm}/>, progressing from a basic tool-calling model to patterns that support permission hierarchies, session scoping, expiration, and agent binding.

## Tool authorization

The simplest model represents tool authorization for a [Model Context Protocol](https://modelcontextprotocol.io/) server. When a task starts, you write tuples granting it permission to call the tools it needs.

```dsl.openfga
model
schema 1.1

type task

type tool
relations
define can_call: [task, task:*]

type tool_resource
relations
define tool: [tool]
define can_call: [task] or can_call from tool
```

A `tool` represents a capability (e.g. `slack_send_message`), and a `tool_resource` represents a specific target within that tool (e.g. a Slack channel). Granting `can_call` on a `tool` automatically grants access to all its resources. You can also grant access to individual resources, or use `task:*` to allow any task to call a tool.

For example, you can grant `task:1` access to send any Slack message, while restricting `task:2` to a specific channel:

```yaml
tuples:
# Any task can list Slack channels
- user: task:*
relation: can_call
object: tool:slack_list_channels

# task:1 can send any Slack message
- user: task:1
relation: can_call
object: tool:slack_send_message

# task:2 can only send messages to channel XGA14FG
- user: task:2
relation: can_call
object: tool_resource:slack_send_message/XGA14FG
```

When checking whether `task:2` can call `tool_resource:slack_send_message/XGA14FG`, send a [contextual tuple](../../interacting/contextual-tuples.mdx) linking the resource to its tool. This avoids storing a tuple for every channel — you provide the tool-to-resource relationship at query time.

<CheckRequestViewer
user={'task:2'}
relation={'can_call'}
object={'tool_resource:slack_send_message/XGA14FG'}
allowed={true}
skipSetup={true}
contextualTuples={[
{
_description: 'Link the tool_resource to its parent tool',
user: 'tool:slack_send_message',
relation: 'tool',
object: 'tool_resource:slack_send_message/XGA14FG',
},
]}
/>

## Domain-specific models

The model above is generic. If you are building agents for your own application, the authorization model should reflect your application's domain. Consider a project management system:

```dsl.openfga
model
schema 1.1

type user

type task

type organization
relations
define admin: [user]
define member: [user]

type project
relations
define organization: [organization]

# relations for users
define owner: [user]
define member: [user]

# relations for tasks
define read: [task]
define write: [task]
define delete: [task]

# permissions for users
define can_delete: delete or owner or admin from organization
define can_edit: write or owner or admin from organization
define can_read: read or can_edit or member from organization
define can_create_ticket: can_edit

type ticket
relations
define project: [project]
define owner: [user]

# relations for tasks
define read: [task]
define write: [task]
define delete: [task]
define can_delete: owner or delete or can_delete from project
define can_edit: owner or write or can_edit from project
define can_read: read or write or can_read from project
```

Here we enrich an existing user-oriented model by adding `task` as a principal. Granting a `task` the `write` relation on a project gives it permission to read/edit the project and all its tickets. You can also grant permissions at the ticket level for more granular control. This makes your application ready for agent authorization with minimal changes to your existing model.

## Scoping permissions to sessions and agents

In interactive agents, users may create multiple sessions. You can scope permissions to a session so that granting access applies to all tasks within it. You can also scope permissions to an agent, so they persist across sessions.

```dsl.openfga
model
schema 1.1

type task

type agent
relations
define task: [task]

type session
relations
define task: [task]

type tool
relations
define can_call: [task, session#task, agent#task]
```

The `can_call` relation accepts three types of assignments:

- `task` — grant permission to a specific task.
- `session#task` — grant permission to all tasks in a session. When the user says "allow this for this session", write a tuple like `user: session:1#task, relation: can_call, object: tool:slack_send_message`.
- `agent#task` — grant permission to all tasks for an agent, across sessions. When the user says "always allow this", write a tuple with `agent:1#task` instead.

