Monitor your OpenAI Agents SDK agents in production.

Agents built with the OpenAI Agents SDK run tools, hand off between agents and call models in a loop. AgentPing captures one record per run so you can see what each cost, whether it ran, and whether the output held up.

Track your first AI workflow Read the TypeScript SDK docs

Production AI in OpenAI Agents SDK fails quietly.

An OpenAI Agents SDK agent can hand off, retry and call a model several times in a single run. The provider console shows tokens by API key, not which agent or run spent them, and nothing tells you when a scheduled agent simply stopped firing.

Wire it up in a few lines.

Initialise once, then wrap the agent run. Hand-offs, tool calls and model calls inside the wrapper roll up into a single run with cost, status and latency.

Install

          install
          OpenAI Agents SDK
        

npm install @agentping/sdk

Instrument

          example · typescript
          OpenAI Agents SDK
        

import { init, run } from "@agentping/sdk";
import { Agent, run as runAgent } from "@openai/agents";

init({ apiKey: process.env.AGENTPING_API_KEY, agent: "support-triage" });

// Wrap the run; hand-offs and tool calls roll up into one record.
await run({ agent: "support-triage", customerId: "acme-corp" }, async () => {
  return await runAgent(agent, input);
});

Full setup, environment variables and options are in the TypeScript SDK docs.

What AgentPing tracks for OpenAI Agents SDK.

Cost per agent run, attributed to the customer and feature you tag.
Tool calls and agent handoffs captured as a single run trace.
Run status, latency and retry count, so a stuck run is visible.
Missed run alerts for agents on a schedule.
Optional output quality scoring on a sampled subset of runs.

Read the TypeScript SDK docs Heartbeat webhook docs

What you see in the dashboard.

A run list for OpenAI Agents SDK, each row showing cost, status and latency, filterable by agent, customer and feature.
Cost by agent, customer and feature, so you can see which accounts and features drive AI spend, not just one provider total.
An incident the moment a scheduled run misses its window or a cost spike breaks its baseline, delivered to Slack, email, PagerDuty or a webhook.
A quality trend once you turn on scoring, so a regression in your OpenAI Agents SDK output shows up as a falling line, not a support ticket.

Does this work with agent handoffs?

Yes. A handoff between agents is captured within the run trace, so a multi-agent run is one record with the tool calls and child runs attached, and the cost is attributed to the run that spent it.

Will it slow my agent down?

No. The SDK never blocks your agent. Telemetry sends on a background thread with a hard 2-second timeout, and if AgentPing is unreachable your agent runs as if nothing is installed.

What does it cost to monitor OpenAI Agents SDK?

There is a free plan with no card and no time limit, enough to wire up your first agents. Paid plans start at $99/month with named limits and no metered billing, so the bill never surprises you. Annual billing is two months free.

Does AgentPing see my prompts and outputs?

Only if you choose to send them. By default AgentPing prices runs from model and token counts and tracks status and timing, which needs no prompt or output content. Payload capture for quality scoring is opt-in and configurable per agent.

Monitor your OpenAI Agents SDK AI workflows.

Send one run from OpenAI Agents SDK and see cost, status and latency. Then add an alert for cost spikes or missed runs.

Track your first AI workflow Read the TypeScript SDK docs

Spend, cost attribution → Pulse, live monitoring → Verify, quality scoring →