Agent Observability

Monitor AI agent behavior with logs, traces, metrics, and cost telemetry. This skill covers the full observability stack for LLM-powered applications: from raw Prometheus counters to Grafana dashboards, OpenTelemetry tracing, structured logging, cost tracking, SLO definition, and PII redaction.

When to Use

Apply this skill whenever you operate:

• Autonomous AI agents that make multi-step tool calls (e.g., coding agents, support agents, data-pipeline agents).
• LLM-backed APIs serving chat completions, summarisation, or classification behind a REST or gRPC gateway.
• RAG pipelines where a retriever fetches context from a vector store before prompting a model.
• Multi-agent orchestrations (crew-style or graph-based) where several agents collaborate on a single task.
• Batch inference jobs that process thousands of prompts against a model endpoint.

Key signals that you need this skill: