Documentation Index
Fetch the complete documentation index at: https://agno-v2-rbac-doc-update.mintlify.app/llms.txt
Use this file to discover all available pages before exploring further.
Access tool execution timing with ToolCallMetrics on each ToolExecution in the run output.
Code
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.yfinance import YFinanceTools
from rich.pretty import pprint
agent = Agent(
model=OpenAIChat(id="gpt-4o-mini"),
tools=[YFinanceTools()],
markdown=True,
)
if __name__ == "__main__":
run_output = agent.run("What is the stock price of AAPL and NVDA?")
# Run-level metrics
print("=" * 50)
print("RUN METRICS")
print("=" * 50)
pprint(run_output.metrics)
# Each tool call carries its own timing metrics
print("=" * 50)
print("TOOL CALL METRICS")
print("=" * 50)
if run_output.tools:
for tool_call in run_output.tools:
print(f"Tool: {tool_call.tool_name}")
if tool_call.metrics:
pprint(tool_call.metrics)
print("-" * 40)
# Per-model breakdown
print("=" * 50)
print("MODEL DETAILS")
print("=" * 50)
if run_output.metrics and run_output.metrics.details:
for model_type, model_metrics_list in run_output.metrics.details.items():
print(f"\n{model_type}:")
for model_metric in model_metrics_list:
pprint(model_metric)
Usage
Create a Python file
Create tool_call_metrics.py with the code above.
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
Install dependencies
uv pip install -U agno openai yfinance
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
Run Agent
python tool_call_metrics.py