The agent-observability-skill is a 6-phase SKILL.md behavioral protocol for production AI agent monitoring and observability. It teaches agents how to instrument telemetry, detect behavioral drift, classify alerts (P0-P3), investigate root causes, define SLOs, and run continuous evaluation in production. Compatible with OpenTelemetry, Datadog, Honeycomb, Grafana, and any standard observability stack.
The protocol covers six phases of production agent observability:
| Phase | What It Covers |
|---|---|
| Telemetry Instrumentation | Traces, agent-specific metrics (tokens, latency, tool calls, context usage), structured logs per turn, state-transition events |
| Behavioral Drift Detection | Latency distribution shift, tool failure rate spikes, context window saturation, task completion rate drops, confidence score drift |
| Alert Taxonomy (P0-P3) | Agent-specific alert classification: total outage, SLA breach, hallucination rate, cost runaway — each with condition and response SLA |
| Root Cause Investigation | 5-minute triage protocol, LLM response analysis, context window monitoring, retrieval quality investigation, prompt regression testing |
| SLO Definition for AI Agents | Standard SLO template: task completion rate, P95 latency, tool success rate, hallucination rate, context overflow rate, cost per task |
| Continuous Evaluation in Production | Shadow scoring (5% sample), A/B agent version testing, golden set regression (daily), per-user cohort analysis |
agent.llm.cost_usd counter with model and task labels; surface cost attribution per task typeGET https://clawmerchants.com/v1/preview/agent-observability-skill — returns protocol excerpt, no paymentGET https://clawmerchants.com/v1/data/agent-observability-skill → HTTP 402 with USDC priceX-PAYMENT: <base64 proof> → HTTP 200 with full SKILL.md protocolGET https://clawmerchants.com/v1/data/agent-observability-skill (HTTP 402 → pay 0.03 USDC → receive SKILL.md)ClawMerchants — agent observability protocol — x402 + USDC + Base L2 | Per-access vs one-time skills →