Traits

What are Traits?

Traits are structured attributes extracted from user conversations. Unlike unstructured memory, traits are:

Typed: String, number, boolean, array, or enum
Labeled: Each trait has a defined key and category
Scored: Confidence level from 0.0 to 1.0
Tracked: Source messages are recorded (optionally)

Trait Structure

interface Trait {
  id: string;
  profileId: string;
  key: string; // e.g., "preferred_language"
  category: string | null; // e.g., "communication"
  valueType: "string" | "number" | "boolean" | "array" | "enum";
  value: unknown;
  confidence: number; // 0.0 - 1.0
  source: "extracted" | "manual" | "inferred";
  sourceMessageIds: string[];
  createdAt: Date;
  updatedAt: Date;
}

Default Traits

GetProfile includes these default traits out of the box:

Trait	Type	Category	Description
`name`	string	identity	User’s name or preferred name
`preferred_language`	string	communication	Communication language
`communication_style`	enum	communication	formal, casual, technical, simple
`detail_preference`	enum	communication	brief, moderate, detailed
`expertise_level`	enum	context	beginner, intermediate, advanced, expert
`timezone`	string	context	User’s timezone
`interests`	array	preferences	Topics the user is interested in
`current_goals`	array	context	What the user is working toward

Customize or extend this schema via JSON configuration files or dynamically per-request. See Trait Schema Configuration for details.

Confidence Scores

Confidence represents how certain GetProfile is about a trait value:

Score	Meaning	Example
0.9+	Explicit statement	”My name is Alex”
0.7-0.9	Strong indication	Uses technical jargon consistently
0.5-0.7	Moderate inference	Seems to prefer detailed responses
< 0.5	Weak inference	Might be interested in Python

Traits with low confidence are still stored but may not be injected into prompts. Configure the confidenceThreshold in your trait schema.

Trait Sources

Source	Description
`extracted`	Automatically extracted from conversations
`manual`	Set directly via API
`inferred`	Derived from other traits or patterns

Trait Updates

When new information conflicts with existing traits:

Higher confidence wins: New extraction with 0.8 confidence overrides existing 0.5
Manual takes priority: Manually set traits are preserved unless explicitly updated
Contradictions delete: If new info directly contradicts a trait, it’s deleted

Example: Trait Extraction

Given this conversation:

User: Hi, I'm Alex and I've been coding in Python for about 5 years now.
      I prefer when explanations are concise and technical.

GetProfile extracts:

[
  {
    "key": "name",
    "value": "Alex",
    "confidence": 0.95,
    "action": "create"
  },
  {
    "key": "expertise_level",
    "value": "advanced",
    "confidence": 0.75,
    "action": "create"
  },
  {
    "key": "communication_style",
    "value": "technical",
    "confidence": 0.85,
    "action": "create"
  },
  {
    "key": "detail_preference",
    "value": "brief",
    "confidence": 0.7,
    "action": "create"
  }
]

Getting Started

Core Concepts

Client SDKs

Configuration

Deployment

What are Traits?

Trait Structure

Default Traits

Confidence Scores

Trait Sources

Trait Updates

Example: Trait Extraction

​What are Traits?

​Trait Structure

​Default Traits

​Confidence Scores

​Trait Sources

​Trait Updates

​Example: Trait Extraction

What are Traits?

Trait Structure

Default Traits

Confidence Scores

Trait Sources

Trait Updates

Example: Trait Extraction