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

# Identity Fields

> Rich metadata in MemU — emotional context, entities, relationships, and personal attributes.

## Overview

MemU memories are more than just text blobs. Each memory carries **identity fields** -- structured metadata that captures the emotional, relational, and contextual dimensions of information. This enables the agent to recall not just *what* happened, but *how it felt*, *who was involved*, and *why it mattered*.

## Entity Fields

### Entities

A JSON array of people, places, organizations, and things referenced in the memory:

```json theme={null}
{
  "entities": ["Jason", "Richard", "Dell R750", "Titanium Computing"]
}
```

Entities are used in:

* **Search boosting**: Queries mentioning an entity boost memories about that entity
* **Relationship mapping**: Understanding who is connected to whom
* **Context assembly**: When the agent is talking to a specific user, relevant entity memories are prioritized

### Relationships

Memories can encode relationships between entities:

```json theme={null}
{
  "content": "Jason and Richard are business partners at Titanium Computing",
  "entities": ["Jason", "Richard", "Titanium Computing"],
  "type": "relationship"
}
```

## Emotional Context

The `emotional_context` field captures the emotional tone or significance of an interaction:

```json theme={null}
{
  "content": "Jason was frustrated with the WhatsApp connection dropping repeatedly",
  "emotional_context": "frustrated, technical difficulty",
  "significance": 6
}
```

This helps the agent:

* Recall how a user felt about something
* Avoid repeating approaches that caused frustration
* Show appropriate empathy in responses

## Memory Types

The `type` field categorizes memories:

| Type           | Description              | Example                                                  |
| -------------- | ------------------------ | -------------------------------------------------------- |
| `fact`         | Objective information    | "Jason has 30+ years IT experience"                      |
| `preference`   | User preferences         | "Prefers open-source when quality is comparable"         |
| `event`        | Something that happened  | "Deployed the new dashboard on Feb 5"                    |
| `relationship` | People connections       | "Jason and Richard are business partners"                |
| `instruction`  | How-to knowledge         | "To rebuild native modules: pnpm rebuild better-sqlite3" |
| `observation`  | Agent's own observations | "User tends to work late on Thursdays"                   |

## Significance Interaction

Identity fields interact with significance scoring. A memory with:

* High emotional intensity -> higher significance
* Multiple entities -> likely more important
* Relationship type -> higher baseline significance

<Info>
  The agent learns to calibrate significance based on these signals over time.
</Info>

## Querying by Identity

Memory recall can leverage identity fields for more targeted searches:

```json theme={null}
{
  "tool": "memory_recall",
  "input": {
    "query": "Richard preferences",
    "entity": "Richard",
    "type": "preference"
  }
}
```

## Privacy Considerations

<Warning>
  Identity fields can contain sensitive personal information. All memory data is stored locally in `~/.argentos/memory.db` and never transmitted externally. The agent's memory is private to the installation.
</Warning>