> For the complete documentation index, see [llms.txt](https://docs.amigo.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.amigo.ai/agent.md).

# Agent

- [Agent Core](https://docs.amigo.ai/agent/agents.md): Versioned agent identity, background, behavioral guidance, communication patterns, and voice configuration.
- [Reasoning Engine](https://docs.amigo.ai/agent/reasoning-engine.md): The modality-independent reasoning core that processes signals and emits effects, powering voice, text, simulation, and API agent interactions through a unified pipeline.
- [Context Graphs](https://docs.amigo.ai/agent/context-graphs.md): Structured state machines that define conversation flow, decision points, and safety boundaries for agent workflows.
- [Dynamic Behaviors](https://docs.amigo.ai/agent/context-graphs/dynamic-behaviors.md): Classic API dynamic behavior sets, including semantic triggers, instruction injection, tool changes, versioning, and Platform API alternatives.
- [Memory](https://docs.amigo.ai/agent/memory.md): How conversation-derived observations, semantic user models, and structured clinical context become source-linked memory for later sessions.
- [Clinical Tools](https://docs.amigo.ai/agent/clinical-tools.md): Current built-in world tools for patient lookup, scheduling, clinical reads, and source-attributed writes.
- [Platform Functions](https://docs.amigo.ai/agent/platform-functions.md): Workspace-registered SQL, AI, Python, and table-valued functions for governed data retrieval and computation.
- [Continuous Improvement](https://docs.amigo.ai/agent/pattern-discovery-and-reuse.md): Use production evidence, simulations, and versioned releases to improve agent behavior through an explicit, governed team workflow.


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.amigo.ai/agent.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.