Team Tool Call Metrics

Access team leader metrics, member run metrics, and tool execution timing with ToolCallMetrics.

Code

team_tool_metrics.py

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.team import Team
from agno.tools.yfinance import YFinanceTools
from rich.pretty import pprint

stock_searcher = Agent(
    name="Stock Searcher",
    model=OpenAIChat(id="gpt-4o-mini"),
    role="Searches for stock information.",
    tools=[YFinanceTools()],
)

team = Team(
    name="Stock Research Team",
    model=OpenAIChat(id="gpt-4o-mini"),
    members=[stock_searcher],
    markdown=True,
    show_members_responses=True,
    store_member_responses=True,
)

if __name__ == "__main__":
    run_output = team.run("What is the stock price of NVDA?")

    # Team leader run metrics
    print("=" * 50)
    print("TEAM LEADER RUN METRICS")
    print("=" * 50)
    pprint(run_output.metrics)

    # Member metrics and tool call timing
    print("=" * 50)
    print("MEMBER METRICS AND TOOL CALLS")
    print("=" * 50)
    if run_output.member_responses:
        for member_response in run_output.member_responses:
            print(f"\nMember: {member_response.agent_name}")
            print("-" * 40)
            pprint(member_response.metrics)

            if member_response.tools:
                print(f"\nTool calls ({len(member_response.tools)}):")
                for tool_call in member_response.tools:
                    print(f"  Tool: {tool_call.tool_name}")
                    if tool_call.metrics:
                        pprint(tool_call.metrics)

Usage

1. Create a Python file

   Create team_tool_metrics.py with the code above.

2. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   
3. Install dependencies

   uv pip install -U agno openai yfinance
   
4. Export your OpenAI API key

   Mac/Linux

   export OPENAI_API_KEY="your_openai_api_key_here"
   
5. Run Team

   python team_tool_metrics.py