Instrumenting Agents with Sigil

Moving AI agents from local development to production requires shifting from manual prompt testing to automated observability. The Grafana Sigil SDK provides an OpenTelemetry-native layer that allows developers to capture agent behavior without altering core business logic.

Implementation involves three lightweight wrappers:

  1. Client Setup: Configuring the endpoint, instance ID, and API key.
  2. Generation Wrapping: Wrapping the generation stream to record traces and metrics enriched with metadata.
  3. Tool Execution: Using sigil_client.start_tool_execution to capture the inputs, outputs, and execution duration of every tool call.

Production Observability and Analysis

Once instrumented, Grafana Cloud provides a centralized dashboard to monitor agent health, latency, error rates, and token usage. Key features include:

  • Performance Metrics: Tracking time-to-first-token and latency across concurrent requests.
  • Tool Inspection: A dedicated tab to audit tool interactions, allowing developers to correlate specific conversations with tool inputs and outputs.
  • AI Evaluations: Implementing "AI judges" to score response quality and trigger alerts when the agent produces undesirable output.

Automating the Remediation Loop

To avoid manual investigation, developers can automate the "observe-analyze-improve" loop using the Grafana Slack app and Claude.

  • Automated Investigation: By tagging the Grafana assistant in Slack, the system automatically correlates telemetry data, identifies bottlenecks (such as rate limit exhaustion or latency spikes), and provides a diagnostic report.
  • Remediation: Developers can then pass this diagnostic data to Claude to generate a concrete implementation plan, effectively closing the loop between identifying a production issue and generating the code or prompt fix.