> ## Documentation Index
> Fetch the complete documentation index at: https://aisa.one/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# What Is an Agent Capability Layer?

> Understand how an agent capability layer combines model inference, data APIs, reusable Skills, authenticated actions, and payment controls.

An **agent capability layer** gives an AI agent access to external capabilities through a common integration surface. It sits between the agent runtime and the model providers, data services, tools, and external systems the agent may need.

A model gateway is one part of this layer. It handles model inference. A broader capability layer also helps agents retrieve current information, execute structured workflows, discover tools, and use controlled side effects or payment flows.

## The problem it solves

Without a shared capability layer, an application may need to maintain separate integrations for:

* Model providers and model-specific request formats.
* Search, financial, social, company, and media data.
* Authentication and API keys for each provider.
* Retry, billing, and usage behavior across services.
* Reusable task instructions for agent runtimes.
* OAuth-connected actions and other side effects.

This fragmentation increases integration and operational work. It can also make it harder for an agent to discover which capability is appropriate for the current task.

## The AIsa capability surfaces

AIsa exposes several surfaces for different levels of control:

| Surface                                    | Use it for                                                       |
| ------------------------------------------ | ---------------------------------------------------------------- |
| [AI model inference](/docs/guides/models)       | Reasoning, generation, coding, vision, and supported media tasks |
| [Agent Skills](/docs/agent-skills)              | Reusable task-oriented workflows and instructions                |
| [Direct APIs](/docs/api-reference)              | Application-controlled endpoint composition                      |
| Authenticated actions                      | Approved writes to connected external systems                    |
| [Agent discovery](/docs/guides/agent-discovery) | A2A, MCP, OpenAPI, and machine-readable capability inspection    |
| [Payments](/docs/guides/pricing/wallet)         | Funding usage and controlling billable API consumption           |

These surfaces are complementary. A workflow may use a model to plan, a Skill to select a process, direct APIs to collect evidence, and an authenticated action to publish an approved result.

## Capability layer versus workflow platform

A capability layer supplies access and reusable integration primitives. It does not automatically define every business process, approval rule, or application state transition.

Your application or agent runtime still owns decisions such as:

* Which task should run.
* Which data is sufficient evidence.
* Which writes require confirmation.
* How budgets and retries are enforced.
* What application state is retained.

Use AIsa to reduce provider integration work, not to replace application-specific policy.

## When this architecture is useful

Consider a capability layer when an agent needs more than one of the following:

* Multiple model families through a common interface.
* Current external data from several domains.
* Reusable Skills shared across agent clients.
* Machine-readable discovery through A2A, MCP, or OpenAPI.
* Controlled external actions or programmatic API purchasing.

A direct provider integration may be simpler when the application needs only one stable model or one specialized API.

## Next steps

* [When to use AIsa](/docs/evaluate/when-to-use-aisa)
* [Model gateway versus capability layer](/docs/concepts/model-gateway-vs-capability-layer)
* [Capabilities by goal](/docs/by-goal)
* [Capabilities by interface](/docs/by-interface)