CrewAI - TraceRoot

Automatically capture agent roles, tasks, crew executions, and tool invocations within the CrewAI framework.

Setup

Python

import traceroot
from traceroot import Integration

traceroot.initialize(integrations=[Integration.CREWAI, Integration.OPENAI])

Usage

Once initialized, crew and agent executions are captured automatically:

from crewai import Agent, Task, Crew

researcher = Agent(
    role="Research Analyst",
    goal="Uncover the latest developments in AI agent frameworks",
    backstory="You are an expert at identifying emerging trends in AI.",
)

writer = Agent(
    role="Tech Writer",
    goal="Craft a compelling summary of AI agent framework trends",
    backstory="You turn complex technical insights into engaging narratives.",
)

research_task = Task(
    description="Analyze the latest AI agent frameworks and summarize key trends.",
    expected_output="A concise research summary",
    agent=researcher,
)

write_task = Task(
    description="Write a short article based on the research summary.",
    expected_output="A short article on AI agent framework trends",
    agent=writer,
    context=[research_task],
)

crew = Crew(agents=[researcher, writer], tasks=[research_task, write_task])

# The entire crew execution is automatically traced
result = crew.kickoff()

What Gets Captured

Attribute	Description
Crew execution	The overarching `kickoff()` session
Agent roles	Each agent’s role, goal, and backstory as span metadata
Task steps	Individual task executions with inputs and outputs
Tool calls	Tool invocations with input arguments and results
LLM calls	Raw completion requests to the provider
Delegation hierarchy	Manager-agent relationships and task assignments
Token usage	Aggregated across all LLM calls
Cost	Total cost for the full crew execution

Run the example

Clone the repo and run a complete agent end-to-end.

Python

Run the Python example