Team Metrics

Access RunMetrics, MessageMetrics, and SessionMetrics from team runs.

The TeamRunOutput from a team run includes detailed metrics about token usage, cost, timing, and per-model breakdowns for the team leader. Member metrics are stored separately on each member’s RunOutput.

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.team import Team
from agno.tools.yfinance import YFinanceTools
from rich.pretty import pprint

stock_agent = Agent(
    name="Stock Agent",
    model=OpenAIResponses(id="gpt-5.2"),
    role="Get stock prices and financial data.",
    tools=[YFinanceTools()],
)

team = Team(
    name="Finance Team",
    model=OpenAIResponses(id="gpt-5.2"),
    members=[stock_agent],
    db=SqliteDb(db_file="tmp/teams.db"),
    markdown=True,
    store_member_responses=True,
)

run_response = team.run("What is the stock price of NVDA?")

# Team leader message metrics (MessageMetrics)
for message in run_response.messages:
    if message.role == "assistant":
        pprint(message.metrics.to_dict())

# Team leader run metrics (RunMetrics)
pprint(run_response.metrics.to_dict())

# Per-model breakdown (leader only)
if run_response.metrics.details:
    for model_type, model_metrics_list in run_response.metrics.details.items():
        for m in model_metrics_list:
            print(f"{model_type}: {m.provider}/{m.id} - {m.total_tokens} tokens")

# Member run metrics (RunMetrics per member)
if run_response.member_responses:
    for member_response in run_response.member_responses:
        print(f"Member: {member_response.agent_name}")
        pprint(member_response.metrics.to_dict())

# Session metrics (SessionMetrics) - aggregates leader + all members
pprint(team.get_session_metrics().to_dict())

Metrics are available at multiple levels:

• Per message: Each assistant message has MessageMetrics with per-API-call token counts and timing.
• Per member run: Each team member run has its own RunMetrics. Set store_member_responses=True to access them.
• Team leader run: TeamRunOutput.metrics has RunMetrics for the team leader’s model calls only.
• Per session: team.get_session_metrics() returns SessionMetrics aggregated across leader and all members.

Level	Type	Access
Per message	MessageMetrics	message.metrics
Per member run	RunMetrics	member_response.metrics (requires store_member_responses=True)
Team leader run	RunMetrics	run_response.metrics
Per session	SessionMetrics	team.get_session_metrics()

Run fields (RunMetrics)

Field	Description
input_tokens	Tokens sent to the model.
output_tokens	Tokens generated by the model.
total_tokens	Sum of input_tokens and output_tokens.
audio_input_tokens	Audio tokens in the input.
audio_output_tokens	Audio tokens in the output.
audio_total_tokens	Sum of audio_input_tokens and audio_output_tokens.
cache_read_tokens	Tokens read from cache.
cache_write_tokens	Tokens written to cache.
reasoning_tokens	Tokens used for reasoning.
cost	Cost of the run.
duration	Run duration in seconds.
time_to_first_token	Time from run start to first token (seconds).
details	Per-model breakdown by model type. See Metrics reference.
additional_metrics	Extra metrics (e.g., eval_duration).

Message fields (MessageMetrics)

Field	Description
input_tokens	Tokens sent to the model.
output_tokens	Tokens generated by the model.
total_tokens	Sum of input_tokens and output_tokens.
audio_input_tokens	Audio tokens in the input.
audio_output_tokens	Audio tokens in the output.
audio_total_tokens	Total audio tokens.
cache_read_tokens	Tokens served from cache.
cache_write_tokens	Tokens written to cache.
reasoning_tokens	Tokens used for reasoning.
cost	Cost of this API call.
duration	Duration of this API call (seconds).
time_to_first_token	Time to first token for this API call (seconds).
provider_metrics	Provider-specific metrics (e.g., Ollama timing, Groq timing, Cerebras timing).

Developer Resources

• TeamRunOutput schema
• Metrics reference
• Cookbook