Each task is linked to its session and agent when created:

```yaml
tuples:
# Link task to its agent and session
- user: task:1
relation: task
object: agent:1
- user: task:1
relation: task
object: session:1

# Grant session-level access
- user: session:1#task
relation: can_call
object: tool:slack_send_message
```

## Expiration and turn count

You can use <ProductName format={ProductNameFormat.ShortForm}/> [conditions](../../configuration-language.mdx#conditional-relationships) to make permissions expire after a duration or a number of agent turns.

```dsl.openfga
model
schema 1.1

type task

type tool
relations
define can_call: [task, task with expiration, task with turn_count]

condition expiration(grant_time: timestamp, grant_duration: duration, current_time: timestamp) {
current_time < grant_time + grant_duration
}

condition turn_count(turns_granted: int, current_turn: int) {
current_turn <= turns_granted
}
```

The `expiration` condition grants access for a fixed duration from the grant time. The `turn_count` condition grants access for a fixed number of agent turns. When writing the tuple, you provide the condition parameters:

```yaml
tuples:
# task:1 can call the tool for 10 minutes
- user: task:1
relation: can_call
object: tool:slack_send_message
condition:
name: expiration
context:
grant_time: "2026-03-22T00:00:00Z"
grant_duration: 10m

# task:2 can call the tool for 2 turns
- user: task:2
relation: can_call
object: tool:slack_send_message
condition:
name: turn_count
context:
turns_granted: 2
```

When checking access, pass the current time or turn number in the request context.

## Binding agents to tasks

The examples above don't verify that the agent making the call is actually assigned to the task. You can enforce this using [contextual tuples](../../interacting/contextual-tuples.mdx) and an intersection (`and`) in the model, similar to the [Authorization Through Organization Context](../organization-context-authorization.mdx) pattern.

```dsl.openfga
model
schema 1.1

type task

type agent
relations
define task: [task]

type tool
relations
define agent_in_context: [agent]
define can_call: [task] and task from agent_in_context
```

The `can_call` relation requires both that the task has been granted access **and** that the agent making the call is linked to the task. When the task is created, link it to its agent:

```yaml
tuples:
- user: task:1
relation: task
object: agent:1
- user: task:1
relation: can_call
object: tool:slack_send_message
```

At check time, send a contextual tuple identifying the calling agent. If the agent is linked to the task, the check returns `true`:

<CheckRequestViewer
user={'task:1'}
relation={'can_call'}
object={'tool:slack_send_message'}
allowed={true}
skipSetup={true}
contextualTuples={[
{
_description: 'The agent making the call',
user: 'agent:1',
relation: 'agent_in_context',
object: 'tool:slack_send_message',
},
]}
/>

If a different agent tries to use `task:1`, the check returns `false` because the agent-to-task link won't match:

<CheckRequestViewer
user={'task:1'}
relation={'can_call'}
object={'tool:slack_send_message'}
allowed={false}
skipSetup={true}
contextualTuples={[
{
_description: 'A different agent making the call',
user: 'agent:2',
relation: 'agent_in_context',
object: 'tool:slack_send_message',
},
]}
/>

### Delegating task permissions to sub-agents

Sub-agents also start with zero permissions. When delegating work, you have two options:

- **Share the task**: assign the same task to the sub-agent, giving it all the task's permissions.
- **Restrict further**: create a new task with a narrower set of permissions for the sub-agent.

## Further reading

Mapping user intent to the right set of permissions is an active area of research. These resources explore the topic:

- [Intent-Based Access Control: Securing Agentic AI Through Fine-Grained Authorization](https://ibac.dev/)
- [Delegated Authorization for Agents Constrained to Semantic Task-to-Scope Matching](https://arxiv.org/abs/2510.26702)
- [The Mission Shaping Problem](https://notes.karlmcguinness.com/notes/the-mission-shaping-problem/)
- [Securing Agentic AI: authorization patterns for autonomous systems](https://dev.to/siddhantkcode/securing-agentic-ai-authorization-patterns-for-autonomous-systems-3ajo)

## Related Sections

<RelatedSection
description="Take a look at the following sections for more information."
relatedLinks={[
{
title: 'Conditions',
description: 'Learn how to model relationships with conditions such as expiration and turn count',
link: '../../modeling/conditions',
},
{
title: 'Contextual Tuples',
description: 'Learn how to use contextual tuples to send dynamic context at query time',
link: '../../interacting/contextual-tuples',
}
]}
/>
17 changes: 17 additions & 0 deletions docs/sidebars.js
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Expand Up @@ -309,6 +309,23 @@ const sidebars = {
},
],
},
{
type: 'category',
collapsed: true,
collapsible: true,
label: 'Authorization for Agents',
link: {
type: 'doc',
id: 'content/modeling/agents/overview',
},
items: [
{
type: 'doc',
label: 'Task-Based Authorization',
id: 'content/modeling/agents/task-based-authorization',
},
],
},
{
type: 'category',
collapsed: true,
Expand Down
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