> ## Documentation Index
> Fetch the complete documentation index at: https://axiom.co/docs/llms.txt
> Use this file to discover all available pages before exploring further.

<AgentInstructions>

## Submitting Feedback

If you encounter incorrect, outdated, or confusing documentation on this page, submit feedback:

POST https://axiom.co/docs/feedback

```json
{
  "path": "/ai-engineering/observe/gen-ai-attributes",
  "feedback": "Description of the issue"
}
```

Only submit feedback when you have something specific and actionable to report.

</AgentInstructions>

# Generative AI attributes

> Understand the key attributes that your generative AI app sends to Axiom.

After you instrument your app, every LLM call sends a detailed span to your Axiom dataset. The spans are enriched with standardized `gen_ai.*` attributes that make your AI interactions easy to query and analyze.

Key attributes include the following:

## Span identification

* `gen_ai.capability.name`: The high-level capability name you defined in `withSpan`.
* `gen_ai.step.name`: The specific step within the capability.
* `gen_ai.operation.name`: The operation type. For example: `chat`, `execute_tool`.

## Model information

* `gen_ai.provider.name`: The model provider. For example: `openai`, `anthropic`.
* `gen_ai.request.model`: The model requested for the completion.
* `gen_ai.response.model`: The model that actually fulfilled the request.
* `gen_ai.output.type`: The output type. For example: `text`, `json`.

## Token usage

* `gen_ai.usage.input_tokens`: The number of tokens in the prompt.
* `gen_ai.usage.output_tokens`: The number of tokens in the generated response.

## Messages

* `gen_ai.input.messages`: The full, rendered prompt or message history sent to the model (as a JSON string).
* `gen_ai.output.messages`: The full response from the model (as a JSON string).
* `gen_ai.response.finish_reasons`: The reason the model stopped generating tokens. For example: `stop`, `tool-calls`.
* `gen_ai.response.id`: The unique identifier for the model response.

## Tool attributes

* `gen_ai.tool.name`: The name of the executed tool.
* `gen_ai.tool.call.arguments`: The arguments passed to the tool (as a JSON string).
* `gen_ai.tool.call.result`: The result returned by the tool (as a JSON string).

## Additional attributes

For a more thorough list of attributes, see the [OpenTelemetry Semantic Conventions for Generative AI](https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-spans/).

## What’s next?

After capturing and analyzing production telemetry:

* [Visualize traces](/query-data/traces) in Console.
* Use the new insights to [iterate](/ai-engineering/iterate) on your capability.