get_cost_summary()
Get an aggregate cost summary for your tenant over a time period.
summary = client.get_cost_summary(
period="month",
from_date="2026-03-01",
to_date="2026-03-17",
)
Aggregation period: day, week, month
Start date (ISO 8601). Defaults to start of current month.
End date (ISO 8601). Defaults to today.
Returns:
{
"total_cost_usd": 1245.67,
"total_input_tokens": 15234000,
"total_output_tokens": 4567000,
"total_requests": 8923,
"period": "month",
"from": "2026-03-01T00:00:00Z",
"to": "2026-03-17T23:59:59Z"
}
get_cost_by_agent()
Break down costs by individual agent.
by_agent = client.get_cost_by_agent(
from_date="2026-03-01",
to_date="2026-03-17",
limit=10,
)
Number of agents to return (sorted by cost descending)
Returns:
[
{
"agent_id": "agt_abc123",
"agent_name": "production-summarizer",
"team": "support-team",
"total_cost_usd": 456.78,
"input_tokens": 5600000,
"output_tokens": 1200000,
"requests": 3400
},
{
"agent_id": "agt_def456",
"agent_name": "lead-qualifier",
"team": "sales-team",
"total_cost_usd": 312.45,
"input_tokens": 4100000,
"output_tokens": 980000,
"requests": 2100
}
]
get_cost_by_model()
Break down costs by model.
by_model = client.get_cost_by_model(
from_date="2026-03-01",
to_date="2026-03-17",
)
Returns:
[
{
"model_provider": "openai",
"model_name": "gpt-4o",
"total_cost_usd": 890.12,
"input_tokens": 10200000,
"output_tokens": 3100000,
"requests": 5800
},
{
"model_provider": "anthropic",
"model_name": "claude-sonnet-4-20250514",
"total_cost_usd": 355.55,
"input_tokens": 5034000,
"output_tokens": 1467000,
"requests": 3123
}
]