# Strands Agents
This page explains how to instrument a [Strands Agents](https://strandsagents.com/latest/) agent, how spans are identified, and how evaluation fields are extracted.
**Topics**
+ [Instrument your agent](#strands-instrument)
+ [How spans are identified](#strands-span-identification)
+ [How evaluation fields are extracted](#strands-extraction)
+ [From event records](#strands-extraction-event-records)
+ [From inline span events](#strands-extraction-inline-events)
+ [Example spans with event records](#strands-examples-with)
+ [Example spans without event records](#strands-examples-without)
## Instrument your agent
The Strands Agents SDK includes built-in telemetry and requires no additional instrumentation library. It produces spans and event records under the scope name `strands.telemetry.tracer`. When deployed on Amazon Bedrock AgentCore Runtime with the AWS Distro for OpenTelemetry (ADOT), the Runtime injects the `session.id` attribute and exports spans and event records automatically.
**Note**
Instrumentation is one step in setting up observability. To export telemetry for evaluation, complete the full setup in [Set up observability](supported-frameworks.md#supported-frameworks-setup).
## How spans are identified
Strands sets the `gen_ai.operation.name` attribute on each span. The evaluation service uses this attribute to classify spans:
| Span type | Identifying attribute | Example span name |
| --- | --- | --- |
| Invoke agent | `gen_ai.operation.name` = `invoke_agent` | `invoke_agent TravelAgent` |
| Execute tool | `gen_ai.operation.name` = `execute_tool` | `execute_tool search_flights` |
| Inference | `gen_ai.operation.name` = `chat` | `chat` |
## How evaluation fields are extracted
The location of the conversation content depends on how telemetry was collected. When ADOT splits telemetry, the content is in a separate event record. When telemetry is not split, the content stays on the span as inline events. For more information, see [Spans, event records, and telemetry signals](supported-frameworks-telemetry.md). The identifying attribute (`gen_ai.operation.name`) is on the span in both cases.
### From event records
When telemetry is split, the service reads content from the event record correlated to each span:
+ **User prompt**: from the agent input messages (`input.messages`), the content of the message with a user role.
+ **Agent response**: from the agent output messages (`output.messages`), the content of the message with an assistant role.
+ **Tool call**: the tool name from the `gen_ai.tool.name` attribute on the execute tool span. The tool arguments and result come from that span’s event record (`input` and `output`).
For examples, see [Example spans with event records](#strands-examples-with).
### From inline span events
When telemetry is not split, the same content is carried in inline span events instead of a separate event record:
+ **User prompt**: from the `gen_ai.user.message` event, the `content` attribute.
+ **Agent response**: from the `gen_ai.choice` event, the `message` attribute.
+ **Tool call**: the tool name from the `gen_ai.tool.name` attribute on the span. The tool arguments come from the `gen_ai.tool.message` event, and the result comes from the `gen_ai.choice` event.
For examples, see [Example spans without event records](#strands-examples-without).
## Example spans with event records
When telemetry is split, the span carries the identifying attributes and the content lives in a correlated event record. The following examples are from a Strands travel-planning agent deployed on Amazon Bedrock AgentCore Runtime.
**Note**
These examples are not complete spans. They show representative data from a real agent interaction, with some fields omitted and long values truncated for readability.
**Example**
The `gen_ai.operation.name` attribute (`invoke_agent`) identifies this as an invoke agent span. The `gen_ai.agent.tools` attribute lists the tools available to the agent.
```
{
"traceId": "69e9cc4771d7cabe0d8e8cea33b6b338",
"spanId": "d24936b8989b6d42",
"parentSpanId": "0ff3498548044e4b",
"name": "invoke_agent TravelAgent",
"kind": "INTERNAL",
"scope": {
"name": "strands.telemetry.tracer",
"version": ""
},
"startTimeUnixNano": 1776929864011990383,
"endTimeUnixNano": 1776929869634304466,
"durationNano": 5622314083,
"attributes": {
"gen_ai.operation.name": "invoke_agent",
"gen_ai.system": "strands-agents",
"gen_ai.agent.name": "TravelAgent",
"gen_ai.request.model": "us.anthropic.claude-sonnet-4-20250514-v1:0",
"gen_ai.usage.input_tokens": 983,
"gen_ai.usage.output_tokens": 232,
"gen_ai.usage.total_tokens": 1215,
"gen_ai.agent.tools": "[\"search_flights\", \"book_flight\", \"search_hotels\", \"book_hotel\", \"search_activities\", \"book_activity\"]",
"session.id": "sea-nyc-trip-2-turns-adot_v17-20260423003743"
},
"status": {
"code": "OK"
}
}
```
The correlated event record carries the conversation content. The user prompt is the user-role message in `input.messages`, and the agent response is the assistant-role message in `output.messages`.
