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DecimalAI’s deepest integration. Pass the Agent object to install() and DecimalAI introspects tools, model config, handoffs, and guardrails — no manual manifest registration needed.

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Install

pip install decimalai

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Use

import decimalai
decimalai.init(api_key="dai_sk_...", openai_agents=True)

# Or for more control:
from decimalai.openai_agents import install
from agents import Agent, Runner

agent = Agent(name="my-agent", instructions="You are helpful.", tools=[...])
install(agent=agent)  # introspects tools, model, and handoffs

result = Runner.run_sync(agent, "Hello!")
# Trace auto-captured with full manifest

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What gets captured

  • All LLM generations with model, tokens, latency
  • Tool calls with inputs and outputs
  • Handoffs between agents (multi-agent flows)
  • Guardrail checks and results
  • Auto-detected manifest from agent config (tools, model, instructions, sub-agents)

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When to use the explicit install(agent=...) form

The flag form (init(openai_agents=True)) hooks into the SDK at module level. Use the explicit install(agent=...) form when you need DecimalAI to introspect the full agent object — tool schemas, sub-agent topology, the resolved instruction prompt. Without the agent= argument, manifest detection captures tool names only.

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What’s next

Multi-agent guide

How handoffs and sub-agent calls show up in the trace tree.

Manifests

Override the auto-detected manifest when you need explicit control.