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

# Agents

> What an agent is, how it runs, and how to control its reasoning behavior.

An **agent** is a configurable AI assistant. It combines a language model with instructions, optional tools, memory, and knowledge — packaged as a reusable unit that the Alquimia Runtime can execute.

## What makes up an agent

| Component                | What it does                                                        | Required                       |
| ------------------------ | ------------------------------------------------------------------- | ------------------------------ |
| **Language model**       | The LLM that generates responses                                    | Yes                            |
| **System prompt**        | Identity, personality, rules, and purpose                           | Yes (auto-generated or custom) |
| **MCP tools**            | External services the agent can call                                | No                             |
| **Agent-to-Agent**       | Other agents the agent can delegate to                              | No                             |
| **Memory**               | Conversation history (short-term) or persistent context (long-term) | No                             |
| **Knowledge base**       | Document collection for RAG-based answers                           | No                             |
| **Integration channels** | WhatsApp, Email — external communication interfaces                 | No                             |
| **Pre-processor**        | Sentinels and empathy rules that run before the agent               | No                             |

## How agents run

When a user sends a message:

```
User message
    ↓
Pre-processor (sentinels, empathy rules) — optional
    ↓
Memory retrieval — inject relevant history
    ↓
Knowledge retrieval — inject relevant document passages
    ↓
LLM call — prompt + context + tool schemas
    ↓
Tool execution (if needed) — ReAct loop
    ↓
Response returned to user
```

The Runtime handles all of this automatically based on the agent's configuration. You don't write any of this logic — you configure it in Studio.

## Evaluation strategies

The evaluation strategy controls how the agent **thinks**. This is one of the most important settings for an agent.

| Strategy    | Description                                     | Best for                              |
| ----------- | ----------------------------------------------- | ------------------------------------- |
| `off`       | Single LLM call, no reasoning loop              | Simple Q\&A, content generation       |
| `one-shoot` | One call with tool schemas injected             | Structured output, simple tool use    |
| `tools`     | LLM calls tools in a single round               | Deterministic, tool-first workflows   |
| `react`     | ReAct loop: reason → act → observe → repeat     | Multi-step tool use, complex tasks    |
| `long-task` | Extended planning for complex, multi-step tasks | Research agents, autonomous workflows |

<Note>
  When you add MCP servers or other agents to your agent, Studio automatically switches the evaluation strategy to `react`. This ensures the agent can actually use its tools. You can override this manually in [Dev Mode](/platform/agent-creation/dev-mode).
</Note>

### The ReAct loop explained

`react` is the most powerful strategy. The agent follows this cycle:

1. **Reason** — "I need to look up the user's account to answer this"
2. **Act** — calls the `get_account` tool from an MCP server
3. **Observe** — receives the tool result
4. **Reason again** — "Now I have the account info, I can answer"
5. **Respond** — generates the final answer

This continues until the agent has enough information to respond or hits its reasoning limit.

## Next steps

<CardGroup cols={2}>
  <Card title="Creating an Agent" icon="plus" href="/platform/agent-creation/overview">
    Step-by-step walkthrough of the agent creation wizard.
  </Card>

  <Card title="Dev Mode" icon="code" href="/platform/agent-creation/dev-mode">
    Take full control of the system prompt and evaluation strategy.
  </Card>
</CardGroup>