> ## 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 task progression

> Learn how to use the session task progression test to evaluate whether sessions make steady progress toward the task

## Definition

The session task progression test evaluates whether a conversation **makes steady
progress** toward the user's inferred task. An LLM-as-a-judge reads the full session
and scores it against four criteria:

* Each turn logically advances the task
* Steps are ordered sensibly (prerequisites before follow-ups)
* Intermediate milestones are acknowledged before moving on
* The conversation doesn't loop, repeat itself, or backtrack unnecessarily

## 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. `0` = no progress, `1` = excellent steady
  progress.

## Why it matters

* A session can end with the goal achieved and still have been inefficient — looping
  through blind alleys before finding the answer.
* Tracking progression complements [Session goal achievement](/tests/catalog/session-goal-achievement):
  together they tell you both whether the task was completed and whether the path to
  completion was clean.

## 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.

<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 task progression above 0.7",
      "description": "Ensure sessions make steady progress toward the user's task",
      "type": "performance",
      "subtype": "sessionTaskProgression",
      "thresholds": [
        {
          "insightName": "sessionTaskProgression",
          "measurement": "meanScore",
          "operator": ">=",
          "value": 0.7
        }
      ],
      "subpopulationFilters": null,
      "mode": "monitoring",
      "usesProductionData": true,
      "evaluationWindow": 3600,
      "delayWindow": 0
    }
  ]
  ```
</CodeGroup>

## Related

* [Session goal achievement](/tests/catalog/session-goal-achievement) — end-state view of the same concern.