> Source: https://builder.ema.ai/v2/agent-reference/respond
> Title: Respond Agent

# Respond Agent

The Respond agent (`respond`) generates a natural-language reply using its system prompt and LLM configuration — nothing more. It is the simplest LLM-based agent type: no search loop, no schema, no tools by default. You give it Instructions and a model, it produces text. Use it whenever a workflow step just needs the model to _say something_ — a confirmation message, a summary, a rewrite, a friendly reply.

In the AI Employee (AIE) builder, the Respond Agent appears in the **Generation** group of the agent library.

> [INFO]
> **First-class, lifecycle-eligible type.** Unlike the Document Writer (which is dispatch-only), `respond` is one of the platform's lifecycle-eligible base types. It is seeded in the agent-type catalog with a live `v0` version and is subject to publish-time version validation, exactly like `search_respond`, `intent_classification`, `extraction`, and `rule_validation`. See the [Agent Reference overview](/builder/v2/agent-reference#the-agent-type-catalog).

## When to use it

Use a Respond agent for a pure generation step where the model's only job is to write a reply from your Instructions:

-   Acknowledge or confirm something to the user ("Your request has been logged…").
-   Summarize or rephrase upstream content.
-   Produce a short message that a later node delivers.

If the step needs to ground the answer in your documents, use [Knowledge Search](/builder/v2/agent-reference/knowledge-search) or [Search and Respond](/builder/v2/agent-reference/search-and-respond). If it needs to call integrations or return structured JSON, use a [Custom](/builder/v2/agent-reference/custom) agent. If it produces a full document, use the [Document Writer](/builder/v2/agent-reference/document-writer).

## How it works

`respond` uses the platform's **passthrough injector**: no type-specific instruction block is appended to your system prompt. What you write in Instructions is what the model receives (after `{{input.field}}` placeholders are substituted and wrapped in a prompt-injection guard). The agent then runs a single LLM completion through EmaFusion™ and returns the text.

Because there is no search step and no type-specific contract, a Respond agent is the lightest LLM type on the [shared execution model](/builder/v2/agent-reference#the-shared-execution-model) — it validates inputs, resolves Instructions, calls the model, and returns the reply.

## Configuration

The Respond agent exposes these advanced settings in the builder:

Setting

Purpose

Instructions

The system prompt the model follows. Supports `{{input.<field>}}` placeholders.

LLM configuration

The model and generation settings, served through EmaFusion™.

HITL

Optional human-in-the-loop, letting the agent pause to ask a clarifying question via `ask_human`.

The `respond` base type has **no required `type_config`** — its `type_config` schema is empty. The default Instructions are:

```text
You are a helpful assistant. Respond to the user based on the system prompt
and LLM configuration.

User instructions: {{input.instructions}}
```

## Inputs and output

The preset declares one input field, `instructions` — the query or prompt the agent should respond to. You wire it on the node through `input_mapping`.

**Input**

```json
{ "instructions": "Thank the customer for their patience and confirm their refund of $49 is being processed." }
```

**Output**

The Respond agent emits a **bare string** — the model's reply, with no JSON wrapper. There is no `{ "message": "..." }` envelope at runtime.

```text
Thank you for your patience! Your refund of $49 is being processed and should
appear on your statement within 5–7 business days.
```

> [TIP]
> **Wiring the output downstream.** Because the output is the whole string, reference it as `{{<node_id>.output}}` in a downstream node's `input_mapping` — without a trailing field name. In a publish node, omit `field_path` so the publisher takes the full string. In the builder, the node also exposes a single `answer` output port that maps to this whole-output value.

## Example

A simple acknowledgment step at the end of a workflow:

1.  An [Intent Classification](/builder/v2/agent-reference/intent-classification) node routes a request.
2.  A **Respond** node generates a tailored confirmation message, with the request details wired into its `instructions` input.
3.  A publish node sends the reply to the user.

## What's next

-   [Agent Reference overview](/builder/v2/agent-reference) — the type model, catalog, and shared execution engine.
-   [Document Writer Agent](/builder/v2/agent-reference/document-writer) — generate structured documents instead of a short reply.
-   [Search and Respond Agent](/builder/v2/agent-reference/search-and-respond) — ground a reply in your knowledge base with citations.