Team Metrics

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Overview

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Accessing Team Metrics

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Token Metrics

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Request & Tool Metrics

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Timing Metrics

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Cost Metrics

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Aggregation Metadata

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Team Identity

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Example

from upsonic import Agent, Team

team = Team(
    entities=[
        Agent("openai/gpt-4o-mini", name="Researcher"),
        Agent("anthropic/claude-sonnet-4-5", name="Reviewer"),
    ],
)

team.do("Plan and review a small feature.")

u = team.usage
print(f"Requests:        {u.requests}")
print(f"Input tokens:    {u.input_tokens}")
print(f"Output tokens:   {u.output_tokens}")
print(f"Tool calls:      {u.tool_calls}")
if u.cost is not None:
    print(f"Cost:            ${u.cost:.4f}")
print(f"Model time:      {u.model_execution_time:.2f}s")
print(f"Tool time:       {u.tool_execution_time:.2f}s")
print(f"Framework time:  {u.upsonic_execution_time:.2f}s")
print(f"Models used:     {u.models}")

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JSON-Friendly Output

import json

snapshot = team.usage.to_dict()
print(json.dumps(snapshot, indent=2))

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Scope & Propagation

• Across members — Every team member’s model call records an entry tagged with the team’s team_usage_id. Reading team.usage re-aggregates all of them.
• Per-member breakdown — Each agent still has its own agent_usage_id. To see one member in isolation, read that agent’s agent.usage. The same entries contribute to both views (one entry, multiple scope tags).
• Sub-teams — When a Team is nested inside another Team, the nested team’s entries carry both team_usage_id tags, rolling up into the parent automatically.
• Sub-pipeline rollup — Memory summarization, reliability validator/editor, culture, policy, and sub-agent calls dispatched by team members inherit the team scope via context variables.
• Retry idempotency — The registry is keyed by entry_id. Retried requests replace their prior entry instead of double-counting.
• JSON snapshot — Call team.usage.to_dict() for a flat dict suitable for logs and dashboards.

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Per-Member Breakdown

print("=== Team total ===")
print(team.usage.to_dict())

print("\n=== Per-member ===")
for entity in team.entities:
    print(f"{entity.name}: {entity.usage.to_dict()}")

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Legacy Migration

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Related Documentation

• Usage Registry — Architecture, scope tags, persistence
• Agent Metrics — Per-member scoped view
• Task Metrics — Per-task scoped view
• Chat Metrics — Per-session scoped view