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

# What are Agents in Octave?

> Agents are out-of-the-box AI workflows grounded in your Library and context. Run them as-is, save reusable configurations, or build your own on the raw primitives.

## What is an Agent?

An Agent in Octave is a pre-built AI workflow that produces a specific GTM outcome — enriching a company, qualifying a person, generating a sequence, prepping for a call — grounded in your [Library](/concepts/library) and your [analytics](/concepts/analytics) findings. Agents are the fastest way to deploy AI into your GTM stack: each one encodes Octave's best-practice prompting, context retrieval, and GTM logic for its task, so you don't have to build that scaffolding yourself.

Over time, teams typically graduate to building their own custom workflows on top of the raw primitives Octave exposes — the [Library](/concepts/library), [Context Search](/v2-api-reference/context/context-search), [Findings](/v2-api-reference/findings/list-findings), and [Resources](/concepts/resources). Out-of-the-box Agents are the on-ramp.

## Agent types

Octave ships with the following agent types. Each has its own input schema and is callable directly or through a saved Agent configuration:

| Agent                 | What it does                                                      |
| --------------------- | ----------------------------------------------------------------- |
| **Enrich Person**     | Builds a structured intelligence report on a single person        |
| **Enrich Company**    | Same, for a single company                                        |
| **Qualify Person**    | Scores a person against your ICP / persona criteria               |
| **Qualify Company**   | Scores a company against your ICP / segment criteria              |
| **Prospector**        | Finds and qualifies prospects matching ICP criteria               |
| **Sequence**          | Generates a multi-touch outbound sequence (1–4 emails)            |
| **Content**           | Generates LinkedIn, social, or short-form copy                    |
| **Call Prep**         | Builds call-prep notes with talking points and objection handling |
| **Context**           | Surfaces relevant Library context for an arbitrary query          |
| **Workspace Builder** | Bootstraps a workspace from a URL or short description            |

See the [Agents API reference](/v2-api-reference/agents/list-agents) for the full request/response schema of each.

## Ad-hoc vs Saved Agents

Every agent type can be called two ways:

1. **Ad-hoc** — POST directly to the agent's run endpoint with all inputs in the body. Good for one-off scripts and testing.
2. **Saved Agent** — create an Agent in the dashboard or via `POST /api/v2/agents/create`, configure it (custom prompts, brand voice, default context), then run it later by passing its `agentOId`. Saved Agents are the right shape for production use because the configuration is versioned and shared across your team.

Saved Agents also support **experiments** via `POST /api/v2/agents/experiment/create` — branch a configuration, test it against the original, and pin the winner.

## How agents use context

Every agent run pulls context from your [Library](/concepts/library) at execution time. For most agents, the relevant [Motion](/concepts/motions) is selected based on the offering and the prospect's persona/segment match, and the matched [Motion ICP](/concepts/motions#motion-icps) supplies the narrative, learnings, and recommended evidence (proof points, references, objections, alternatives) that ground the output.

You can override the auto-selected context with `customContext` in the request body — pinning a specific playbook, product, persona, or segment when you want fully deterministic output.

## Sync vs Async

Most agent endpoints expose both a synchronous variant (returns the result in the HTTP response) and an async variant via [Async / callbacks](/concepts/async-callbacks). Choose async for batch operations, expensive agents (Enrich, Prospector), or any workflow that exceeds the sync timeout.

## Workflows

For multi-step pipelines (enrich → qualify → generate → notify), use [Workflows](/concepts/workflows) — graphs of agents wired together that you trigger as a single async job.

## Managing Agents via API

* `GET /api/v2/agents/list` — list saved agents
* `GET /api/v2/agents/get` — get a specific saved agent
* `POST /api/v2/agents/create` — create a saved agent
* `POST /api/v2/agents/update` — update a saved agent
* `DELETE /api/v2/agents/delete` — delete a saved agent
* `GET /api/v2/agents/types` — list available agent types
* `GET /api/v2/agents/languages` — list supported output languages
* `POST /api/v2/agents/experiment/create` — branch a saved agent into an experiment
* `POST /api/v2/agents/{type}/run` — run an agent of a given type (sync)
* `POST /api/v2/async/agent/run` — run any saved agent asynchronously with a callback URL