Monitor LLMs and agentic apps: performance, token/cost, response quality, and workflow orchestration.
Monitor LLMs and agentic apps: performance, token/cost, response quality, and workflow orchestration. Use when the user asks about LLM monitoring, GenAI observability, or AI cost/quality.This is the skill's description: the text your AI reads to decide when the skill applies.
elastic-llm-obs/SKILL.md
---
name: observability-llm-obs
description: >
Monitor LLMs and agentic apps: performance, token/cost, response quality, and workflow
orchestration. Use when the user asks about LLM monitoring, GenAI observability,
or AI cost/quality.
metadata:
author: elastic
version: 0.1.0
---
# LLM and Agentic Observability
Answer user questions about monitoring LLMs and agentic components using **data ingested into Elastic** only. Focus on
LLM performance, cost and token utilization, response quality, and call chaining or agentic workflow orchestration. Use
**ES|QL**, Elasticsearch APIs, and (where needed) Kibana APIs. Do not rely on Kibana UI; the skill works without it. A
given deployment typically uses **one or more** ingestion paths (APM/OTLP traces **and/or** integration metrics/logs)—
discover what is available before querying.
## Where to look
- **Trace and metrics data (APM / OTel):** Trace data in Elastic is stored in **`traces*`** when collected by the
Elastic APM Agent, and in **`traces-generic.otel-default`** (and similar) when collected by OpenTelemetry. Use the
generic pattern **`traces*`** to find all trace data regardless of source. When the application is instrumented with
OpenTelemetry (e.g. Elastic