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

# Session role adherence

> Learn how to use the session role adherence test to evaluate whether the assistant stays in its defined role

## Definition

The session role adherence test evaluates whether the assistant **stays in its
defined role** across a multi-turn conversation. You supply a role description in
plain English (for example, "a customer-support agent for an e-commerce platform
who handles order tracking, returns, and product questions"), and an LLM-as-a-judge
scores how well the assistant kept to that role throughout the session.

## Taxonomy

* **Task types**: LLM.
* **Availability**: <Tooltip tip="Continuously evaluate your models and datasets as you iterate on their versions.">development</Tooltip>
  and <Tooltip tip="Monitor a model in production, measure its health, check for drifts and set up alerts.">monitoring</Tooltip>.
* **Evaluation level**: session.
* **Polarity**: higher score = better (role adhered to).

## Why it matters

* Role drift is a leading indicator of prompt leakage, jailbreak success, or
  retrieval-augmented context bleeding into the agent's persona.
* Role adherence at the session level catches drift that builds across turns and is
  invisible to per-turn checks.

## Required columns

* **Input**: The user's message in each turn.
* **Output**: The assistant's response in each turn.
* **Session ID**: Groups turns belonging to the same conversation.
* **Timestamp**: Used to reconstruct turn order within a session.

## Insight parameters

* **`role_definition`** (string, optional): A plain-English description of the
  assistant's expected role. If omitted, the judge falls back to a generic
  "appropriate-for-context" role check (useful when you haven't yet formalized
  the role, but lower-signal than the explicit version).

The judge evaluates four dimensions when a role is supplied:

* **Persona / expertise** — does the assistant present itself as the specified role?
* **Scope** — does it stay within the role's topical boundaries?
* **Tone & style** — does it match the communication style expected of the role?
* **Handling out-of-role requests** — does it decline or redirect cleanly?

<Note>
  This metric relies on an LLM evaluator. On Openlayer you can configure the
  underlying LLM used to compute it. Check out the
  [OpenAI](/integrations/openai#openai-llm-evaluator) or
  [Anthropic](/integrations/anthropic#anthropic-llm-evaluator) integration
  guides for details.
</Note>

## Test configuration examples

<CodeGroup>
  ```json Monitoring theme={null}
  [
    {
      "name": "Session role adherence above 0.7",
      "description": "Ensure the assistant stays in its defined customer-support role",
      "type": "performance",
      "subtype": "sessionRoleAdherence",
      "thresholds": [
        {
          "insightName": "sessionRoleAdherence",
          "insightParameters": [
            {
              "name": "role_definition",
              "value": "You are a customer-support agent for an e-commerce platform. You help with order tracking, returns, and product questions."
            }
          ],
          "measurement": "meanScore",
          "operator": ">=",
          "value": 0.7
        }
      ],
      "subpopulationFilters": null,
      "mode": "monitoring",
      "usesProductionData": true,
      "evaluationWindow": 3600,
      "delayWindow": 0
    }
  ]
  ```
</CodeGroup>

## Related

* [Session guideline adherence](/tests/catalog/session-guideline-adherence) — broader custom-behaviour check.