Session token count

Definition

The session token count test monitors the total tokens used per session. It aggregates the per-trace token count across all turns in a session. No LLM evaluator is involved — it’s a deterministic aggregation.

Taxonomy

Task types: LLM.
Availability: and .
Evaluation level: session.
Computation: deterministic aggregation.

Why it matters

Session-level token usage is the cleanest proxy for “how much work did the LLM do for this user”.
Outliers often reveal conversations that are hitting context-window limits, pulling in too much RAG context per turn, or looping.

Available measurements

Measurement	What it means
`totalTokens`	Sum of tokens across all traces in the window (global, not per-session)
`meanTokensPerSession`	Mean of per-session token sums across sessions in the window
`medianTokensPerSession`	Median of per-session token sums across sessions in the window

Required columns

Session ID: Groups turns belonging to the same conversation.
Token count: Per-trace token count (usually populated automatically by the Openlayer client or via OpenTelemetry).

Test configuration examples

[
  {
    "name": "Mean session token count below 10k",
    "description": "Alert when average session token usage exceeds 10,000 tokens",
    "type": "performance",
    "subtype": "sessionTokenCount",
    "thresholds": [
      {
        "insightName": "sessionTokenCount",
        "measurement": "meanTokensPerSession",
        "operator": "<=",
        "value": 10000
      }
    ],
    "subpopulationFilters": null,
    "mode": "monitoring",
    "usesProductionData": true,
    "evaluationWindow": 3600,
    "delayWindow": 0
  }
]

Session cost — cost view of the same usage.
Mean tokens, Max tokens, Total tokens — trace-level token metrics.

Session task progression

Session turn relevancy

⌘I

​Definition

​Taxonomy

​Why it matters

​Available measurements

​Required columns

​Test configuration examples

​Related