> ## 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 guideline adherence

> Learn how to use the session guideline adherence test to evaluate whether the assistant follows a given behavioural guideline

## Definition

The session guideline adherence test evaluates whether the assistant **followed one
or more customer-supplied behavioural guidelines** across a conversation. You supply
each guideline as an object with a `criteria` rule (e.g., "always refer to the user
by their first name") and a `scoring` mode (`"Yes or No"` or `"0-1"`). An
LLM-as-a-judge evaluates the full session against each guideline independently and
reports per-guideline scores plus aggregate adherence metrics.

This is the session-level metric most suited to codifying product-specific behaviour
that generic catalog tests don't cover.

## 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 (guideline followed).

## Why it matters

* Almost every product has a handful of custom behavioural rules that don't map to
  the generic catalog — this metric is the knob for those.
* Because the guideline is customer-supplied, you can track behaviour unique to your
  product, brand voice, or regulatory context.
* Multi-guideline support lets you bundle a policy (brand voice + tone + forbidden
  topics) into a single insight and see aggregate adherence across a session.

## 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

* **`criteria_list`** (list of objects, required): One or more guidelines to
  evaluate. Each object contains:
  * **`criteria`** (string): The guideline text in plain English.
  * **`scoring`** (string): Either `"Yes or No"` (binary judgment — adherent or
    not) or `"0-1"` (a continuous 0–1 float where `1` = perfect adherence).

<Note>
  All guidelines in a single `criteria_list` should use the same `scoring` mode
  — the default adherence threshold is derived from the first entry's mode.
</Note>

<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>

## Default adherence threshold

A session is counted as "adherent" when its aggregate score is at or above:

* **`0.8`** when `scoring` is `"0-1"`
* **`0.5`** when `scoring` is `"Yes or No"` (Yes is encoded as `1.0`, No as `0.0`)

This threshold drives the `adherentSessionsPercent` and `violationRate` measurements
below.

## Available measurements

| Measurement                | What it means                                         |
| -------------------------- | ----------------------------------------------------- |
| `meanGuidelineAdherence`   | Average adherence score across sessions in the window |
| `medianGuidelineAdherence` | Median adherence score across sessions                |
| `stdGuidelineAdherence`    | Standard deviation of per-session adherence scores    |
| `minGuidelineAdherence`    | Lowest per-session adherence score                    |
| `maxGuidelineAdherence`    | Highest per-session adherence score                   |
| `adherentSessionsPercent`  | % of sessions meeting the default adherence threshold |
| `violationRate`            | % of sessions below the default adherence threshold   |
| `totalEvaluatedSessions`   | Count of sessions the judge evaluated                 |
| `erroredSessionsCount`     | Count of sessions that errored during evaluation      |
| `skippedSessionsCount`     | Count of sessions skipped (e.g., insufficient turns)  |

## Test configuration examples

<CodeGroup>
  ```json Monitoring theme={null}
  [
    {
      "name": "Brand-voice guideline adherence above 0.7",
      "description": "Ensure the assistant follows the brand-voice guideline across sessions",
      "type": "performance",
      "subtype": "sessionGuidelineAdherence",
      "thresholds": [
        {
          "insightName": "sessionGuidelineAdherence",
          "insightParameters": [
            {
              "name": "criteria_list",
              "value": [
                {
                  "criteria": "Always refer to the user by their first name and never recommend a competitor product.",
                  "scoring": "0-1"
                }
              ]
            }
          ],
          "measurement": "meanGuidelineAdherence",
          "operator": ">=",
          "value": 0.7
        }
      ],
      "subpopulationFilters": null,
      "mode": "monitoring",
      "usesProductionData": true,
      "evaluationWindow": 3600,
      "delayWindow": 0
    }
  ]
  ```
</CodeGroup>

## Related

* [Session role adherence](/tests/catalog/session-role-adherence) — related signal focused on staying in a defined role.