# AI Observability Telemetry Requirements - GenAI Attributes

> Source: <https://signoz.io/docs/ai-observability-telemetry-requirements>
> Published: 2026-09-29 00:00:00+00:00

[AI Observability](https://signoz.io/docs/ai-observability/) reads these attributes from your spans. A panel stays empty until your spans carry the attributes that it uses. Most names come from the [OpenTelemetry GenAI semantic conventions](https://opentelemetry.io/docs/specs/semconv/gen-ai/). If your instrumentation uses other names, map them in [Attribute Mapping](https://signoz.io/docs/ai-observability-attribute-mapping/).

## Span attributes

| Attribute | Used by | 
|---|---|
| `gen_ai.request.model` | All LLM panels and the **model** filter. SigNoz counts a span with this attribute as an LLM call. | 
| `gen_ai.provider.name` | **Cost by provider** and the**provider** filter. | 
| `gen_ai.usage.input_tokens` ,`gen_ai.usage.output_tokens` | Token panels and cost. | 
| `gen_ai.usage.cache_read.input_tokens` ,`gen_ai.usage.cache_creation.input_tokens` | Cache token panels, cache cost, and **Prompt cache hit ratio** . | 
| `gen_ai.server.ttft` | **TTFT (p95)** and**Time to first token** . Streaming instrumentations, such as OpenLIT, send this attribute in seconds. | 
| `gen_ai.response.finish_reasons` | **Finish reasons** . | 
| `gen_ai.tool.name` | All **Tool calls** panels. SigNoz counts a span with this attribute as a tool call. | 
| `gen_ai.agent.name` | Agent spans for the **Per-trace usage** panels. | 

An AI trace is a trace with at least one LLM, tool, or agent span. Error panels use the error status of the span, not an attribute.

## Resource attributes

| Attribute | Used by | 
|---|---|
| `deployment.environment` | The **environment** filter. | 
| `service.name` | The **service_name** filter and**Cost by service** . | 

Tool spans do not carry a model. As a result, the **model** and **provider** filters do not affect the **Tool calls** panels or **Calls per AI trace**.

## Cost attributes

You do not send cost. When SigNoz receives a span, it calculates cost from the token counts and the price of the model in [Model pricing](https://signoz.io/docs/ai-observability-model-pricing/). SigNoz writes the total to `signoz.gen_ai.usage.tokens.cost`, and one cost attribute for each token type:

- `signoz.gen_ai.usage.input_tokens.cost`
- `signoz.gen_ai.usage.output_tokens.cost`
- `signoz.gen_ai.usage.cache_read.input_tokens.cost`
- `signoz.gen_ai.usage.cache_write.input_tokens.cost`

## Next steps

- [AI Observability overview](https://signoz.io/docs/ai-observability/) : see cost, tokens, latency, and tool calls on one dashboard.
- [Attribute Mapping](https://signoz.io/docs/ai-observability-attribute-mapping/) : map other attribute names to the GenAI names.
- [LLM Observability integrations](https://signoz.io/docs/llm-observability/) : instrument OpenAI, Anthropic, LiteLLM, CrewAI, and other frameworks.

## Get Help

If you need help with the steps in this topic, please reach out to us on [SigNoz Community Slack](https://signoz.io/slack/). If you are a SigNoz Cloud user, please use in product chat support located at the bottom right corner of your SigNoz instance or contact us at [cloud-support@signoz.io](mailto:cloud-support@signoz.io).