naming.mdx

title	Naming Your Agents
sidebar_order	12
description	Set the agent name so Sentry can identify, filter, and alert on individual agents in the AI Agents Dashboard.
keywords	AI agents agent name gen_ai.agent.name agent monitoring agent identification

Sentry uses the gen_ai.agent.name span attribute to identify agents in the AI Agents Dashboard. Without a name, you won't be able to filter for a specific agent, group results by agent, or set up alerts for individual agents.

Quick Reference

Framework	Platform	How to Name
OpenAI Agents SDK	Python	Agent(name="...")
Pydantic AI	Python	Agent(..., name="...")
LangChain	Python	create_agent(model, tools, name="...")
LangGraph	Python	.compile(name="...") or create_react_agent(..., name="...")
Vercel AI SDK	JS	experimental_telemetry: { functionId: "..." } on generateText or ToolLoopAgent
LangGraph	JS	.compile({ name: "..." }) or createReactAgent({ name: "..." })
LangChain	JS	createAgent({ name: "..." })
Mastra	JS	Agent({ id: "...", name: "..." })
.NET (M.E.AI)	.NET	options.Experimental.AgentName = "..."
Other / raw LLM clients	Any	Manual instrumentation

Framework Integrations

Most AI agent frameworks have a built-in name parameter that Sentry picks up automatically.

Python

OpenAI Agents SDK

The name parameter is required by the SDK. Sentry reads it automatically.

from openai import agents

agent = agents.Agent(
    name="Weather Agent",
    instructions="You are a helpful weather assistant.",
    model="gpt-4o-mini",
)

OpenAI Agents integration docs

Pydantic AI

Pass name when creating the agent.

from pydantic_ai import Agent

agent = Agent(
    "openai:gpt-4o-mini",
    name="Customer Support Agent",
    system_prompt="You help customers with their questions.",
)

Pydantic AI integration docs

LangChain

Pass name to create_agent.

from langchain.agents import create_agent
from langchain.chat_models import init_chat_model

model = init_chat_model("gpt-4o-mini", model_provider="openai")
agent = create_agent(model, tools, name="dice_agent")

LangChain integration docs

LangGraph

Pass name to StateGraph.compile() or create_react_agent.

from langgraph.graph import StateGraph

graph = StateGraph(AgentState)
# ... add nodes and edges ...
agent = graph.compile(name="dice_agent")

Or with the prebuilt helper:

from langgraph.prebuilt import create_react_agent

agent = create_react_agent(model, tools, name="dice_agent")

LangGraph integration docs

JavaScript / Node.js

Vercel AI SDK

Set functionId in experimental_telemetry — Sentry uses this as the agent identifier. This works for both generateText and ToolLoopAgent:

import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const result = await generateText({
  model: openai("gpt-4o"),
  prompt: "Tell me a joke",
  experimental_telemetry: {
    isEnabled: true,
    functionId: "joke_agent",
  },
});

For the ToolLoopAgent class, set functionId in the constructor:

import { ToolLoopAgent } from "ai";
import { openai } from "@ai-sdk/openai";

const agent = new ToolLoopAgent({
  model: openai("gpt-4o"),
  tools: {
    /* ... */
  },
  experimental_telemetry: {
    isEnabled: true,
    functionId: "weather_agent",
  },
});

<PlatformLink platform="javascript.node" to="/configuration/integrations/vercelai/"

Vercel AI SDK integration docs

LangGraph

Pass name to .compile() or createReactAgent.

import { StateGraph } from "@langchain/langgraph";

const graph = new StateGraph(AgentState);
// ... add nodes and edges ...
const agent = graph.compile({ name: "weather_agent" });

Or with the prebuilt helper:

import { createReactAgent } from "@langchain/langgraph/prebuilt";

const agent = createReactAgent({
  llm: model,
  tools: [getWeather],
  name: "weather_agent",
});

<PlatformLink platform="javascript.node" to="/configuration/integrations/langgraph/"

LangGraph integration docs

LangChain

Pass name to createAgent.

import { createAgent } from "langchain";

const agent = createAgent({
  llm: model,
  tools: [getWeather],
  name: "weather_agent",
});

<PlatformLink platform="javascript.node" to="/configuration/integrations/langchain/"

LangChain integration docs

Mastra

Mastra requires both id and name on the agent definition. The Mastra exporter sends the name to Sentry automatically.

const agent = new Agent({
  id: "weather-agent",
  name: "Weather Agent",
  instructions: "You are a helpful weather assistant.",
  model: "openai/gpt-4o",
});

Mastra integration docs

.NET

Set AgentName in the Sentry AI instrumentation options.

var client = new OpenAI.Chat.ChatClient("gpt-4o-mini", apiKey)
    .AsIChatClient()
    .AddSentry(options =>
    {
        options.Experimental.AgentName = "WeatherAgent";
    });

See the .NET AI Agents instrumentation docs for the full setup.

Manual Instrumentation

For frameworks without built-in naming, or when using raw LLM clients (OpenAI, Anthropic, Google GenAI, LiteLLM), wrap your agent logic in an invoke_agent span and set gen_ai.agent.name.

Python

import sentry_sdk

with sentry_sdk.start_span(
    op="gen_ai.invoke_agent",
    name="invoke_agent Weather Agent",
) as span:
    span.set_data("gen_ai.agent.name", "Weather Agent")
    span.set_data("gen_ai.request.model", "gpt-4o-mini")

    result = my_agent.run()

    span.set_data("gen_ai.usage.input_tokens", result.usage.input_tokens)
    span.set_data("gen_ai.usage.output_tokens", result.usage.output_tokens)

See Python manual instrumentation for full span attributes.

JavaScript

import * as Sentry from "@sentry/node";

await Sentry.startSpan(
  {
    op: "gen_ai.invoke_agent",
    name: "invoke_agent Weather Agent",
    attributes: {
      "gen_ai.agent.name": "Weather Agent",
      "gen_ai.request.model": "gpt-4o-mini",
    },
  },
  async (span) => {
    const result = await myAgent.run();

    span.setAttribute("gen_ai.usage.input_tokens", result.usage.inputTokens);
    span.setAttribute("gen_ai.usage.output_tokens", result.usage.outputTokens);
  }
);

See JavaScript manual instrumentation for full span attributes.

Next Steps

• AI Agents Dashboard — view and filter agents by name
• Data Privacy — control what data is sent to Sentry
• Model Costs — track token usage and estimated costs