```
{
"spanId": "d24936b8989b6d42",
"traceId": "69e9cc4771d7cabe0d8e8cea33b6b338",
"scope": {
"name": "strands.telemetry.tracer"
},
"body": {
"input": {
"messages": [
{
"role": "user",
"content": "Hey, how can you help me"
}
]
},
"output": {
"messages": [
{
"role": "assistant",
"content": {
"message": "Hi there! I'm your travel planning assistant ...",
"finish_reason": "end_turn"
}
}
]
}
}
}
```
The `gen_ai.operation.name` attribute (`execute_tool`) identifies this as an execute tool span. The `gen_ai.tool.name` attribute holds the tool name.
```
{
"traceId": "69e9cc4d132b180909ba49f613f273dd",
"spanId": "fff785ce12d6fda8",
"parentSpanId": "96915bf5ecc78743",
"name": "execute_tool search_flights",
"kind": "INTERNAL",
"scope": {
"name": "strands.telemetry.tracer",
"version": ""
},
"startTimeUnixNano": 1776929872258292842,
"endTimeUnixNano": 1776929872259611427,
"durationNano": 1318585,
"attributes": {
"gen_ai.operation.name": "execute_tool",
"gen_ai.tool.name": "search_flights",
"gen_ai.tool.call.id": "tooluse_hiWwdtThuD67G5cK8cp5mj",
"gen_ai.tool.status": "success",
"gen_ai.tool.description": "Search for available flights between cities.",
"session.id": "sea-nyc-trip-2-turns-adot_v17-20260423003743"
},
"status": {
"code": "OK"
}
}
```
The correlated event record carries the tool input (arguments) and output (result).
```
{
"spanId": "fff785ce12d6fda8",
"traceId": "69e9cc4d132b180909ba49f613f273dd",
"scope": {
"name": "strands.telemetry.tracer"
},
"body": {
"input": {
"messages": [
{
"role": "tool",
"content": {
"content": "{\"origin\": \"SEA\", \"destination\": \"NYC\", \"date\": \"2025-03-15\"}",
"role": "tool",
"id": "tooluse_hiWwdtThuD67G5cK8cp5mj"
}
}
]
},
"output": {
"messages": [
{
"role": "assistant",
"content": {
"message": "[{\"text\": \"{\\\"origin\\\": \\\"SEA\\\", \\\"destination\\\": \\\"NYC\\\", \\\"flights\\\": [ ... ]}\"}]",
"id": "tooluse_hiWwdtThuD67G5cK8cp5mj"
}
}
]
}
}
}
```
## Example spans without event records
When telemetry is not split, the same content is carried in inline span events on the span, with no separate event record. The following examples are from a Strands travel-planning agent.
**Note**
These examples are not complete spans. They show representative data from a real agent interaction, with some fields omitted and long values truncated for readability.
**Example**
The `gen_ai.user.message` event holds the user prompt, and the `gen_ai.choice` event holds the agent response.
```
{
"traceId": "69e9cc4771d7cabe0d8e8cea33b6b338",
"spanId": "d2ee0e4765cc773e",
"name": "invoke_agent TravelAgent",
"kind": "INTERNAL",
"scope": {
"name": "strands.telemetry.tracer"
},
"attributes": {
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.name": "TravelAgent",
"session.id": "sea-nyc-trip-2-turns-unified"
},
"events": [
{
"name": "gen_ai.user.message",
"attributes": {
"content": "[{\"text\": \"Hey, how can you help me\"}]"
}
},
{
"name": "gen_ai.choice",
"attributes": {
"message": "Hi there! I'm your travel planning assistant ...",
"finish_reason": "end_turn"
}
}
]
}
```
The `gen_ai.tool.message` event holds the tool arguments, and the `gen_ai.choice` event holds the tool result.
```
{
"traceId": "69e9cc4d132b180909ba49f613f273dd",
"spanId": "0a988e27758ebb53",
"name": "execute_tool search_flights",
"kind": "INTERNAL",
"scope": {
"name": "strands.telemetry.tracer"
},
"attributes": {
"gen_ai.operation.name": "execute_tool",
"gen_ai.tool.name": "search_flights",
"gen_ai.tool.call.id": "tooluse_JuGterOaZfQV2c55Rp3S7C",
"gen_ai.tool.status": "success",
"session.id": "sea-nyc-trip-2-turns-unified"
},
"events": [
{
"name": "gen_ai.tool.message",
"attributes": {
"content": "{\"origin\": \"SEA\", \"destination\": \"NYC\", \"date\": \"2025-03-15\"}",
"role": "tool",
"id": "tooluse_JuGterOaZfQV2c55Rp3S7C"
}
},
{
"name": "gen_ai.choice",
"attributes": {
"message": "[{\"text\": \"{\\\"origin\\\": \\\"SEA\\\", \\\"destination\\\": \\\"NYC\\\", \\\"flights\\\": [ ... ]}\"}]",
"id": "tooluse_JuGterOaZfQV2c55Rp3S7C"
}
}
]
}
```